Relational Algebra in Spatial Decision Support Systems Ontologies.

PubMed

Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos

2017-01-01

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.

SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2008-12-01

In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:

The anatomy of decision support during inpatient care provider order entry (CPOE): Empirical observations from a decade of CPOE experience at Vanderbilt

PubMed Central

Miller, Randolph A.; Waitman, Lemuel R.; Chen, Sutin; Rosenbloom, S. Trent

2006-01-01

The authors describe a pragmatic approach to the introduction of clinical decision support at the point of care, based on a decade of experience in developing and evolving Vanderbilt’s inpatient “WizOrder” care provider order entry (CPOE) system. The inpatient care setting provides a unique opportunity to interject CPOE-based decision support features that restructure clinical workflows, deliver focused relevant educational materials, and influence how care is delivered to patients. From their empirical observations, the authors have developed a generic model for decision support within inpatient CPOE systems. They believe that the model’s utility extends beyond Vanderbilt, because it is based on characteristics of end-user workflows and on decision support considerations that are common to a variety of inpatient settings and CPOE systems. The specific approach to implementing a given clinical decision support feature within a CPOE system should involve evaluation along three axes: what type of intervention to create (for which the authors describe 4 general categories); when to introduce the intervention into the user’s workflow (for which the authors present 7 categories), and how disruptive, during use of the system, the intervention might be to end-users’ workflows (for which the authors describe 6 categories). Framing decision support in this manner may help both developers and clinical end-users plan future alterations to their systems when needs for new decision support features arise. PMID:16290243

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

PubMed

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

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.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

PubMed Central

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

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

The Feasibility of a Decision Support System for the Determination of Source Selection Evaluation Criteria

DTIC Science & Technology

1984-09-01

is not only difficult and time consuming , but also crucial to the success of the project, the question is whether a decision support system designed...KtI I - uAujvhIMtf IENE In THE FEASIBILITY OF A DECISION SUPPORT SYSTEM FOR THE DETERMINATION OF SOURCE SELECTION EVALUATION ’CRITERIA THESIS .2...INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DZM=0N STATEMENT A ,’r !’ILMILSHIM S /8 4 THE FEASIBILITY OF A DECISION SUPPORT SYSTEM FOR

Semantic Clinical Guideline Documents

PubMed Central

Eriksson, Henrik; Tu, Samson W.; Musen, Mark

2005-01-01

Decision-support systems based on clinical practice guidelines can support physicians and other health-care personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner, perform consistency checks, and use the guidelines directly in decision-support systems. Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support. PMID:16779037

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

NASA Astrophysics Data System (ADS)

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

2003-09-01

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

Using Visualization in Cockpit Decision Support Systems

NASA Technical Reports Server (NTRS)

Aragon, Cecilia R.

2005-01-01

In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

SANDS: A Service-Oriented Architecture for Clinical Decision Support in a National Health Information Network

PubMed Central

Wright, Adam; Sittig, Dean F.

2008-01-01

In this paper we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. PMID:18434256

Clinical decision support provided within physician order entry systems: a systematic review of features effective for changing clinician behavior.

PubMed

Kawamoto, Kensaku; Lobach, David F

2003-01-01

Computerized physician order entry (CPOE) systems represent an important tool for providing clinical decision support. In undertaking this systematic review, our objective was to identify the features of CPOE-based clinical decision support systems (CDSSs) most effective at modifying clinician behavior. For this review, two independent reviewers systematically identified randomized controlled trials that evaluated the effectiveness of CPOE-based CDSSs in changing clinician behavior. Furthermore, each included study was assessed for the presence of 14 CDSS features. We screened 10,023 citations and included 11 studies. Of the 10 studies comparing a CPOE-based CDSS intervention against a non-CDSS control group, 7 reported a significant desired change in professional practice. Moreover, meta-regression analysis revealed that automatic provision of the decision support was strongly associated with improved professional practice (adjusted odds ratio, 23.72; 95% confidence interval, 1.75-infiniti). Thus, we conclude that automatic provision of decision support is a critical feature of successful CPOE-based CDSS interventions.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

PubMed

DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

Enabling Cross-Platform Clinical Decision Support through Web-Based Decision Support in Commercial Electronic Health Record Systems: Proposal and Evaluation of Initial Prototype Implementations

PubMed Central

Zhang, Mingyuan; Velasco, Ferdinand T.; Musser, R. Clayton; Kawamoto, Kensaku

2013-01-01

Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

Discusses knowledge-based decision-support systems that use artificial intelligence approaches. Addresses the issue of how to create an effective case-based reasoning system for complex and evolving domains, focusing on automated methods for system optimization and domain knowledge evolution that can supplement knowledge acquired from domain…

A Web-Based Tool to Support Data-Based Early Intervention Decision Making

ERIC Educational Resources Information Center

Buzhardt, Jay; Greenwood, Charles; Walker, Dale; Carta, Judith; Terry, Barbara; Garrett, Matthew

2010-01-01

Progress monitoring and data-based intervention decision making have become key components of providing evidence-based early childhood special education services. Unfortunately, there is a lack of tools to support early childhood service providers' decision-making efforts. The authors describe a Web-based system that guides service providers…

A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

NASA Astrophysics Data System (ADS)

Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

2007-06-01

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study.

PubMed

Amland, Robert C; Lyons, Jason J; Greene, Tracy L; Haley, James M

2015-10-01

To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients' designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. 'Suspected infection' was the established gold standard to assess clinical decision support clinimetric performance. A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying 'suspected infection' as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis.

Preparing for a decision support system.

PubMed

Callan, K

2000-08-01

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.

Web-based Traffic Noise Control Support System for Sustainable Transportation

NASA Astrophysics Data System (ADS)

Fan, Lisa; Dai, Liming; Li, Anson

Traffic noise is considered as one of the major pollutions that will affect our communities in the future. This paper presents a framework of web-based traffic noise control support system (WTNCSS) for a sustainable transportation. WTNCSS is to provide the decision makers, engineers and publics a platform to efficiently access the information, and effectively making decisions related to traffic control. The system is based on a Service Oriented Architecture (SOA) which takes the advantages of the convenience of World Wide Web system with the data format of XML. The whole system is divided into different modules such as the prediction module, ontology-based expert module and dynamic online survey module. Each module of the system provides a distinct information service to the decision support center through the HTTP protocol.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

PubMed Central

DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

Decision-support systems for natural-hazards and land-management issues

USGS Publications Warehouse

Dinitz, Laura; Forney, William; Byrd, Kristin

2012-01-01

Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

Toward the Modularization of Decision Support Systems

NASA Astrophysics Data System (ADS)

Raskin, R. G.

2009-12-01

Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.

Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

PubMed

Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

2015-07-01

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.

NED-IIS: An Intelligent Information System for Forest Ecosystem Management

Treesearch

W.D. Potter; S. Somasekar; R. Kommineni; H.M. Rauscher

1999-01-01

We view Intelligent Information System (IIS) as composed of a unified knowledge base, database, and model base. The model base includes decision support models, forecasting models, and cvsualization models for example. In addition, we feel that the model base should include domain specific porblems solving modules as well as decision support models. This, then,...

Web-based decision support system to predict risk level of long term rice production

NASA Astrophysics Data System (ADS)

Mukhlash, Imam; Maulidiyah, Ratna; Sutikno; Setiyono, Budi

2017-09-01

Appropriate decision making in risk management of rice production is very important in agricultural planning, especially for Indonesia which is an agricultural country. Good decision would be obtained if the supporting data required are satisfied and using appropriate methods. This study aims to develop a Decision Support System that can be used to predict the risk level of rice production in some districts which are central of rice production in East Java. Web-based decision support system is constructed so that the information can be easily accessed and understood. Components of the system are data management, model management, and user interface. This research uses regression models of OLS and Copula. OLS model used to predict rainfall while Copula model used to predict harvested area. Experimental results show that the models used are successfully predict the harvested area of rice production in some districts which are central of rice production in East Java at any given time based on the conditions and climate of a region. Furthermore, it can predict the amount of rice production with the level of risk. System generates prediction of production risk level in the long term for some districts that can be used as a decision support for the authorities.

Modular Architecture for Integrated Model-Based Decision Support.

PubMed

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

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.

A prototype knowledge-based decision support system for industrial waste management. Part 1: The decision support system

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

Boyle, C.A.; Baetz, B.W.

1998-12-31

Although there are a number of expert systems available which are designed to assist in resolving environmental problems, there is still a need for a system which would assist managers in determining waste management options for all types of wastes from one or more industrial plants, giving priority to sustainable use of resources, reuse and recycling. A prototype model was developed to determine the potentials for reuse and recycling of waste materials, to select the treatments needed to recycle waste materials or for treatment before disposal, and to determine potentials for co-treatment of wastes. A knowledge-based decision support system wasmore » then designed using this model. This paper describes the prototype model, the developed knowledge-based decision support system, the input and storage of data within the system and the inference engine developed for the system to determine the treatment options for the wastes. Options for sorting and selecting treatment trains are described, along with a discussion of the limitations of the approach and future developments needed for the system.« less

Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes.

PubMed

García-Sáez, Gema; Rigla, Mercedes; Martínez-Sarriegui, Iñaki; Shalom, Erez; Peleg, Mor; Broens, Tom; Pons, Belén; Caballero-Ruíz, Estefanía; Gómez, Enrique J; Hernando, M Elena

2014-03-01

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system. © 2014 Diabetes Technology Society.

Decision Support Systems (DSSs) For Contaminated Land Management - Gaps And Challenges

EPA Science Inventory

A plethora of information is available when considering decision support systems for risk-based management of contaminated land. Broad issues of what is contaminated land, what is a brownfield, and what is remediation are discussed in EU countries and the U.S. Making decisions ...

Texas urban triangle : creating a spatial decision support system for mobility policy and investments that shape the sustainable growth of Texas.

DOT National Transportation Integrated Search

2010-11-01

This project developed a GIS-based Spatial Decision Support System to help local, metropolitan, and state : jurisdictions and authorities in Texas understand the implications of transportation planning and : investment decisions, and plan appropriate...

The use of the Dutch Self-Sufficiency Matrix (SSM-D) to inform allocation decisions to public mental health care for homeless people.

PubMed

Lauriks, Steve; de Wit, Matty A S; Buster, Marcel C A; Fassaert, Thijs J L; van Wifferen, Ron; Klazinga, Niek S

2014-10-01

The current study set out to develop a decision support tool based on the Self-Sufficiency Matrix (Dutch version; SSM-D) for the clinical decision to allocate homeless people to the public mental health care system at the central access point of public mental health care in Amsterdam, The Netherlands. Logistic regression and receiver operating characteristic-curve analyses were used to model professional decisions and establish four decision categories based on SSM-D scores from half of the research population (Total n = 612). The model and decision categories were found to be accurate and reliable in predicting professional decisions in the second half of the population. Results indicate that the decision support tool based on the SSM-D is useful and feasible. The method to develop the SSM-D as a decision support tool could be applied to decision-making processes in other systems and services where the SSM-D has been implemented, to further increase the utility of the instrument.

Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care.

PubMed

Gadd, C S; Baskaran, P; Lobach, D F

1998-01-01

Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings.

Design, implementation, use, and preliminary evaluation of SEBASTIAN, a standards-based Web service for clinical decision support.

PubMed

Kawamoto, Kensaku; Lobach, David F

2005-01-01

Despite their demonstrated ability to improve care quality, clinical decision support systems are not widely used. In part, this limited use is due to the difficulty of sharing medical knowledge in a machine-executable format. To address this problem, we developed a decision support Web service known as SEBASTIAN. In SEBASTIAN, individual knowledge modules define the data requirements for assessing a patient, the conclusions that can be drawn using that data, and instructions on how to generate those conclusions. Using standards-based XML messages transmitted over HTTP, client decision support applications provide patient data to SEBASTIAN and receive patient-specific assessments and recommendations. SEBASTIAN has been used to implement four distinct decision support systems; an architectural overview is provided for one of these systems. Preliminary assessments indicate that SEBASTIAN fulfills all original design objectives, including the re-use of executable medical knowledge across diverse applications and care settings, the straightforward authoring of knowledge modules, and use of the framework to implement decision support applications with significant clinical utility.

System for selecting relevant information for decision support.

PubMed

Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana

2013-01-01

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.

Decision support systems in health economics.

PubMed

Quaglini, S; Dazzi, L; Stefanelli, M; Barosi, G; Marchetti, M

1999-08-01

This article describes a system addressed to different health care professionals for building, using, and sharing decision support systems for resource allocation. The system deals with selected areas, namely the choice of diagnostic tests, the therapy planning, and the instrumentation purchase. Decision support is based on decision-analytic models, incorporating an explicit knowledge representation of both the medical domain knowledge and the economic evaluation theory. Application models are built on top of meta-models, that are used as guidelines for making explicit both the cost and effectiveness components. This approach improves the transparency and soundness of the collaborative decision-making process and facilitates the result interpretation.

A decision-based perspective for the design of methods for systems design

NASA Technical Reports Server (NTRS)

Mistree, Farrokh; Muster, Douglas; Shupe, Jon A.; Allen, Janet K.

1989-01-01

Organization of material, a definition of decision based design, a hierarchy of decision based design, the decision support problem technique, a conceptual model design that can be manufactured and maintained, meta-design, computer-based design, action learning, and the characteristics of decisions are among the topics covered.

New approaches for real time decision support systems

NASA Technical Reports Server (NTRS)

Hair, D. Charles; Pickslay, Kent

1994-01-01

NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

Design and implementation of the standards-based personal intelligent self-management system (PICS).

PubMed

von Bargen, Tobias; Gietzelt, Matthias; Britten, Matthias; Song, Bianying; Wolf, Klaus-Hendrik; Kohlmann, Martin; Marschollek, Michael; Haux, Reinhold

2013-01-01

Against the background of demographic change and a diminishing care workforce there is a growing need for personalized decision support. The aim of this paper is to describe the design and implementation of the standards-based personal intelligent care systems (PICS). PICS makes consistent use of internationally accepted standards such as the Health Level 7 (HL7) Arden syntax for the representation of the decision logic, HL7 Clinical Document Architecture for information representation and is based on a open-source service-oriented architecture framework and a business process management system. Its functionality is exemplified for the application scenario of a patient suffering from congestive heart failure. Several vital signs sensors provide data for the decision support system, and a number of flexible communication channels are available for interaction with patient or caregiver. PICS is a standards-based, open and flexible system enabling personalized decision support. Further development will include the implementation of components on small computers and sensor nodes.

Scalable software architectures for decision support.

PubMed

Musen, M A

1999-12-01

Interest in decision-support programs for clinical medicine soared in the 1970s. Since that time, workers in medical informatics have been particularly attracted to rule-based systems as a means of providing clinical decision support. Although developers have built many successful applications using production rules, they also have discovered that creation and maintenance of large rule bases is quite problematic. In the 1980s, several groups of investigators began to explore alternative programming abstractions that can be used to build decision-support systems. As a result, the notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) problem-solving methods--domain-independent algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper highlights how developers can construct large, maintainable decision-support systems using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

Identifying the decision to be supported: a review of papers from environmental modelling and software

USGS Publications Warehouse

Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

2012-01-01

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for consideration by journal editors to aid them in filtering papers that use the term, “decision support”.

Development of prototype decision support systems for real-time freeway traffic routing. Volume I.

DOT National Transportation Integrated Search

1998-01-01

For a traffic management system (TMS) to improve traffic flow, TMS operators must develop effective routing strategies based on the data collected by the system. The purpose of this research was to build prototype decision support systems (DSS) for t...

Geospatial Data Fusion and Multigroup Decision Support for Surface Water Quality Management

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Osidele, O.; Green, R. T.; Xie, H.

2010-12-01

Social networking and social media have gained significant popularity and brought fundamental changes to many facets of our everyday life. With the ever-increasing adoption of GPS-enabled gadgets and technology, location-based content is likely to play a central role in social networking sites. While location-based content is not new to the geoscience community, where geographic information systems (GIS) are extensively used, the delivery of useful geospatial data to targeted user groups for decision support is new. Decision makers and modelers ought to make more effective use of the new web-based tools to expand the scope of environmental awareness education, public outreach, and stakeholder interaction. Environmental decision processes are often rife with uncertainty and controversy, requiring integration of multiple sources of information and compromises between diverse interests. Fusing of multisource, multiscale environmental data for multigroup decision support is a challenging task. Toward this goal, a multigroup decision support platform should strive to achieve transparency, impartiality, and timely synthesis of information. The latter criterion often constitutes a major technical bottleneck to traditional GIS-based media, featuring large file or image sizes and requiring special processing before web deployment. Many tools and design patterns have appeared in recent years to ease the situation somewhat. In this project, we explore the use of Web 2.0 technologies for “pushing” location-based content to multigroups involved in surface water quality management and decision making. In particular, our granular bottom-up approach facilitates effective delivery of information to most relevant user groups. Our location-based content includes in-situ and remotely sensed data disseminated by NASA and other national and local agencies. Our project is demonstrated for managing the total maximum daily load (TMDL) program in the Arroyo Colorado coastal river basin in Texas. The overall design focuses on assigning spatial information to decision support elements and on efficiently using Web 2.0 technologies to relay scientific information to the nonscientific community. We conclude that (i) social networking, if appropriately used, has great potential for mitigating difficulty associated with multigroup decision making; (ii) all potential stakeholder groups should be involved in creating a useful decision support system; and (iii) environmental decision support systems should be considered a must-have, instead of an optional component of TMDL decision support projects. Acknowledgment: This project was supported by NASA grant NNX09AR63G.

Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

PubMed

Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

2009-04-01

Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support.

PubMed

Xia, Eryu; Liu, Haifeng; Li, Jing; Mei, Jing; Li, Xuejun; Xu, Enliang; Li, Xiang; Hu, Gang; Xie, Guotong; Xu, Meilin

2017-01-01

Clinical decision support systems are information technology systems that assist clinical decision-making tasks, which have been shown to enhance clinical performance. Cluster analysis, which groups similar patients together, aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. Useful as it is, the application of cluster analysis in clinical decision support systems is less reported. Here, we describe the usage of cluster analysis in clinical decision support systems, by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles. This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians. We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes. These efforts represent a step toward promoting patient-centered care and enabling precision medicine.

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

PubMed

Yu, Peter Paul

2015-03-01

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.

Decision Support System for Disability Assessment and Intervention.

ERIC Educational Resources Information Center

Dowler, Denetta L.; And Others

1991-01-01

Constructed decision support system to aid referral of good candidates for rehabilitation from Social Security Administration to rehabilitation counselors. Three layers of system were gross screening based on policy guidelines, training materials, and interviews with experts; physical and mental functional capacity items derived from policy…

A decision technology system for health care electronic commerce.

PubMed

Forgionne, G A; Gangopadhyay, A; Klein, J A; Eckhardt, R

1999-08-01

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.

From guideline modeling to guideline execution: defining guideline-based decision-support services.

PubMed Central

Tu, S. W.; Musen, M. A.

2000-01-01

We describe our task-based approach to defining the guideline-based decision-support services that the EON system provides. We categorize uses of guidelines in patient-specific decision support into a set of generic tasks--making of decisions, specification of work to be performed, interpretation of data, setting of goals, and issuance of alert and reminders--that can be solved using various techniques. Our model includes constructs required for representing the knowledge used by these techniques. These constructs form a toolkit from which developers can select modeling solutions for guideline task. Based on the tasks and the guideline model, we define a guideline-execution architecture and a model of interactions between a decision-support server and clients that invoke services provided by the server. These services use generic interfaces derived from guideline tasks and their associated modeling constructs. We describe two implementations of these decision-support services and discuss how this work can be generalized. We argue that a well-defined specification of guideline-based decision-support services will facilitate sharing of tools that implement computable clinical guidelines. PMID:11080007

A multicriteria decision making model for assessment and selection of an ERP in a logistics context

NASA Astrophysics Data System (ADS)

Pereira, Teresa; Ferreira, Fernanda A.

2017-07-01

The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care.

PubMed Central

Gadd, C. S.; Baskaran, P.; Lobach, D. F.

1998-01-01

Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings. Images Figure 1 PMID:9929188

Sbexpert users guide (version 1.0): A knowledge-based decision-support system for spruce beetle management. Forest Service general technical report

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

Reynolds, K.M.; Holsten, E.H.; Werner, R.A.

1995-03-01

SBexpert version 1.0 is a knowledge-based decision-support system for management of spruce beetle developed for use in Microsoft Windows. The users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main subprograms; introduction, analysis, textbook, and literature. The introduction is the first of the five subtopics in the SBexpert help system. The analysis topic is an advisory system for spruce beetle management that provides recommendation for reducing spruce beetle hazard and risk to spruce stands and is the main analytical topic in SBexpert. The textbook and literature topics provide complementary decision support for analysis.

An IT Architecture for Systems Medicine.

PubMed

Ganzinger, Matthias; Gietzelt, Matthias; Karmen, Christian; Firnkorn, Daniel; Knaup, Petra

2015-01-01

Systems medicine aims to support treatment of complex diseases like cancer by integrating all available data for the disease. To provide such a decision support in clinical practice, a suitable IT architecture is necessary. We suggest a generic architecture comprised of the following three layers: data representation, decision support, and user interface. For the systems medicine research project "Clinically-applicable, omics-based assessment of survival, side effects, and targets in multiple myeloma" (CLIOMMICS) we developed a concrete instance of the generic architecture. We use i2b2 for representing the harmonized data. Since no deterministic model exists for multiple myeloma we use case-based reasoning for decision support. For clinical practice, visualizations of the results must be intuitive and clear. At the same time, they must communicate the uncertainty immanent in stochastic processes. Thus, we develop a specific user interface for systems medicine based on the web portal software Liferay.

SBexpert users guide (version 1.0): a knowledge-based decision-support system for spruce beetle management.

Treesearch

Keith M. Reynolds; Edward H. Holsten; Richard A. Werner

1994-01-01

SBexpert version 1.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rutipennis (Kby.)) management developed for use in Microsoft Windows with the KnowledgePro Windows development language. The SBexpert users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main topics (...

Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

ERIC Educational Resources Information Center

Kunisch, Joseph Martin

2012-01-01

Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

GET SMARTE: A DECISION SUPPORT SYSTEM TO REVITALIZE COMMUNITIES - CABERNET 2007

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...

Decision support tools to support the operations of traffic management centers (TMC)

DOT National Transportation Integrated Search

2011-01-31

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...

Driving with roadmaps and dashboards: using information resources to structure the decision models in service organizations.

PubMed

Chorpita, Bruce F; Bernstein, Adam; Daleiden, Eric L

2008-03-01

This paper illustrates the application of design principles for tools that structure clinical decision-making. If the effort to implement evidence-based practices in community services organizations is to be effective, attention must be paid to the decision-making context in which such treatments are delivered. Clinical research trials commonly occur in an environment characterized by structured decision making and expert supports. Technology has great potential to serve mental health organizations by supporting these potentially important contextual features of the research environment, through organization and reporting of clinical data into interpretable information to support decisions and anchor decision-making procedures. This article describes one example of a behavioral health reporting system designed to facilitate clinical and administrative use of evidence-based practices. The design processes underlying this system-mapping of decision points and distillation of performance information at the individual, caseload, and organizational levels-can be implemented to support clinical practice in a wide variety of settings.

Using a Group Decision Support System for Creativity.

ERIC Educational Resources Information Center

Aiken, Milam; Riggs, Mary

1993-01-01

A computer-based group decision support system (GDSS) to increase collaborative group productivity and creativity is explained. Various roles for the computer are identified, and implementation of GDSS systems at the University of Mississippi and International Business Machines are described. The GDSS is seen as fostering productivity through…

Evaluate the ability of clinical decision support systems (CDSSs) to improve clinical practice.

PubMed

Ajami, Sima; Amini, Fatemeh

2013-01-01

Prevalence of new diseases, medical science promotion and increase of referring to health care centers, provide a good situation for medical errors growth. Errors can involve medicines, surgery, diagnosis, equipment, or lab reports. Medical errors can occur anywhere in the health care system: In hospitals, clinics, surgery centers, doctors' offices, nursing homes, pharmacies, and patients' homes. According to the Institute of Medicine (IOM), 98,000 people die every year from preventable medical errors. In 2010 from all referred medical error records to Iran Legal Medicine Organization, 46/5% physician and medical team members were known as delinquent. One of new technologies that can reduce medical errors is clinical decision support systems (CDSSs). This study was unsystematic-review study. The literature was searched on evaluate the "ability of clinical decision support systems to improve clinical practice" with the help of library, books, conference proceedings, data bank, and also searches engines available at Google, Google scholar. For our searches, we employed the following keywords and their combinations: medical error, clinical decision support systems, Computer-Based Clinical Decision Support Systems, information technology, information system, health care quality, computer systems in the searching areas of title, keywords, abstract, and full text. In this study, more than 100 articles and reports were collected and 38 of them were selected based on their relevancy. The CDSSs are computer programs, designed for help to health care careers. These systems as a knowledge-based tool could help health care manager in analyze evaluation, improvement and selection of effective solutions in clinical decisions. Therefore, it has a main role in medical errors reduction. The aim of this study was to express ability of the CDSSs to improve

Use of declarative statements in creating and maintaining computer-interpretable knowledge bases for guideline-based care.

PubMed

Tu, Samson W; Hrabak, Karen M; Campbell, James R; Glasgow, Julie; Nyman, Mark A; McClure, Robert; McClay, James; Abarbanel, Robert; Mansfield, James G; Martins, Susana M; Goldstein, Mary K; Musen, Mark A

2006-01-01

Developing computer-interpretable clinical practice guidelines (CPGs) to provide decision support for guideline-based care is an extremely labor-intensive task. In the EON/ATHENA and SAGE projects, we formulated substantial portions of CPGs as computable statements that express declarative relationships between patient conditions and possible interventions. We developed query and expression languages that allow a decision-support system (DSS) to evaluate these statements in specific patient situations. A DSS can use these guideline statements in multiple ways, including: (1) as inputs for determining preferred alternatives in decision-making, and (2) as a way to provide targeted commentaries in the clinical information system. The use of these declarative statements significantly reduces the modeling expertise and effort required to create and maintain computer-interpretable knowledge bases for decision-support purpose. We discuss possible implications for sharing of such knowledge bases.

Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

NASA Astrophysics Data System (ADS)

Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

2016-09-01

In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

Knowledge base and sensor bus messaging service architecture for critical tsunami warning and decision-support

NASA Astrophysics Data System (ADS)

Sabeur, Z. A.; Wächter, J.; Middleton, S. E.; Zlatev, Z.; Häner, R.; Hammitzsch, M.; Loewe, P.

2012-04-01

The intelligent management of large volumes of environmental monitoring data for early tsunami warning requires the deployment of robust and scalable service oriented infrastructure that is supported by an agile knowledge-base for critical decision-support In the TRIDEC project (TRIDEC 2010-2013), a sensor observation service bus of the TRIDEC system is being developed for the advancement of complex tsunami event processing and management. Further, a dedicated TRIDEC system knowledge-base is being implemented to enable on-demand access to semantically rich OGC SWE compliant hydrodynamic observations and operationally oriented meta-information to multiple subscribers. TRIDEC decision support requires a scalable and agile real-time processing architecture which enables fast response to evolving subscribers requirements as the tsunami crisis develops. This is also achieved with the support of intelligent processing services which specialise in multi-level fusion methods with relevance feedback and deep learning. The TRIDEC knowledge base development work coupled with that of the generic sensor bus platform shall be presented to demonstrate advanced decision-support with situation awareness in context of tsunami early warning and crisis management.

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis

PubMed Central

Miller, Matthew James; McGuire, Kerry M.; Feigh, Karen M.

2016-01-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity. The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design. PMID:28491008

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis.

PubMed

Miller, Matthew James; McGuire, Kerry M; Feigh, Karen M

2017-06-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity . The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

SBexpert users guide (version 2.0): a knowledge-based decision-support system for spruce beetle management.

Treesearch

Keith M. Reynolds; Edward H. Holsten

1997-01-01

SBexpert version 2.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rufipennis (Kby.)) management developed for use in Microsoft (MS) Windows with the KnowledgePro Windows development language. Version 2.0 is a significant enhancement of version 1.0. The SBexpert users guide provides detailed instructions on the use of...

Human-computer interface for the study of information fusion concepts in situation analysis and command decision support systems

NASA Astrophysics Data System (ADS)

Roy, Jean; Breton, Richard; Paradis, Stephane

2001-08-01

Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.

SADA: Ecological Risk Based Decision Support System for Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

EPA Science Inventory

Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

Towards generic online multicriteria decision support in patient-centred health care.

PubMed

Dowie, Jack; Kjer Kaltoft, Mette; Salkeld, Glenn; Cunich, Michelle

2015-10-01

To introduce a new online generic decision support system based on multicriteria decision analysis (MCDA), implemented in practical and user-friendly software (Annalisa©). All parties in health care lack a simple and generic way to picture and process the decisions to be made in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. 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 scored and ranked. The scores for each option combine, in a simple expected value calculation, the best estimates available now for the performance of those options on patient-determined criteria, with the individual patient's preferences, expressed as importance weightings for those criteria. The survey 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-off practicality (including resource constraints) with normative rigour and empirical complexity, in both their development and delivery, is emphasized. The MCDA-/Annalisa-based decision support system represents a prescriptive addition to the portfolio of decision-aiding tools available online to individuals and clinicians interested in pursuing shared decision making and informed choice within a commitment to transparency in relation to both the evidence and preference bases of decisions. Some empirical data establishing its usability are provided. © 2013 The Authors. Health Expectations published by John Wiley & Sons Ltd.

A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department.

PubMed

Wilk, S; Michalowski, W; O'Sullivan, D; Farion, K; Sayyad-Shirabad, J; Kuziemsky, C; Kukawka, B

2013-01-01

The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A decision support system for map projections of small scale data

USGS Publications Warehouse

Finn, Michael P.; Usery, E. Lynn; Posch, Stephan T.; Seong, Jeong Chang

2004-01-01

The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience.

PubMed

Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel

2012-11-01

Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.

GREENER CHEMICAL PROCESS DESIGN ALTERNATIVES ARE REVEALED USING THE WASTE REDUCTION DECISION SUPPORT SYSTEM (WAR DSS)

EPA Science Inventory

The Waste Reduction Decision Support System (WAR DSS) is a Java-based software product providing comprehensive modeling of potential adverse environmental impacts (PEI) predicted to result from newly designed or redesigned chemical manufacturing processes. The purpose of this so...

An Environment for Guideline-based Decision Support Systems for Outpatients Monitoring.

PubMed

Zini, Elisa M; Lanzola, Giordano; Bossi, Paolo; Quaglini, Silvana

2017-08-11

We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic. We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2. The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient's conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients. Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients' needs, in our work the Decision Support System also helps the physicians in properly configuring the mobile application. Then the Decision Support System is also continuously fed by patient-reported outcomes.

Designing Computerized Decision Support That Works for Clinicians and Families

PubMed Central

Fiks, Alexander G.

2011-01-01

Evidence-based decision-making is central to the practice of pediatrics. Clinical trials and other biomedical research provide a foundation for this process, and practice guidelines, drawing from their results, inform the optimal management of an increasing number of childhood health problems. However, many clinicians fail to adhere to guidelines. Clinical decision support delivered using health information technology, often in the form of electronic health records, provides a tool to deliver evidence-based information to the point of care and has the potential to overcome barriers to evidence-based practice. An increasing literature now informs how these systems should be designed and implemented to most effectively improve outcomes in pediatrics. Through the examples of computerized physician order entry, as well as the impact of alerts at the point of care on immunization rates, the delivery of evidence-based asthma care, and the follow-up of children with attention deficit hyperactivity disorder, the following review addresses strategies for success in using these tools. The following review argues that, as decision support evolves, the clinician should no longer be the sole target of information and alerts. Through the Internet and other technologies, families are increasingly seeking health information and gathering input to guide health decisions. By enlisting clinical decision support systems to deliver evidence-based information to both clinicians and families, help families express their preferences and goals, and connect families to the medical home, clinical decision support may ultimately be most effective in improving outcomes. PMID:21315295

The development of a decision support system for prioritizing forested wetland restoration areeas in the lower Yazoo River Basin, Mississippi

Treesearch

Anegla A. Davis; Barbara A. Kleiss; Charles G. O' Hara; Jennifer S. Derby

2000-01-01

The Eco-Assessor, a GIS-based decision-support system, has been developed for the lower part of the Yazoo River Basin, Mississippi, to help planners and managers determine the best locations for the restoration of wetlands based on defined ecological and geographic criteria and probability of success. To assess the functional characteristics of the potential...

A knowledge-based patient assessment system: conceptual and technical design.

PubMed Central

Reilly, C. A.; Zielstorff, R. D.; Fox, R. L.; O'Connell, E. M.; Carroll, D. L.; Conley, K. A.; Fitzgerald, P.; Eng, T. K.; Martin, A.; Zidik, C. M.; Segal, M.

2000-01-01

This paper describes the design of an inpatient patient assessment application that captures nursing assessment data using a wireless laptop computer. The primary aim of this system is to capture structured information for facilitating decision support and quality monitoring. The system also aims to improve efficiency of recording patient assessments, reduce costs, and improve discharge planning and early identification of patient learning needs. Object-oriented methods were used to elicit functional requirements and to model the proposed system. A tools-based development approach is being used to facilitate rapid development and easy modification of assessment items and rules for decision support. Criteria for evaluation include perceived utility by clinician users, validity of decision support rules, time spent recording assessments, and perceived utility of aggregate reports for quality monitoring. PMID:11079970

A knowledge-based patient assessment system: conceptual and technical design.

PubMed

Reilly, C A; Zielstorff, R D; Fox, R L; O'Connell, E M; Carroll, D L; Conley, K A; Fitzgerald, P; Eng, T K; Martin, A; Zidik, C M; Segal, M

2000-01-01

This paper describes the design of an inpatient patient assessment application that captures nursing assessment data using a wireless laptop computer. The primary aim of this system is to capture structured information for facilitating decision support and quality monitoring. The system also aims to improve efficiency of recording patient assessments, reduce costs, and improve discharge planning and early identification of patient learning needs. Object-oriented methods were used to elicit functional requirements and to model the proposed system. A tools-based development approach is being used to facilitate rapid development and easy modification of assessment items and rules for decision support. Criteria for evaluation include perceived utility by clinician users, validity of decision support rules, time spent recording assessments, and perceived utility of aggregate reports for quality monitoring.

Assessing an AI knowledge-base for asymptomatic liver diseases.

PubMed

Babic, A; Mathiesen, U; Hedin, K; Bodemar, G; Wigertz, O

1998-01-01

Discovering not yet seen knowledge from clinical data is of importance in the field of asymptomatic liver diseases. Avoidance of liver biopsy which is used as the ultimate confirmation of diagnosis by making the decision based on relevant laboratory findings only, would be considered an essential support. The system based on Quinlan's ID3 algorithm was simple and efficient in extracting the sought knowledge. Basic principles of applying the AI systems are therefore described and complemented with medical evaluation. Some of the diagnostic rules were found to be useful as decision algorithms i.e. they could be directly applied in clinical work and made a part of the knowledge-base of the Liver Guide, an automated decision support system.

A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines.

PubMed

Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar

2017-03-01

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.

Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

PubMed

Kalogeropoulos, Dimitris A; Carson, Ewart R; Collinson, Paul O

2003-09-01

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

Decision support for the integrated restoration and protection strategy of the Forest Service, Northern Region

Treesearch

Keith Reynolds; Barry Bollenbacher; Chip Fisher; Melissa Hart; Mary Manning; Eric Henderson; Bruce Sims

2016-01-01

This report documents a decision-support process developed in the U.S. Department of Agriculture, Forest Service, Northern Region to assess management opportunities as part of an ecosystem-based approach to management that emphasizes ecological resilience. The decision-support system described in this work implements what is known as the Integrated Restoration and...

Medication-related clinical decision support in computerized provider order entry systems: a review.

PubMed

Kuperman, Gilad J; Bobb, Anne; Payne, Thomas H; Avery, Anthony J; Gandhi, Tejal K; Burns, Gerard; Classen, David C; Bates, David W

2007-01-01

While medications can improve patients' health, the process of prescribing them is complex and error prone, and medication errors cause many preventable injuries. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety and lower medication-related costs. To realize the medication-related benefits of CDS within CPOE, one must overcome significant challenges. Healthcare organizations implementing CPOE must understand what classes of CDS their CPOE systems can support, assure that clinical knowledge underlying their CDS systems is reasonable, and appropriately represent electronic patient data. These issues often influence to what extent an institution will succeed with its CPOE implementation and achieve its desired goals. Medication-related decision support is probably best introduced into healthcare organizations in two stages, basic and advanced. Basic decision support includes drug-allergy checking, basic dosing guidance, formulary decision support, duplicate therapy checking, and drug-drug interaction checking. Advanced decision support includes dosing support for renal insufficiency and geriatric patients, guidance for medication-related laboratory testing, drug-pregnancy checking, and drug-disease contraindication checking. In this paper, the authors outline some of the challenges associated with both basic and advanced decision support and discuss how those challenges might be addressed. The authors conclude with summary recommendations for delivering effective medication-related clinical decision support addressed to healthcare organizations, application and knowledge base vendors, policy makers, and researchers.

A pilot study of distributed knowledge management and clinical decision support in the cloud.

PubMed

Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford

2013-09-01

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 path toward achieving better support of clinical decision-making across the widest range of health care providers. Published by Elsevier B.V.

Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

PubMed Central

Bornstein, Aaron M.; Daw, Nathaniel D.

2013-01-01

How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770

The Integrated Medical Model - A Risk Assessment and Decision Support Tool for Human Space Flight Missions

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles G.; Saile, Lynn; FreiredeCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

2010-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight.

A Review of Decision Support Systems for Smart Homes in the Health Care System.

PubMed

Baumgärtel, Diana; Mielke, Corinna; Haux, Reinhold

2018-01-01

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.

Automatic Generation of Customized, Model Based Information Systems for Operations Management.

DTIC Science & Technology

The paper discusses the need for developing a customized, model based system to support management decision making in the field of operations ... management . It provides a critique of the current approaches available, formulates a framework to classify logistics decisions, and suggests an approach for the automatic development of logistics systems. (Author)

Extensions to regret-based decision curve analysis: an application to hospice referral for terminal patients.

PubMed

Tsalatsanis, Athanasios; Barnes, Laura E; Hozo, Iztok; Djulbegovic, Benjamin

2011-12-23

Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.

Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients

PubMed Central

2011-01-01

Background Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. Methods We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. Results The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. Conclusions We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned. PMID:22196308

Decision Support Systems for Operational Level Command and Control

DTIC Science & Technology

1990-04-30

business -based. These definitions still have applicability to military command and control - the business of military operations. A synthesis of the...other hand, there are such studies that were conducted in business environments. An eight week empincal study39 was 37 bd, pp 8-1 I. 38 Ranesh Shada...pp 139-158. 19 conducted and the groups with access to decision support system made significantly more effective decisions :n a business simulation

What can paper-based clinical information systems tell us about the design of computerized clinical information systems (CIS) in the ICU?

PubMed

Miller, A; Pilcher, D; Mercaldo, N; Leong, T; Scheinkestel, C; Schildcrout, J

2010-08-01

Screen designs in computerized clinical information systems (CIS) have been modeled on their paper predecessors. However, limited understanding about how paper forms support clinical work means that we risk repeating old mistakes and creating new opportunities for error and inefficiency as illustrated by problems associated with computerized provider order entry systems. This study was designed to elucidate principles underlying a successful ICU paper-based CIS. The research was guided by two exploratory hypotheses: (1) paper-based artefacts (charts, notes, equipment, order forms) are used differently by nurses, doctors and other healthcare professionals in different (formal and informal) conversation contexts and (2) different artefacts support different decision processes that are distributed across role-based conversations. All conversations undertaken at the bedsides of five patients were recorded with any supporting artefacts for five days per patient. Data was coded according to conversational role-holders, clinical decision process, conversational context and artefacts. 2133 data points were analyzed using Poisson logistic regression analyses. Results show significant interactions between artefacts used during different professional conversations in different contexts (chi(2)((df=16))=55.8, p<0.0001). The interaction between artefacts used during different professional conversations for different clinical decision processes was not statistically significant although all two-way interactions were statistically significant. Paper-based CIS have evolved to support complex interdisciplinary decision processes. The translation of two design principles - support interdisciplinary perspectives and integrate decision processes - from paper to computerized CIS may minimize the risks associated with computerization. 2010 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.

Development, deployment and usability of a point-of-care decision support system for chronic disease management using the recently-approved HL7 decision support service standard.

PubMed

Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight

2007-01-01

Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

Functional specifications for a radioactive waste decision support system

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

Westrom, G.B.; Kurrasch, E.R.; Carlton, R.E.

1989-09-01

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,more » 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.« less

A computerized clinical decision support system as a means of implementing depression guidelines.

PubMed

Trivedi, Madhukar H; Kern, Janet K; Grannemann, Bruce D; Altshuler, Kenneth Z; Sunderajan, Prabha

2004-08-01

The authors describe the history and current use of computerized systems for implementing treatment guidelines in general medicine as well as the development, testing, and early use of a computerized decision support system for depression treatment among "real-world" clinical settings in Texas. In 1999 health care experts from Europe and the United States met to confront the well-documented challenges of implementing treatment guidelines and to identify strategies for improvement. They suggested the integration of guidelines into computer systems that is incorporated into clinical workflow. Several studies have demonstrated improvements in physicians' adherence to guidelines when such guidelines are provided in a computerized format. Although computerized decision support systems are being used in many areas of medicine and have demonstrated improved patient outcomes, their use in psychiatric illness is limited. The authors designed and developed a computerized decision support system for the treatment of major depressive disorder by using evidence-based guidelines, transferring the knowledge gained from the Texas Medication Algorithm Project (TMAP). This computerized decision support system (CompTMAP) provides support in diagnosis, treatment, follow-up, and preventive care and can be incorporated into the clinical setting. CompTMAP has gone through extensive testing to ensure accuracy and reliability. Physician surveys have indicated a positive response to CompTMAP, although the sample was insufficient for statistical testing. CompTMAP is part of a new era of comprehensive computerized decision support systems that take advantage of advances in automation and provide more complete clinical support to physicians in clinical practice.

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

A web platform for integrated surface water - groundwater modeling and data management

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

Model-based decision support systems are considered to be reliable and time-efficient tools for resources management in various hydrology related fields. However, searching and acquisition of the required data, preparation of the data sets for simulations as well as post-processing, visualization and publishing of the simulations results often requires significantly more work and time than performing the modeling itself. The purpose of the developed software is to combine data storage facilities, data processing instruments and modeling tools in a single platform which potentially can reduce time required for performing simulations, hence decision making. The system is developed within the INOWAS (Innovative Web Based Decision Support System for Water Sustainability under a Changing Climate) project. The platform integrates spatially distributed catchment scale rainfall - runoff, infiltration and groundwater flow models with data storage, processing and visualization tools. The concept is implemented in a form of a web-GIS application and is build based on free and open source components, including the PostgreSQL database management system, Python programming language for modeling purposes, Mapserver for visualization and publishing the data, Openlayers for building the user interface and others. Configuration of the system allows performing data input, storage, pre- and post-processing and visualization in a single not disturbed workflow. In addition, realization of the decision support system in the form of a web service provides an opportunity to easily retrieve and share data sets as well as results of simulations over the internet, which gives significant advantages for collaborative work on the projects and is able to significantly increase usability of the decision support system.

A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

di, L.; Yang, Z.

2009-12-01

Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the adjustment of NASS survey data. This presentation will discuss the architecture, Earth observation data, and the crop progress model used in the decision support system.

The state of development of fire management decision support systems in America and Europe

Treesearch

Robert Mavsar; Armando González-Cabán; Elsa Varela

2013-01-01

Forest fires affect millions of people worldwide, and cause major ecosystem and economic impacts at different scales. The management policies implemented to minimize the negative impacts of forest fires require substantial investment of financial, human and organizational resources, which must be justifiable and efficient. Decision support systems based on economic...

Development of a decision support system for tsunami evacuation: application to the Jiyang District of Sanya city in China

NASA Astrophysics Data System (ADS)

Hou, Jingming; Yuan, Ye; Wang, Peitao; Ren, Zhiyuan; Li, Xiaojuan

2017-03-01

Major tsunami disasters often cause great damage in the first few hours following an earthquake. The possible severity of such events requires preparations to prevent tsunami disasters or mitigate them. This paper is an attempt to develop a decision support system for rapid tsunami evacuation for local decision makers. Based on the numerical results database of tsunami disasters, this system can quickly obtain the tsunami inundation and travel time. Because numerical models are calculated in advance, this system can reduce decision-making time. Population distribution, as a vulnerability factor, was analyzed to identify areas of high risk for tsunami disasters. Combined with spatial data, this system can comprehensively analyze the dynamic and static evacuation process and identify problems that negatively impact evacuation, thus supporting the decision-making for tsunami evacuation in high-risk areas. When an earthquake and tsunami occur, this system can rapidly obtain the tsunami inundation and travel time and provide information to assist with tsunami evacuation operations.

Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment

PubMed Central

2011-01-01

Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases. PMID:21385459

Development of a real-time clinical decision support system upon the Web MVC-based architecture for prostate cancer treatment.

PubMed

Lin, Hsueh-Chun; Wu, Hsi-Chin; Chang, Chih-Hung; Li, Tsai-Chung; Liang, Wen-Miin; Wang, Jong-Yi Wang

2011-03-08

A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases.

Dairy cow culling strategies: making economical culling decisions.

PubMed

Lehenbauer, T W; Oltjen, J W

1998-01-01

The purpose of this report was to examine important economic elements of culling decisions, to review progress in development of culling decision support systems, and to discern some of the potentially rewarding areas for future research on culling models. Culling decisions have an important influence on the economic performance of the dairy but are often made in a nonprogrammed fashion and based partly on the intuition of the decision maker. The computer technology that is available for dairy herd management has made feasible the use of economic models to support culling decisions. Financial components--including profit, cash flow, and risk--are major economic factors affecting culling decisions. Culling strategies are further influenced by short-term fluctuations in cow numbers as well as by planned herd expansion. Changes in herd size affect the opportunity cost for postponed replacement and may alter the relevance of optimization strategies that assume a fixed herd size. Improvements in model components related to biological factors affecting future cow performance, including milk production, reproductive status, and mastitis, appear to offer the greatest economic potential for enhancing culling decision support systems. The ultimate value of any culling decision support system for developing economic culling strategies will be determined by its results under field conditions.

Information systems: the key to evidence-based health practice.

PubMed Central

Rodrigues, R. J.

2000-01-01

Increasing prominence is being given to the use of best current evidence in clinical practice and health services and programme management decision-making. The role of information in evidence-based practice (EBP) is discussed, together with questions of how advanced information systems and technology (IS&T) can contribute to the establishment of a broader perspective for EBP. The author examines the development, validation and use of a variety of sources of evidence and knowledge that go beyond the well-established paradigm of research, clinical trials, and systematic literature review. Opportunities and challenges in the implementation and use of IS&T and knowledge management tools are examined for six application areas: reference databases, contextual data, clinical data repositories, administrative data repositories, decision support software, and Internet-based interactive health information and communication. Computerized and telecommunications applications that support EBP follow a hierarchy in which systems, tasks and complexity range from reference retrieval and the processing of relatively routine transactions, to complex "data mining" and rule-driven decision support systems. PMID:11143195

CEOS Contributions to Informing Energy Management and Policy Decision Making Using Space-Based Earth Observations

NASA Technical Reports Server (NTRS)

Eckman, Richard S.

2009-01-01

Earth observations are playing an increasingly significant role in informing decision making in the energy sector. In renewable energy applications, space-based observations now routinely augment sparse ground-based observations used as input for renewable energy resource assessment applications. As one of the nine Group on Earth Observations (GEO) societal benefit areas, the enhancement of management and policy decision making in the energy sector is receiving attention in activities conducted by the Committee on Earth Observation Satellites (CEOS). CEOS has become the "space arm" for the implementation of the Global Earth Observation System of Systems (GEOSS) vision. It is directly supporting the space-based, near-term tasks articulated in the GEO three-year work plan. This paper describes a coordinated program of demonstration projects conducted by CEOS member agencies and partners to utilize Earth observations to enhance energy management end-user decision support systems. I discuss the importance of engagement with stakeholders and understanding their decision support needs in successfully increasing the uptake of Earth observation products for societal benefit. Several case studies are presented, demonstrating the importance of providing data sets in formats and units familiar and immediately usable by decision makers. These projects show the utility of Earth observations to enhance renewable energy resource assessment in the developing world, forecast space-weather impacts on the power grid, and improve energy efficiency in the built environment.

On Developing a Taxonomy for Multidisciplinary Design Optimization: A Decision-Based Perspective

NASA Technical Reports Server (NTRS)

Lewis, Kemper; Mistree, Farrokh

1995-01-01

In this paper, we approach MDO from a Decision-Based Design (DBD) perspective and explore classification schemes for designing complex systems and processes. Specifically, we focus on decisions, which are only a small portion of the Decision Support Problem (DSP) Technique, our implementation of DBD. We map coupled nonhierarchical and hierarchical representations from the DSP Technique into the Balling-Sobieski (B-S) framework (Balling and Sobieszczanski-Sobieski, 1994), and integrate domain-independent linguistic terms to complete our taxonomy. Application of DSPs to the design of complex, multidisciplinary systems include passenger aircraft, ships, damage tolerant structural and mechanical systems, and thermal energy systems. In this paper we show that Balling-Sobieski framework is consistent with that of the Decision Support Problem Technique through the use of linguistic entities to describe the same type of formulations. We show that the underlying linguistics of the solution approaches are the same and can be coalesced into a homogeneous framework with which to base the research, application, and technology MDO upon. We introduce, in the Balling-Sobieski framework, examples of multidisciplinary design, namely, aircraft, damage tolerant structural and mechanical systems, and thermal energy systems.

DISPLA: decision information system for procurement and logistics analysis

NASA Astrophysics Data System (ADS)

Calvo, Alberto B.; Danish, Alexander J.; Lamonakis, Gregory G.

2002-08-01

This paper describes an information-exchange system for Display systems acquisition and logistics support. DISPLA (Decision Information System for Procurement and Logistics Analysis) is an Internet-based system concept for bringing sellers (display system and component suppliers) and buyers (Government Program Offices and System Integrators) together in an electronic exchange to improve the acquisition and logistics analysis support of Flat Panel Displays for the military. A proof-of-concept demonstration is presented in this paper using sample data from vendor Web sites and Government data sources.

School-Based Decision-Making: The Canadian Perspective.

ERIC Educational Resources Information Center

Peters, Frank

1997-01-01

In Canada, school-based decision making is a political expedient to co-opt public support for public education at the same time as financial resources to schools are being curtailed. School councils are advisory in nature and have no statutory position in either school or school-system decisions. (17 references) (MLF)

A medical informatics perspective on clinical decision support systems. Findings from the yearbook 2013 section on decision support.

PubMed

Bouaud, J; Lamy, J-B

2013-01-01

To summarize excellent research and to select best papers published in 2012 in the field of computer-based decision support in healthcare. A bibliographic search focused on clinical decision support systems (CDSSs) and computer provider order entry was performed, followed by a double-blind literature review. The review process yielded six papers, illustrating various aspects of clinical decision support. The first paper is a systematic review of CDSS intervention trials in real settings, and considers different types of possible outcomes. It emphasizes the heterogeneity of studies and confirms that CDSSs can improve process measures but that evidence lacks for other types of outcomes, especially clinical or economic. Four other papers tackle the safety of drug prescribing and show that CDSSs can be efficient in reducing prescription errors. The sixth paper exemplifies the growing role of ontological resources which can be used for several applications including decision support. CDSS research has to be continuously developed and assessed. The wide variety of systems and of interventions limits the understanding of factors of success of CDSS implementations. A standardization in the characterization of CDSSs and of intervention trial reporting will help to overcome this obstacle.

Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey.

PubMed

Leong, T Y; Kaiser, K; Miksch, S

2007-01-01

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support. We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards. To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation. There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

Lessons learned from implementing service-oriented clinical decision support at four sites: A qualitative study.

PubMed

Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford

2015-11-01

To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

NASA Astrophysics Data System (ADS)

Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

2013-04-01

A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

A decision support system for telemedicine through the mobile telecommunications platform.

PubMed

Eren, Ali; Subasi, Abdulhamit; Coskun, Osman

2008-02-01

In this paper we have discussed the application of artificial intelligence in telemedicine using mobile device. The main goal of our research is to develop methods and systems to collect, analyze, distribute and use medical diagnostics information from multiple knowledge sources and areas of expertise. Physicians may collect and analyze information obtained from experts worldwide with the help of a medical decision support system. In this information retrieval system, modern communication tools such as computers and mobile phones can be used efficiently. In this work we propose a medical decision support system using the general packet radio service (GPRS). GPRS, a data extension of the mobile telephony standard Global system for mobile communications (GSM) is emerging as the first true packet-switched architecture to allow mobile subscribers to benefit from high-speed transmission rates and run JAVA based applications from their mobile terminals. An academic prototype of a medical decision support system using mobile device was implemented. The results reveal that the system could find acceptance from the medical community and it could be an effective means of providing quality health care in developing countries.

Using old technology to implement modern computer-aided decision support for primary diabetes care.

PubMed Central

Hunt, D. L.; Haynes, R. B.; Morgan, D.

2001-01-01

BACKGROUND: Implementation rates of interventions known to be beneficial for people with diabetes mellitus are often suboptimal. Computer-aided decision support systems (CDSSs) can improve these rates. The complexity of establishing a fully integrated electronic medical record that provides decision support, however, often prevents their use. OBJECTIVE: To develop a CDSS for diabetes care that can be easily introduced into primary care settings and diabetes clinics. THE SYSTEM: The CDSS uses fax-machine-based optical character recognition software for acquiring patient information. Simple, 1-page paper forms, completed by patients or health practitioners, are faxed to a central location. The information is interpreted and recorded in a database. This initiates a routine that matches the information against a knowledge base so that patient-specific recommendations can be generated. These are formatted and faxed back within 4-5 minutes. IMPLEMENTATION: The system is being introduced into 2 diabetes clinics. We are collecting information on frequency of use of the system, as well as satisfaction with the information provided. CONCLUSION: Computer-aided decision support can be provided in any setting with a fax machine, without the need for integrated electronic medical records or computerized data-collection devices. PMID:11825194

Using old technology to implement modern computer-aided decision support for primary diabetes care.

PubMed

Hunt, D L; Haynes, R B; Morgan, D

2001-01-01

Implementation rates of interventions known to be beneficial for people with diabetes mellitus are often suboptimal. Computer-aided decision support systems (CDSSs) can improve these rates. The complexity of establishing a fully integrated electronic medical record that provides decision support, however, often prevents their use. To develop a CDSS for diabetes care that can be easily introduced into primary care settings and diabetes clinics. THE SYSTEM: The CDSS uses fax-machine-based optical character recognition software for acquiring patient information. Simple, 1-page paper forms, completed by patients or health practitioners, are faxed to a central location. The information is interpreted and recorded in a database. This initiates a routine that matches the information against a knowledge base so that patient-specific recommendations can be generated. These are formatted and faxed back within 4-5 minutes. The system is being introduced into 2 diabetes clinics. We are collecting information on frequency of use of the system, as well as satisfaction with the information provided. Computer-aided decision support can be provided in any setting with a fax machine, without the need for integrated electronic medical records or computerized data-collection devices.

Considering Information Up-to-Dateness to Increase the Accuracy of Therapy Decision Support Systems.

PubMed

Gaebel, Jan; Cypko, Mario A; Oeltze-Jafra, Steffen

2017-01-01

During the diagnostic process a lot of information is generated. All this information is assessed when making a final diagnosis and planning the therapy. While some patient information is stable, e.g., gender, others may become outdated, e.g., tumor size derived from CT data. Quantifying this information up-to-dateness and deriving consequences are difficult. Especially for the implementation in clinical decision support systems, this has not been studied. When information entities tend to become outdated, in practice, clinicians intuitively reduce their impact when making decisions. Therefore, in a system's calculations their impact should be reduced as well. We propose a method of decreasing the certainty of information entities based on their up-to-dateness. The method is tested in a decision support system for TNM staging based on Bayesian networks. We compared the actual N-state in records of 39 patients to the N-state calculated with and without decreasing data certainty. The results under decreased certainty correlated better with the actual states (r=0.958, p=0.008). We conclude that the up-to-dateness must be considered when processing clinical information to enhance decision making and ensure more patient safety.

Decision Support System for Medical Care Quality Assessment Based on Health Records Analysis in Russia.

PubMed

Taranik, Maksim; Kopanitsa, Georgy

2017-01-01

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.

Web-based health services and clinical decision support.

PubMed

Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

2004-01-01

The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.

Decision Support Systems for Launch and Range Operations Using Jess

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2007-01-01

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

Integrating conflict analysis and consensus reaching in a decision support system for water resource management.

PubMed

Giordano, R; Passarella, G; Uricchio, V F; Vurro, M

2007-07-01

The importance of shared decision processes in water management derives from the awareness of the inadequacy of traditional--i.e. engineering--approaches in dealing with complex and ill-structured problems. It is becoming increasingly obvious that traditional problem solving and decision support techniques, based on optimisation and factual knowledge, have to be combined with stakeholder based policy design and implementation. The aim of our research is the definition of an integrated decision support system for consensus achievement (IDSS-C) able to support a participative decision-making process in all its phases: problem definition and structuring, identification of the possible alternatives, formulation of participants' judgments, and consensus achievement. Furthermore, the IDSS-C aims at structuring, i.e. systematising the knowledge which has emerged during the participative process in order to make it comprehensible for the decision-makers and functional for the decision process. Problem structuring methods (PSM) and multi-group evaluation methods (MEM) have been integrated in the IDSS-C. PSM are used to support the stakeholders in providing their perspective of the problem and to elicit their interests and preferences, while MEM are used to define not only the degree of consensus for each alternative, highlighting those where the agreement is high, but also the consensus label for each alternative and the behaviour of individuals during the participative decision-making. The IDSS-C is applied experimentally to a decision process regarding the use of treated wastewater for agricultural irrigation in the Apulia Region (southern Italy).

GIS-based spatial decision support system for grain logistics management

NASA Astrophysics Data System (ADS)

Zhen, Tong; Ge, Hongyi; Jiang, Yuying; Che, Yi

2010-07-01

Grain logistics is the important component of the social logistics, which can be attributed to frequent circulation and the great quantity. At present time, there is no modern grain logistics distribution management system, and the logistics cost is the high. Geographic Information Systems (GIS) have been widely used for spatial data manipulation and model operations and provide effective decision support through its spatial database management capabilities and cartographic visualization. In the present paper, a spatial decision support system (SDSS) is proposed to support policy makers and to reduce the cost of grain logistics. The system is composed of two major components: grain logistics goods tracking model and vehicle routing problem optimization model and also allows incorporation of data coming from external sources. The proposed system is an effective tool to manage grain logistics in order to increase the speed of grain logistics and reduce the grain circulation cost.

Advanced Decision-Support for Coastal Beach Health: Virtual Beach 3.0

EPA Science Inventory

Virtual Beach is a free decision-support system designed to help beach managers and researchers construct, evaluate, and operate site-specific statistical models that can predict levels of fecal indicator bacteria (FIB) based on environmental conditions that are more readily mea...

Knowledge-based geographic information systems on the Macintosh computer: a component of the GypsES project

Treesearch

Gregory Elmes; Thomas Millette; Charles B. Yuill

1991-01-01

GypsES, a decision-support and expert system for the management of Gypsy Moth addresses five related research problems in a modular, computer-based project. The modules are hazard rating, monitoring, prediction, treatment decision and treatment implementation. One common component is a geographic information system designed to function intelligently. We refer to this...

Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework.

PubMed

Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song

2016-05-01

Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.

COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

EPA Science Inventory

Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends

A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

Development of a robust space power system decision model

NASA Astrophysics Data System (ADS)

Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert

2001-02-01

NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .

Personalization and Patient Involvement in Decision Support Systems: Current Trends

PubMed Central

Sacchi, L.; Lanzola, G.; Viani, N.

2015-01-01

Summary Objectives This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods We considered papers published on scientific journals, by querying PubMed and Web of Science™. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Conclusions Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large. PMID:26293857

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

PubMed

Lee, Seonah

2013-10-01

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

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

PubMed

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) 2001-2004

EPA Science Inventory

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identific...

THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) - 2007 UPDATE

EPA Science Inventory

CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based ...

Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

PubMed

Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

2018-06-01

Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

Design and evaluation of an imaging informatics system for analytics-based decision support in radiation therapy

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; DeMarco, John; Liu, Brent J.

2015-03-01

We have developed a comprehensive DICOM RT specific database of retrospective treatment planning data for radiation therapy of head and neck cancer. Further, we have designed and built an imaging informatics module that utilizes this database to perform data mining. The end-goal of this data mining system is to provide radiation therapy decision support for incoming head and neck cancer patients, by identifying best practices from previous patients who had the most similar tumor geometries. Since the performance of such systems often depends on the size and quality of the retrospective database, we have also placed an emphasis on developing infrastructure and strategies to encourage data sharing and participation from multiple institutions. The infrastructure and decision support algorithm have both been tested and evaluated with 51 sets of retrospective treatment planning data of head and neck cancer patients. We will present the overall design and architecture of our system, an overview of our decision support mechanism as well as the results of our evaluation.

Strategic analytics: towards fully embedding evidence in healthcare decision-making.

PubMed

Garay, Jason; Cartagena, Rosario; Esensoy, Ali Vahit; Handa, Kiren; Kane, Eli; Kaw, Neal; Sadat, Somayeh

2015-01-01

Cancer Care Ontario (CCO) has implemented multiple information technology solutions and collected health-system data to support its programs. There is now an opportunity to leverage these data and perform advanced end-to-end analytics that inform decisions around improving health-system performance. In 2014, CCO engaged in an extensive assessment of its current data capacity and capability, with the intent to drive increased use of data for evidence-based decision-making. The breadth and volume of data at CCO uniquely places the organization to contribute to not only system-wide operational reporting, but more advanced modelling of current and future state system management and planning. In 2012, CCO established a strategic analytics practice to assist the agency's programs contextualize and inform key business decisions and to provide support through innovative predictive analytics solutions. This paper describes the organizational structure, services and supporting operations that have enabled progress to date, and discusses the next steps towards the vision of embedding evidence fully into healthcare decision-making. Copyright © 2014 Longwoods Publishing.

A GH-Based Ontology to Support Applications for Automating Decision Support

DTIC Science & Technology

2005-03-01

architecture for a decision support sys - tem. For this reason, it obtains data from, and updates, a database. IDA also wanted the prototype’s architecture...Chief In- formation Officer CoABS Control of Agent Based Sys - tems DBMS Database Management System DoD Department of Defense DTD Document Type...Generic Hub, the Moyeu Générique, and the Generische Nabe , specifying each as a separate service description with property names and values of the GH

Trajectory-Based Takeoff Time Predictions Applied to Tactical Departure Scheduling: Concept Description, System Design, and Initial Observations

NASA Technical Reports Server (NTRS)

Engelland, Shawn A.; Capps, Alan

2011-01-01

Current aircraft departure release times are based on manual estimates of aircraft takeoff times. Uncertainty in takeoff time estimates may result in missed opportunities to merge into constrained en route streams and lead to lost throughput. However, technology exists to improve takeoff time estimates by using the aircraft surface trajectory predictions that enable air traffic control tower (ATCT) decision support tools. NASA s Precision Departure Release Capability (PDRC) is designed to use automated surface trajectory-based takeoff time estimates to improve en route tactical departure scheduling. This is accomplished by integrating an ATCT decision support tool with an en route tactical departure scheduling decision support tool. The PDRC concept and prototype software have been developed, and an initial test was completed at air traffic control facilities in Dallas/Fort Worth. This paper describes the PDRC operational concept, system design, and initial observations.

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

NASA Astrophysics Data System (ADS)

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

2008-10-01

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

A dashboard-based system for supporting diabetes care.

PubMed

Dagliati, Arianna; Sacchi, Lucia; Tibollo, Valentina; Cogni, Giulia; Teliti, Marsida; Martinez-Millana, Antonio; Traver, Vicente; Segagni, Daniele; Posada, Jorge; Ottaviano, Manuel; Fico, Giuseppe; Arredondo, Maria Teresa; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

2018-05-01

To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice. The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, care-flow mining, drug exposure pattern detection, and risk-prediction models for type 2 diabetes complications. The dashboard has 2 components, designed for (1) clinical decision support during follow-up consultations and (2) outcome assessment on populations of interest. To assess the impact of the clinical decision support component, a pre-post study was conducted considering visit duration, number of screening examinations, and lifestyle interventions. A pilot sample of 700 Italian patients was investigated. Judgments on the outcome assessment component were obtained via focus groups with clinicians and health care managers. The use of the decision support component in clinical activities produced a reduction in visit duration (P ≪ .01) and an increase in the number of screening exams for complications (P < .01). We also observed a relevant, although nonstatistically significant, increase in the proportion of patients receiving lifestyle interventions (from 69% to 77%). Regarding the outcome assessment component, focus groups highlighted the system's capability of identifying and understanding the characteristics of patient subgroups treated at the center. Our study demonstrates that decision support tools based on the integration of multiple-source data and visual and predictive analytics do improve the management of a chronic disease such as type 2 diabetes by enacting a successful implementation of the learning health care system cycle.

Improvement of sand filter and constructed wetland design using an environmental decision support system.

PubMed

Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

2008-01-01

With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.

On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies.

PubMed

Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

2006-01-01

We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.

Tailoring Software for Multiple Processor Systems

DTIC Science & Technology

1982-10-01

resource management decisions . Despite the lack of programming support, the use of multiple processor systems has grown sub- -stantially. Software has...making resource management decisions . Specifically, program- 1 mers need not allocate specific hardware resources to individual program components...Instead, such allocation decisions are automatically made based on high-level resource directives stated by ap- plication programmers, where each directive

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

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).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

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) PMID:21394218

Flu Diagnosis System Using Jaccard Index and Rough Set Approaches

NASA Astrophysics Data System (ADS)

Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip

2018-04-01

Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.

A web-based personalized risk communication and decision-making tool for women with dense breasts: Design and methods of a randomized controlled trial within an integrated health care system.

PubMed

Knerr, Sarah; Wernli, Karen J; Leppig, Kathleen; Ehrlich, Kelly; Graham, Amanda L; Farrell, David; Evans, Chalanda; Luta, George; Schwartz, Marc D; O'Neill, Suzanne C

2017-05-01

Mammographic breast density is one of the strongest risk factors for breast cancer after age and family history. Mandatory breast density disclosure policies are increasing nationally without clear guidance on how to communicate density status to women. Coupling density disclosure with personalized risk counseling and decision support through a web-based tool may be an effective way to allow women to make informed, values-consistent risk management decisions without increasing distress. This paper describes the design and methods of Engaged, a prospective, randomized controlled trial examining the effect of online personalized risk counseling and decision support on risk management decisions in women with dense breasts and increased breast cancer risk. The trial is embedded in a large integrated health care system in the Pacific Northwest. A total of 1250 female health plan members aged 40-69 with a recent negative screening mammogram who are at increased risk for interval cancer based on their 5-year breast cancer risk and BI-RADS® breast density will be randomly assigned to access either a personalized web-based counseling and decision support tool or standard educational content. Primary outcomes will be assessed using electronic health record data (i.e., chemoprevention and breast MRI utilization) and telephone surveys (i.e., distress) at baseline, six weeks, and twelve months. Engaged will provide evidence about whether a web-based personalized risk counseling and decision support tool is an effective method for communicating with women about breast density and risk management. An effective intervention could be disseminated with minimal clinical burden to align with density disclosure mandates. Clinical Trials Registration Number:NCT03029286. Copyright © 2017 Elsevier Inc. All rights reserved.

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts.

PubMed

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam; Zurek, Tomasz

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains.

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts

PubMed Central

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains. PMID:26495435

Acceptance and barriers pertaining to a general practice decision support system for multiple clinical conditions: A mixed methods evaluation.

PubMed

Arts, Derk L; Medlock, Stephanie K; van Weert, Henk C P M; Wyatt, Jeremy C; Abu-Hanna, Ameen

2018-01-01

Many studies have investigated the use of clinical decision support systems as a means to improve care, but have thus far failed to show significant effects on patient-related outcomes. We developed a clinical decision support system that attempted to address issues that were identified in these studies. The system was implemented in Dutch general practice and was designed to be both unobtrusive and to respond in real time. Despite our efforts, usage of the system was low. In the current study we perform a mixed methods evaluation to identify remediable barriers which led to disappointing usage rates for our system. A mixed methods evaluation employing an online questionnaire and focus group. The focus group was organized to clarify free text comments and receive more detailed feedback from general practitioners. Topics consisted of items based on results from the survey and additional open questions. The response rate for the questionnaire was 94%. Results from the questionnaire and focus group can be summarized as follows: The system was perceived as interruptive, despite its design. Participants felt that there were too many recommendations and that the relevance of the recommendations varied. Demographic based recommendations (e.g. age) were often irrelevant, while specific risk-based recommendations (e.g. diagnosis) were more relevant. The other main barrier to use was lack of time during the patient visit. These results are likely to be useful to other researchers who are attempting to address the problems of interruption and alert fatigue in decision support.

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

Effects of Using a Web-Based Individualized Education Program Decision Making Tutorial

ERIC Educational Resources Information Center

Shriner, James G.; Carty, Susan J.; Rose, Chad A.; Shogren, Karrie A.; Kim, Myungjin; Trach, John S.

2013-01-01

This study explored the effects of a web-based decision support system ("Tutorial") for writing standards-based Individualized Education Programs (IEPs). A total of 35 teachers and 154 students participated across two academic years. Participants were assigned to one of three intervention groups based on level of "Tutorial"…

Effects of Using a Web-Based Individualized Education Program Decision-Making Tutorial

ERIC Educational Resources Information Center

Shriner, James G.; Carty, Susan J.; Rose, Chad A.; Shogren, Karrie A.; Kim, Myungjin; Trach, John S.

2013-01-01

This study explored the effects of a web-based decision support system ("Tutorial") for writing standards-based Individualized Education Programs (IEPs). A total of 35 teachers and 154 students participated across two academic years. Participants were assigned to one of three intervention groups based on level of "Tutorial"…

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

NASA Astrophysics Data System (ADS)

Saito, Yoshihito; Matsuo, Tokuro

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

Clinical decision support for personalized medicine: an opportunity for pharmacist-physician collaboration.

PubMed

Barlow, Jane F

2012-06-01

Pharmacogenomics has significant potential to improve the efficacy and safety of medication therapy, but it requires new expertise and adds a new layer of complexity for all healthcare professionals. Pharmacists and pharmacy management systems can play a leading role in providing clinical decision support for the use and interpretation of pharmacogenomic tests. To serve this role effectively, pharmacists will need to expand their expertise in the emerging field of clinical pharmacogenomics. Pharmacy-based clinical programs can expedite the use of pharmacogenomic testing, help physicians interpret the test results and identify future medication risks associated with the patient's phenotype. Over time, some of these functions can be embedded in clinical decision support systems as part of the broader automation of the healthcare system.

Publically accessible decision support system of the spatially referenced regressions on watershed attributes (SPARROW) model and model enhancements in South Carolina

Treesearch

Celeste Journey; Anne B. Hoos; David E. Ladd; John W. brakebill; Richard A. Smith

2016-01-01

The U.S. Geological Survey (USGS) National Water Quality Assessment program has developed a web-based decision support system (DSS) to provide free public access to the steady-stateSPAtially Referenced Regressions On Watershed attributes (SPARROW) model simulation results on nutrient conditions in streams and rivers and to offer scenario testing capabilities for...

Data Mining for Web-Based Support Systems: A Case Study in e-Custom Systems

NASA Astrophysics Data System (ADS)

Razmerita, Liana; Kirchner, Kathrin

This chapter provides an example of a Web-based support system (WSS) used to streamline trade procedures, prevent potential security threats, and reduce tax-related fraud in cross-border trade. The architecture is based on a service-oriented architecture that includes smart seals and Web services. We discuss the implications and suggest further enhancements to demonstrate how such systems can move toward a Web-based decision support system with the support of data mining methods. We provide a concrete example of how data mining can help to analyze the vast amount of data collected while monitoring the container movements along its supply chain.

Development of a decision support system for analysis and solutions of prolonged standing in the workplace.

PubMed

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-06-01

Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.

Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

PubMed Central

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-01-01

Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

PubMed

da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

2005-01-01

This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment.

Multicriteria decision model for retrofitting existing buildings

NASA Astrophysics Data System (ADS)

Bostenaru Dan, B.

2003-04-01

In this paper a model to decide which buildings from an urban area should be retrofitted is presented. The model has been cast into existing ones by choosing the decision rule, criterion weighting and decision support system types most suitable for the spatial problem of reducing earthquake risk in urban areas, considering existing spatial multiatributive and multiobjective decision methods and especially collaborative issues. Due to the participative character of the group decision problem "retrofitting existing buildings" the decision making model is based on interactivity. Buildings have been modeled following the criteria of spatial decision support systems. This includes identifying the corresponding spatial elements of buildings according to the information needs of actors from different sphaeres like architects, construction engineers and economists. The decision model aims to facilitate collaboration between this actors. The way of setting priorities interactivelly will be shown, by detailing the two phases: judgemental and computational, in this case site analysis, collection and evaluation of the unmodified data and converting survey data to information with computational methods using additional expert support. Buildings have been divided into spatial elements which are characteristic for the survey, present typical damages in case of an earthquake and are decisive for a better seismic behaviour in case of retrofitting. The paper describes the architectural and engineering characteristics as well as the structural damage for constuctions of different building ages on the example of building types in Bucharest, Romania in compressible and interdependent charts, based on field observation, reports from the 1977 earthquake and detailed studies made by the author together with a local engineer for the EERI Web Housing Encyclopedia. On this base criteria for setting priorities flow into the expert information contained in the system.

Integrating complex business processes for knowledge-driven clinical decision support systems.

PubMed

Kamaleswaran, Rishikesan; McGregor, Carolyn

2012-01-01

This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

Veal marketing could return more than traditional weaning

USDA-ARS?s Scientific Manuscript database

How profitable is a system of marketing early-weaned calves for veal production versus a traditional system based on more traditional weaning and marketing feeder calves? In an attempt to answer this question, decision support software (Decision Evaluator for the Cattle Industry, DECI) developed at...

DE.SMARTe: US-German Bilateral Cooperation For The Development Of An Internet-Based Decision Support System For Sustainable Revitalisation of Contaminated Sites - June 2009

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is a web-based decision support tool developed by he Office of Research and Development (ORD) in partnership with the Office of Brownfields and Land Revitaliza...

Computerized Clinical Decision Support: Contributions from 2015

PubMed Central

Bouaud, J.

2016-01-01

Summary Objective To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection. Results Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians’ decisions. Conclusions While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate the benefits that they promise. PMID:27830247

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation.

PubMed

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-06-01

This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.

A GIS BASED DECISION SUPPORT SYSTEM AND RESOURCE TOOL FOR USE ON STUDIES OF THE LAKE TEXOMA ECOSYSTEM

EPA Science Inventory

Investigations are underway at Lake Texoma, to develop decision support tools and information to evaluate the transport and attenuation of contaminants and stressors in a lake ecosystem, and link them to observable ecological effects. The U.S. EPA, USGS, U. S. Army Corps of Eng...

Development and evaluation of online evidence based guideline bank system.

PubMed

Park, Myonghwa

2006-01-01

The purpose of this study was to develop and evaluate the online evidence-based nursing practice guideline bank system to support the best evidence-based decision in the clinical and community practice settings. The main homepage consisted of seven modules for introduction of site, EBN, guideline bank, guideline development, guideline review, related sites, and community. The major contents in the guidelines were purpose, developer, intended audience, method of development, target population, testing, knowledge components, and evaluation. Electronic versions of the guidelines were displayed by XML, PDF, and PDA versions. The system usability were evaluated by general users, guideline developers, and guideline reviewers on the web and the results showed high scores of satisfaction. This online evidence-based guideline bank system could support nurses' best and cost-effective clinical decision using the sharable standardized guidelines with education module of evidence based nursing.

Decision support systems for clinical radiological practice — towards the next generation

PubMed Central

Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A

2010-01-01

The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully. PMID:20965900

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

PubMed Central

Aronsky, D.; Haug, P. J.

1999-01-01

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

Assessing School Readiness for a Practice Arrangement Using Decision Tree Methodology.

ERIC Educational Resources Information Center

Barger, Sara E.

1998-01-01

Questions in a decision-tree address mission, faculty interest, administrative support, and practice plan as a way of assessing arrangements for nursing faculty's clinical practice. Decisions should be based on congruence between the human resource allocation and the reward systems. (SK)

Privacy-preserving clinical decision support system using Gaussian kernel-based classification.

PubMed

Rahulamathavan, Yogachandran; Veluru, Suresh; Phan, Raphael C-W; Chambers, Jonathon A; Rajarajan, Muttukrishnan

2014-01-01

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.

A Conceptual Framework for the Electronic Performance Support Systems within IBM Lotus Notes 6 (LN6) Example

ERIC Educational Resources Information Center

Bayram, Servet

2005-01-01

The concept of Electronic Performance Support Systems (EPSS) is containing multimedia or computer based instruction components that improves human performance by providing process simplification, performance information and decision support system. EPSS has become a hot topic for organizational development, human resources, performance technology,…

Seismic slope-performance analysis: from hazard map to decision support system

USGS Publications Warehouse

Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

1999-01-01

In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

Automatic system testing of a decision support system for insulin dosing using Google Android.

PubMed

Spat, Stephan; Höll, Bernhard; Petritsch, Georg; Schaupp, Lukas; Beck, Peter; Pieber, Thomas R

2013-01-01

Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards.

Decision blocks: A tool for automating decision making in CLIPS

NASA Technical Reports Server (NTRS)

Eick, Christoph F.; Mehta, Nikhil N.

1991-01-01

The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program.

Decision-Guided Recommenders with Composite Alternatives

ERIC Educational Resources Information Center

Alodhaibi, Khalid

2011-01-01

Recommender systems aim to support users in their decision-making process while interacting with large information spaces and recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems are increasingly used with product and service selection over the Internet. Although…

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations.

PubMed

Mohammed, Ibrahim Nourein; Bolten, John D; Srinivasan, Raghavan; Lakshmi, Venkat

2018-06-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region's hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling.

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations

PubMed Central

Mohammed, Ibrahim Nourein; Bolten, John D.; Srinivasan, Raghavan; Lakshmi, Venkat

2018-01-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region’s hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling. PMID:29938116

DoD Can Save Millions by Using Energy Efficient Centralized Aircraft Support Systems.

DTIC Science & Technology

1982-05-07

recommends that the Secretary of the Air Force: -- Reevaluate the decision not to install centralized systems at tactical bases. If the systems can be...discontinue using the aircraft’s onboard auxillary power units. These units consume tremendous amounts of jet fuel in providing cabin air-conditioning...requirements. Each command has been asked to analyze its bases to determine if centralized systems should be installed. Although a final decision has not

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less

Decision support system for emergency management of oil spill accidents in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Liubartseva, Svitlana; Coppini, Giovanni; Pinardi, Nadia; De Dominicis, Michela; Lecci, Rita; Turrisi, Giuseppe; Cretì, Sergio; Martinelli, Sara; Agostini, Paola; Marra, Palmalisa; Palermo, Francesco

2016-08-01

This paper presents an innovative web-based decision support system to facilitate emergency management in the case of oil spill accidents, called WITOIL (Where Is The Oil). The system can be applied to create a forecast of oil spill events, evaluate uncertainty of the predictions, and calculate hazards based on historical meteo-oceanographic datasets. To compute the oil transport and transformation, WITOIL uses the MEDSLIK-II oil spill model forced by operational meteo-oceanographic services. Results of the modeling are visualized through Google Maps. A special application for Android is designed to provide mobile access for competent authorities, technical and scientific institutions, and citizens.

Ending on a positive: Examining the role of safety leadership decisions, behaviours and actions in a safety critical situation.

PubMed

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

2018-01-01

Safety leadership is an important factor in supporting safe performance in the workplace. The present case study examined the role of safety leadership during the Bingham Canyon Mine high-wall failure, a significant mining incident in which no fatalities or injuries were incurred. The Critical Decision Method (CDM) was used in conjunction with a self-reporting approach to examine safety leadership in terms of decisions, behaviours and actions that contributed to the incidents' safe outcome. Mapping the analysis onto Rasmussen's Risk Management Framework (Rasmussen, 1997), the findings demonstrate clear links between safety leadership decisions, and emergent behaviours and actions across the work system. Communication and engagement based decisions featured most prominently, and were linked to different leadership practices across the work system. Further, a core sub-set of CDM decision elements were linked to the open flow and exchange of information across the work system, which was critical to supporting the safe outcome. The findings provide practical implications for the development of safety leadership capability to support safety within the mining industry. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2013-05-01

To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows.

FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING, FRED: A TOOL FOR ENVIRONMENTALLY-PREFERABLE PURCHASING

EPA Science Inventory

In support of the Environmentally Preferable Purchasing Program of the US EPA, the Systems Analysis Branch has developed a decision-making tool based on life cycle assessment. This tool, the Framework for Responsible Environmental Decision-making or FRED streamlines LCA by choosi...

DSOM - Decision Support for Operations and Maintenance - Application to a USMC Base Centralized Energy System.

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

Meador, Richard J.; Hatley, Darrel D.

2004-06-01

PNNL DSOM technology coordinates efficient steam plant operation with EMCS and SCADA systems, providing generation support and automated load shedding to meet peak demand limits saving over $1M in two years.

Towards a decision support system for hand dermatology.

PubMed

Mazzola, Luca; Cavazzina, Alice; Pinciroli, Francesco; Bonacina, Stefano; Pigatto, Paolo; Ayala, Fabio; De Pità, Ornella; Marceglia, Sara

2014-01-01

The complexity of the medical diagnosis is faced by practitioners relying mainly on their experiences. This can be acquired during daily practices and on-the-job training. Given the complexity and extensiveness of the subject, supporting tools that include knowledge extracted by highly specialized practitioners can be valuable. In the present work, a Decision Support System (DSS) for hand dermatology was developed based on data coming from a Visit Report Form (VRF). Using a Bayesian approach and factors significance difference over the population average for the case, we demonstrated the potentiality of creating an enhanced VRF that include a diagnoses distribution probability based on the DSS rules applied for the specific patient situation.

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Technical Reports Server (NTRS)

Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

2017-01-01

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

IDESSA: An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Authmann, Christian; Dreber, Niels; Hess, Bastian; Kellner, Klaus; Morgenthal, Theunis; Nauss, Thomas; Seeger, Bernhard; Tsvuura, Zivanai; Wiegand, Kerstin

2017-04-01

Bush encroachment is a syndrome of land degradation that occurs in many savannas including those of southern Africa. The increase in density, cover or biomass of woody vegetation often has negative effects on a range of ecosystem functions and services, which are hardly reversible. However, despite its importance, neither the causes of bush encroachment, nor the consequences of different resource management strategies to combat or mitigate related shifts in savanna states are fully understood. The project "IDESSA" (An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas) aims to improve the understanding of the complex interplays between land use, climate patterns and vegetation dynamics and to implement an integrative monitoring and decision-support system for the sustainable management of different savanna types. For this purpose, IDESSA follows an innovative approach that integrates local knowledge, botanical surveys, remote-sensing and machine-learning based time-series of atmospheric and land-cover dynamics, spatially explicit simulation modeling and analytical database management. The integration of the heterogeneous data will be implemented in a user oriented database infrastructure and scientific workflow system. Accessible via web-based interfaces, this database and analysis system will allow scientists to manage and analyze monitoring data and scenario computations, as well as allow stakeholders (e. g. land users, policy makers) to retrieve current ecosystem information and seasonal outlooks. We present the concept of the project and show preliminary results of the realization steps towards the integrative savanna management and decision-support system.

Natural resource assessment and decision support tools for bird conservation planning

Treesearch

Carl E. Korschgen; Melinda G. Knutson; Timothy J. Fox; Leslie Holland-Bartels; Henry C. Dehaan; Charles H. Theiling; Jason J. Rohweder; Kevin Kenow; Linda E. Leake; Tom Will

2005-01-01

We have used a place-based decision support system for several years to identify bird conservation issues relating to the management and planning needs of resource managers. Public and private land managers are constantly seeking better ways to incorporate landscape, species, and habitat relationships into the conservation planning process. The U.S. Fish and Wildlife...

How to guide - transit operations decision support systems (TODSS).

DOT National Transportation Integrated Search

2014-12-01

Transit Operations Decision Support Systems (TODSS) are decision support systems designed to support dispatchers in real-time bus operations management in response to incidents, special events, and other changing conditions in order to restore servic...

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Decision support systems for ecosystem management: An evaluation of existing systems

Treesearch

H. Todd Mowrer; Klaus Barber; Joe Campbell; Nick Crookston; Cathy Dahms; John Day; Jim Laacke; Jim Merzenich; Steve Mighton; Mike Rauscher; Rick Sojda; Joyce Thompson; Peter Trenchi; Mark Twery

1997-01-01

This report evaluated 24 computer-aided decision support systems (DSS) that can support management decision-making in forest ecosystems. It compares the scope of each system, spatial capabilities, computational methods, development status, input and output requirements, user support availability, and system performance. Questionnaire responses from the DSS developers (...

Measurement-based care for refractory depression: a clinical decision support model for clinical research and practice.

PubMed

Trivedi, Madhukar H; Daly, Ella J

2007-05-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the "next best" treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses.

Measurement-Based Care for Refractory Depression: A Clinical Decision Support Model for Clinical Research and Practice

PubMed Central

Trivedi, Madhukar H.; Daly, Ella J.

2009-01-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the “next best” treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses. PMID:17320312

User-centered design to improve clinical decision support in primary care.

PubMed

Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M

2017-08-01

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 improvement" was the only user-centered design practice significantly associated with perceived utility of clinical decision support, b=.47 (p<.001). This association was present in hospital-based clinics, b=.34 (p<.05), but was stronger at community-based clinics, b=.61 (p<.001). Our findings are highly supportive of the practice of analyzing the impact of clinical decision support on performance metrics. This was the most common user-centered design practice in our study, and was the practice associated with higher perceived utility of clinical decision support. This practice may be particularly helpful at community-based clinics, which are typically less connected to VA medical center resources. Published by Elsevier B.V.

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation

PubMed Central

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-01-01

Introduction: This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. Material and methods: The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. Results: The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. Conclusion: The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care. PMID:28883678

Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS)

NASA Astrophysics Data System (ADS)

Zhang, Zhong

In this work, motivated by the need to coordinate transmission maintenance scheduling among a multiplicity of self-interested entities in restructured power industry, a distributed decision support framework based on multiagent negotiation systems (MANS) is developed. An innovative risk-based transmission maintenance optimization procedure is introduced. Several models for linking condition monitoring information to the equipment's instantaneous failure probability are presented, which enable quantitative evaluation of the effectiveness of maintenance activities in terms of system cumulative risk reduction. Methodologies of statistical processing, equipment deterioration evaluation and time-dependent failure probability calculation are also described. A novel framework capable of facilitating distributed decision-making through multiagent negotiation is developed. A multiagent negotiation model is developed and illustrated that accounts for uncertainty and enables social rationality. Some issues of multiagent negotiation convergence and scalability are discussed. The relationships between agent-based negotiation and auction systems are also identified. A four-step MAS design methodology for constructing multiagent systems for power system applications is presented. A generic multiagent negotiation system, capable of inter-agent communication and distributed decision support through inter-agent negotiations, is implemented. A multiagent system framework for facilitating the automated integration of condition monitoring information and maintenance scheduling for power transformers is developed. Simulations of multiagent negotiation-based maintenance scheduling among several independent utilities are provided. It is shown to be a viable alternative solution paradigm to the traditional centralized optimization approach in today's deregulated environment. This multiagent system framework not only facilitates the decision-making among competing power system entities, but also provides a tool to use in studying competitive industry relative to monopolistic industry.

Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems

PubMed Central

Sittig, Dean F; Ash, Joan S; Feblowitz, Joshua; Meltzer, Seth; McMullen, Carmit; Guappone, Ken; Carpenter, Jim; Richardson, Joshua; Simonaitis, Linas; Evans, R Scott; Nichol, W Paul; Middleton, Blackford

2011-01-01

Background Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. Objective To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. Study design and methods We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Results Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. Conclusion We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content. PMID:21415065

Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge

PubMed Central

2012-01-01

Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475

SMARTE: IMPROVING REVITALIZATION DECISIONS - PRESENTATION IN NRMRL SEMINAR SERIES

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electribuc) is an open-source, web-based, decision-support system for developing and evaluating alternative reuse scenarios for potentially contaminated sites (e.g., brownfields). It is being developed collaborati...

SMARTE: IMPROVING REVITALIZATION DECISIONS - PRESENTATION FOR ETV INTERNATIONAL FORUM

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools - electronic) is an open-source, web-based, decision-support system for developing and evaluating alternative reuse scenarios for potentially contaminated sites (e.g., brownfields). It is being developed collabora...

GET SMARTE: DECISION TOOLS TO REVITALIZE BROWNFIELDS

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

Opportunities and Strategies to Incorporate Ecosystem Services Knowledge and Decision Support Tools into Planning and Decision Making in Hawai`i

NASA Astrophysics Data System (ADS)

Bremer, Leah L.; Delevaux, Jade M. S.; Leary, James J. K.; J. Cox, Linda; Oleson, Kirsten L. L.

2015-04-01

Incorporating ecosystem services into management decisions is a promising means to link conservation and human well-being. Nonetheless, planning and management in Hawai`i, a state with highly valued natural capital, has yet to broadly utilize an ecosystem service approach. We conducted a stakeholder assessment, based on semi-structured interviews, with terrestrial ( n = 26) and marine ( n = 27) natural resource managers across the State of Hawai`i to understand the current use of ecosystem services (ES) knowledge and decision support tools and whether, how, and under what contexts, further development would potentially be useful. We found that ES knowledge and tools customized to Hawai`i could be useful for communication and outreach, justifying management decisions, and spatial planning. Greater incorporation of this approach is clearly desired and has a strong potential to contribute to more sustainable decision making and planning in Hawai`i and other oceanic island systems. However, the unique biophysical, socio-economic, and cultural context of Hawai`i, and other island systems, will require substantial adaptation of existing ES tools. Based on our findings, we identified four key opportunities for the use of ES knowledge and tools in Hawai`i: (1) linking native forest protection to watershed health; (2) supporting sustainable agriculture; (3) facilitating ridge-to-reef management; and (4) supporting statewide terrestrial and marine spatial planning. Given the interest expressed by natural resource managers, we envision broad adoption of ES knowledge and decision support tools if knowledge and tools are tailored to the Hawaiian context and coupled with adequate outreach and training.

Opportunities and strategies to incorporate ecosystem services knowledge and decision support tools into planning and decision making in Hawai'i.

PubMed

Bremer, Leah L; Delevaux, Jade M S; Leary, James J K; J Cox, Linda; Oleson, Kirsten L L

2015-04-01

Incorporating ecosystem services into management decisions is a promising means to link conservation and human well-being. Nonetheless, planning and management in Hawai'i, a state with highly valued natural capital, has yet to broadly utilize an ecosystem service approach. We conducted a stakeholder assessment, based on semi-structured interviews, with terrestrial (n = 26) and marine (n = 27) natural resource managers across the State of Hawai'i to understand the current use of ecosystem services (ES) knowledge and decision support tools and whether, how, and under what contexts, further development would potentially be useful. We found that ES knowledge and tools customized to Hawai'i could be useful for communication and outreach, justifying management decisions, and spatial planning. Greater incorporation of this approach is clearly desired and has a strong potential to contribute to more sustainable decision making and planning in Hawai'i and other oceanic island systems. However, the unique biophysical, socio-economic, and cultural context of Hawai'i, and other island systems, will require substantial adaptation of existing ES tools. Based on our findings, we identified four key opportunities for the use of ES knowledge and tools in Hawai'i: (1) linking native forest protection to watershed health; (2) supporting sustainable agriculture; (3) facilitating ridge-to-reef management; and (4) supporting statewide terrestrial and marine spatial planning. Given the interest expressed by natural resource managers, we envision broad adoption of ES knowledge and decision support tools if knowledge and tools are tailored to the Hawaiian context and coupled with adequate outreach and training.

Spatial decision support system for tobacco enterprise based on spatial data mining

NASA Astrophysics Data System (ADS)

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

2007-11-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

A Service Oriented Architecture Approach to Achieve Interoperability between Immunization Information Systems in Iran

PubMed Central

Hosseini, Masoud; Ahmadi, Maryam; Dixon, Brian E.

2014-01-01

Clinical decision support (CDS) systems can support vaccine forecasting and immunization reminders; however, immunization decision-making requires data from fragmented, independent systems. Interoperability and accurate data exchange between immunization information systems (IIS) is an essential factor to utilize Immunization CDS systems. Service oriented architecture (SOA) and Health Level 7 (HL7) are dominant standards for web-based exchange of clinical information. We implemented a system based on SOA and HL7 v3 to support immunization CDS in Iran. We evaluated system performance by exchanging 1500 immunization records for roughly 400 infants between two IISs. System turnaround time is less than a minute for synchronous operation calls and the retrieved immunization history of infants were always identical in different systems. CDS generated reports were accordant to immunization guidelines and the calculations for next visit times were accurate. Interoperability is rare or nonexistent between IIS. Since inter-state data exchange is rare in United States, this approach could be a good prototype to achieve interoperability of immunization information. PMID:25954452

A Service Oriented Architecture Approach to Achieve Interoperability between Immunization Information Systems in Iran.

PubMed

Hosseini, Masoud; Ahmadi, Maryam; Dixon, Brian E

2014-01-01

Clinical decision support (CDS) systems can support vaccine forecasting and immunization reminders; however, immunization decision-making requires data from fragmented, independent systems. Interoperability and accurate data exchange between immunization information systems (IIS) is an essential factor to utilize Immunization CDS systems. Service oriented architecture (SOA) and Health Level 7 (HL7) are dominant standards for web-based exchange of clinical information. We implemented a system based on SOA and HL7 v3 to support immunization CDS in Iran. We evaluated system performance by exchanging 1500 immunization records for roughly 400 infants between two IISs. System turnaround time is less than a minute for synchronous operation calls and the retrieved immunization history of infants were always identical in different systems. CDS generated reports were accordant to immunization guidelines and the calculations for next visit times were accurate. Interoperability is rare or nonexistent between IIS. Since inter-state data exchange is rare in United States, this approach could be a good prototype to achieve interoperability of immunization information.

Software Tools For Building Decision-support Models For Flood Emergency Situations

NASA Astrophysics Data System (ADS)

Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.

The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.

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

PubMed

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

2014-06-01

This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice.

Methods Used to Support a Life Cycle of Complex Engineering Products

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

XWeB: The XML Warehouse Benchmark

NASA Astrophysics Data System (ADS)

Mahboubi, Hadj; Darmont, Jérôme

With the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of benchmarks. However, decision support benchmarks do not currently support XML features. In this paper, we introduce the XML Warehouse Benchmark (XWeB), which aims at filling this gap. XWeB derives from the relational decision support benchmark TPC-H. It is mainly composed of a test data warehouse that is based on a unified reference model for XML warehouses and that features XML-specific structures, and its associate XQuery decision support workload. XWeB's usage is illustrated by experiments on several XML database management systems.

A Mobile Computerized Decision Support System to Prevent Hypoglycemia in Hospitalized Patients With Type 2 Diabetes Mellitus

PubMed Central

Spat, Stephan; Donsa, Klaus; Beck, Peter; Höll, Bernhard; Mader, Julia K.; Schaupp, Lukas; Augustin, Thomas; Chiarugi, Franco; Lichtenegger, Katharina M.; Plank, Johannes; Pieber, Thomas R.

2016-01-01

Background: Diabetes management requires complex and interdisciplinary cooperation of health care professionals (HCPs). To support this complex process, IT-support is recommended by clinical guidelines. The aim of this article is to report on results from a clinical feasibility study testing the prototype of a mobile, tablet-based client-server system for computerized decision and workflow support (GlucoTab®) and to discuss its impact on hypoglycemia prevention. Methods: The system was tested in a monocentric, open, noncontrolled intervention study in 30 patients with type 2 diabetes mellitus (T2DM). The system supports HCPs in performing a basal-bolus insulin therapy. Diabetes therapy, adverse events, software errors and user feedback were documented. Safety, efficacy and user acceptance of the system were investigated. Results: Only 1.3% of blood glucose (BG) measurements were <70 mg/dl and only 2.6% were >300 mg/dl. The availability of the system (97.3%) and the rate of treatment activities documented with the system (>93.5%) were high. Only few suggestions from the system were overruled by the users (>95.7% adherence). Evaluation of the 3 anonymous questionnaires showed that confidence in the system increased over time. The majority of users believed that treatment errors could be prevented by using this system. Conclusions: Data from our feasibility study show a significant reduction of hypoglycemia by implementing a computerized system for workflow and decision support for diabetes management, compared to a paper-based process. The system was well accepted by HCPs, which is shown in the user acceptance analysis and that users adhered to the insulin dose suggestions made by the system. PMID:27810995

D-Side: A Facility and Workforce Planning Group Multi-criteria Decision Support System for Johnson Space Center

NASA Technical Reports Server (NTRS)

Tavana, Madjid

2005-01-01

"To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers" is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach. Keywords: NASA, Multi-Criteria Decision Making, Decision Support System, AHP, Euclidean Distance, 3-D Modeling, Facility Planning, Workforce Planning.

Proceedings of the workshop "Development of biological decision support systems for resource managers": Denver, Colorado, October 27-29, 1998

USGS Publications Warehouse

Getter, James; D'Erchia, Terry D.; Root, Ralph; Getter, James; D'Erchia, Terry D.; Root, Ralph

1999-01-01

The format for this 3-day workshop (27-29 October 1998) included plenary presentations by USGS Biological Resources Division (BRD) and U.S. Fish and Wildlife Service per onnel who u e and develop decision support systems (DSS); breakout ses ions addressing DSS technical information aspect , outreach/ customer requirements, and future perspectives; and a DSS Steering Committee meeting to evaluate work hop goals and to provide guidance for fu ture efforts. Steering committee action item developed from workshop inputs were to ( I) develop a "DSS framework" document for u e in biological research. (2) develop a "proof of concept" DSS based upon the framework document, and (3) integrate decision support ystem into BRD program elements.

Operationalizing Semantic Medline for meeting the information needs at point of care.

PubMed

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible.

Operationalizing Semantic Medline for meeting the information needs at point of care

PubMed Central

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible. PMID:26306259

NED-2: A decision support system for integrated forest ecosystem management

Treesearch

Mark J. Twery; Peter D. Knopp; Scott A. Thomasma; H. Michael Rauscher; Donald E. Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mayukh Dass; Hajime Uchiyama; Astrid Glende; Robin E. Hoffman

2005-01-01

NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment...

NED-2: a decision support system for integrated forest ecosystem management

Treesearch

Mark J. Twery; Peter D. Knopp; Scott A. Thomasma; H. Michael Rauscher; Donald E. Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mayukh Dass; Hajime Uchiyama; Astrid Glende; Robin E. Hoffman

2005-01-01

NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment...

Classroom Composition and Measured Teacher Performance: What Do Teacher Observation Scores Really Measure?

ERIC Educational Resources Information Center

Steinberg, Matthew P.; Garrett, Rachel

2016-01-01

As states and districts implement more rigorous teacher evaluation systems, measures of teacher performance are increasingly being used to support instruction and inform retention decisions. Classroom observations take a central role in these systems, accounting for the majority of teacher ratings upon which accountability decisions are based.…

Quantifying Risk of Financial Incapacity and Financial Exploitation in Community-dwelling Older Adults: Utility of a Scoring System for the Lichtenberg Financial Decision-making Rating Scale.

PubMed

Lichtenberg, Peter A; Gross, Evan; Ficker, Lisa J

2018-06-08

This work examines the clinical utility of the scoring system for the Lichtenberg Financial Decision-making Rating Scale (LFDRS) and its usefulness for decision making capacity and financial exploitation. Objective 1 was to examine the clinical utility of a person centered, empirically supported, financial decision making scale. Objective 2 was to determine whether the risk-scoring system created for this rating scale is sufficiently accurate for the use of cutoff scores in cases of decisional capacity and cases of suspected financial exploitation. Objective 3 was to examine whether cognitive decline and decisional impairment predicted suspected financial exploitation. Two hundred independently living, non-demented community-dwelling older adults comprised the sample. Participants completed the rating scale and other cognitive measures. Receiver operating characteristic curves were in the good to excellent range for decisional capacity scoring, and in the fair to good range for financial exploitation. Analyses supported the conceptual link between decision making deficits and risk for exploitation, and supported the use of the risk-scoring system in a community-based population. This study adds to the empirical evidence supporting the use of the rating scale as a clinical tool assessing risk for financial decisional impairment and/or financial exploitation.

Development of the Supported Decision Making Inventory System.

PubMed

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

2017-12-01

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

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Astrophysics Data System (ADS)

Szatkowski, Gerard P.; Schultz, Roger

1988-11-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Technical Reports Server (NTRS)

Szatkowski, Gerard P.; Schultz, Roger

1988-01-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Maintenance and operations decision support tool : Clarus regional demonstrations.

DOT National Transportation Integrated Search

2011-01-01

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

Data warehousing: toward knowledge management.

PubMed

Shams, K; Farishta, M

2001-02-01

With rapid changes taking place in the practice and delivery of health care, decision support systems have assumed an increasingly important role. More and more health care institutions are deploying data warehouse applications as decision support tools for strategic decision making. By making the right information available at the right time to the right decision makers in the right manner, data warehouses empower employees to become knowledge workers with the ability to make the right decisions and solve problems, creating strategic leverage for the organization. Health care management must plan and implement data warehousing strategy using a best practice approach. Through the power of data warehousing, health care management can negotiate bettermanaged care contracts based on the ability to provide accurate data on case mix and resource utilization. Management can also save millions of dollars through the implementation of clinical pathways in better resource utilization and changing physician behavior to best practices based on evidence-based medicine.

Digital technology and clinical decision making in depression treatment: Current findings and future opportunities.

PubMed

Hallgren, Kevin A; Bauer, Amy M; Atkins, David C

2017-06-01

Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains. © 2017 Wiley Periodicals, Inc.

A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests.

PubMed

Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A

2015-10-01

Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

GET SMARTE: DECISION TOOLS TO REVITALIZE COMMUNITIES (MAY 2006)

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

RF-CLASS: A Remote-sensing-based Interoperable Web service system for Flood Crop Loss Assessment

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Kang, L.

2014-12-01

Flood is one of the worst natural disasters in the world. Flooding often causes significant crop loss over large agricultural areas in the United States. Two USDA agencies, the National Agricultural Statistics Service (NASS) and Risk Management Agency (RMA), make decisions on flood statistics, crop insurance policy, and recovery management by collecting, analyzing, reporting, and utilizing flooded crop acreage and crop loss information. NASS has the mandate to report crop loss after all flood events. RMA manages crop insurance policy and uses crop loss information to guide the creation of the crop insurance policy and the aftermath compensation. Many studies have been conducted in the recent years on monitoring floods and assessing the crop loss due to floods with remote sensing and geographic information technologies. The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS), being developed with NASA and USDA support, aims to significantly improve the post-flood agricultural decision-making supports in USDA by integrating and advancing the recently developed technologies. RF-CLASS will operationally provide information to support USDA decision making activities on collecting and archiving flood acreage and duration, recording annual crop loss due to flood, assessing the crop insurance rating areas, investigating crop policy compliance, and spot checking of crop loss claims. This presentation will discuss the remote sensing and GIS based methods for deriving the needed information to support the decision making, the RF-CLASS cybersystem architecture, the standards and interoperability arrangements in the system, and the current and planned capabilities of the system.

Evaluation of a decision support system for pressure ulcer prevention and management: preliminary findings.

PubMed

Zielstorff, R D; Estey, G; Vickery, A; Hamilton, G; Fitzmaurice, J B; Barnett, G O

1997-01-01

A decision support system for prevention and management of pressure ulcers was developed based on AHCPR guidelines and other sources. The system was implemented for 21 weeks on a 20-bed clinical care unit. Fifteen nurses on that unit volunteered as subjects of the intervention to see whether use of the system would have a positive effect on their knowledge about pressure ulcers and on their decision-making skills related to this topic. A similar care unit was used as a control. In addition, the system was evaluated by experts for its instructional adequacy, and by end users for their satisfaction with the system. Preliminary results show no effect on knowledge about pressure ulcers and no effect on clinical decision making skills. The system was rated positively for instructional adequacy, and positively for user satisfaction. User interviews related to satisfaction supplemented the quantitative findings. A discussion of the issues of conducting experiments like this in today's clinical environment is included.

A qualitative analysis of coronary heart disease patient views of dietary adherence and web-based and mobile-based nutrition tools

PubMed Central

Yehle, Karen S.; Chen, Aleda M. H.; Plake, Kimberly S.; Yi, Ji Soo; Mobley, Amy R.

2012-01-01

PURPOSE Dietary adherence can be challenging for patients with coronary heart disease (CHD), as they may require multiple dietary changes. Choosing appropriate food items may be difficult or take extensive amounts of time without the aid of technology. The objective of this project was to (1) examine the dietary challenges faced by patients with CHD, (2) examine methods of coping with dietary challenges, (3) explore the feasibility of a web-based food decision support system, and (4) explore the feasibility of a mobile-based food decision support system. METHODS Food for the Heart (FFH), a website-based food decision support system, and Mobile Magic Lens (MML), a mobile-based system, were developed to aid in daily dietary choices. Three CHD patient focus groups were conducted and focused on CHD-associated dietary changes as well as the FFH and MML prototypes. A total of 20 CHD patients and 7 informal caregivers participated. Qualitative, content analysis was performed to find themes grounded in the responses. RESULTS Five predominant themes emerged: 1) decreasing carbohydrate intake and portion control are common dietary challenges, 2) clinician and social support makes dietary adherence easier, 3) FFH could make meal-planning and dietary adherence less complicated, 4) MML could save time and assist with healthy choices, and 5) additional features need to be added to make both tools more comprehensive. CONCLUSIONS FFH and MML may be tools that CHD patients would value in making food choices and adhering to dietary recommendations, especially if additional features are added to assist patients with changes. PMID:22760245

A computerized handheld decision-support system to improve pulmonary embolism diagnosis: a randomized trial.

PubMed

Roy, Pierre-Marie; Durieux, Pierre; Gillaizeau, Florence; Legall, Catherine; Armand-Perroux, Aurore; Martino, Ludovic; Hachelaf, Mohamed; Dubart, Alain-Eric; Schmidt, Jeannot; Cristiano, Mirko; Chretien, Jean-Marie; Perrier, Arnaud; Meyer, Guy

2009-11-17

Testing for pulmonary embolism often differs from that recommended by evidence-based guidelines. To assess the effectiveness of a handheld clinical decision-support system to improve the diagnostic work-up of suspected pulmonary embolism among patients in the emergency department. Cluster randomized trial. Assignment was by random-number table, providers were not blinded, and outcome assessment was automated. (ClinicalTrials.gov registration number: NCT00188032). 20 emergency departments in France. 1103 and 1768 consecutive outpatients with suspected pulmonary embolism. After a preintervention period involving 20 centers and 1103 patients, in which providers grew accustomed to inputting clinical data into handheld devices and investigators assessed baseline testing, emergency departments were randomly assigned to activation of a decision-support system on the devices (10 centers, 753 patients) or posters and pocket cards that showed validated diagnostic strategies (10 centers, 1015 patients). Appropriateness of diagnostic work-up, defined as any sequence of tests that yielded a posttest probability less than 5% or greater than 85% (primary outcome) or as strict adherence to guideline recommendations (secondary outcome); number of tests per patient (secondary outcome). The proportion of patients who received appropriate diagnostic work-ups was greater during the trial than in the preintervention period in both groups, but the increase was greater in the computer-based guidelines group (adjusted mean difference in increase, 19.3 percentage points favoring computer-based guidelines [95% CI, 2.9 to 35.6 percentage points]; P = 0.023). Among patients with appropriate work-ups, those in the computer-based guidelines group received slightly fewer tests than did patients in the paper guidelines group (mean tests per patient, 1.76 [SD, 0.98] vs. 2.25 [SD, 1.04]; P < 0.001). The study was not designed to show a difference in the clinical outcomes of patients during follow-up. A handheld decision-support system improved diagnostic decision making for patients with suspected pulmonary embolism in the emergency department.

Artificial intelligence based decision support for trumpeter swan management

USGS Publications Warehouse

Sojda, Richard S.

2002-01-01

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 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.

PubMed

Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí

2014-11-28

The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

PubMed Central

2014-01-01

Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems. PMID:25471545

Decision Support Systems: Applications in Statistics and Hypothesis Testing.

ERIC Educational Resources Information Center

Olsen, Christopher R.; Bozeman, William C.

1988-01-01

Discussion of the selection of appropriate statistical procedures by educators highlights a study conducted to investigate the effectiveness of decision aids in facilitating the use of appropriate statistics. Experimental groups and a control group using a printed flow chart, a computer-based decision aid, and a standard text are described. (11…

Therapy Decision Support Based on Recommender System Methods

PubMed Central

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

2017-01-01

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

A Decision Support System for Evaluating and Selecting Information Systems Projects

NASA Astrophysics Data System (ADS)

Deng, Hepu; Wibowo, Santoso

2009-01-01

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

Arctic Collaborative Environment: A New Multi-National Partnership for Arctic Science and Decision Support

NASA Technical Reports Server (NTRS)

Laymon, Charles A,; Kress, Martin P.; McCracken, Jeff E.; Spehn, Stephen L.; Tanner, Steve

2011-01-01

The Arctic Collaborative Environment (ACE) project is a new international partnership for information sharing to meet the challenges of addressing Arctic. The goal of ACE is to create an open source, web-based, multi-national monitoring, analysis, and visualization decision-support system for Arctic environmental assessment, management, and sustainability. This paper will describe the concept, system architecture, and data products that are being developed and disseminated among partners and independent users through remote access.

A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.

2014-03-01

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.

A Semantic Approach with Decision Support for Safety Service in Smart Home Management

PubMed Central

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-01-01

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

PubMed

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-08-03

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

Toward patient-centered, personalized and personal decision support and knowledge management: a survey.

PubMed

Leong, T-Y

2012-01-01

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 participatory health care model for patient-centered, personalized medicine. There is also an increasing emphasis on managing complexity with changing care models, processes, and settings.

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

PubMed

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

2017-02-01

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

Medical knowledge packages and their integration into health-care information systems and the World Wide Web.

PubMed

Adlassnig, Klaus-Peter; Rappelsberger, Andrea

2008-01-01

Software-based medical knowledge packages (MKPs) are packages of highly structured medical knowledge that can be integrated into various health-care information systems or the World Wide Web. They have been established to provide different forms of clinical decision support such as textual interpretation of combinations of laboratory rest results, generating diagnostic hypotheses as well as confirmed and excluded diagnoses to support differential diagnosis in internal medicine, or for early identification and automatic monitoring of hospital-acquired infections. Technically, an MKP may consist of a number of inter-connected Arden Medical Logic Modules. Several MKPs have been integrated thus far into hospital, laboratory, and departmental information systems. This has resulted in useful and widely accepted software-based clinical decision support for the benefit of the patient, the physician, and the organization funding the health care system.

Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

NASA Astrophysics Data System (ADS)

da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

2018-02-01

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

A decision support system using combined-classifier for high-speed data stream in smart grid

NASA Astrophysics Data System (ADS)

Yang, Hang; Li, Peng; He, Zhian; Guo, Xiaobin; Fong, Simon; Chen, Huajun

2016-11-01

Large volume of high-speed streaming data is generated by big power grids continuously. In order to detect and avoid power grid failure, decision support systems (DSSs) are commonly adopted in power grid enterprises. Among all the decision-making algorithms, incremental decision tree is the most widely used one. In this paper, we propose a combined classifier that is a composite of a cache-based classifier (CBC) and a main tree classifier (MTC). We integrate this classifier into a stream processing engine on top of the DSS such that high-speed steaming data can be transformed into operational intelligence efficiently. Experimental results show that our proposed classifier can return more accurate answers than other existing ones.

Selection criteria and facilitation training for the study of groupware

NASA Technical Reports Server (NTRS)

Robichaux, Barry P.

1993-01-01

Computer support for planning and decision making groups is a growing trend in the 90s. Groupware is a name often applied to group software and has been defined as 'computer-based systems that support groups engaged in a common task (or goal) and that provide an interface to a shared environment'. Unlike most single-user software, groupware assists user groups in their collaboration, coordination, and communication efforts. This paper focuses on groupware to support the meeting process. These systems are often called group decision support systems (GDSS), electronic meeting systems (EMS), or group support systems (GSS). The term 'meeting support groupware' is used here to include any computer-based system to support meetings. In order to understand this technology, one must first understand groups, what they do and the problems they face, and groupware, a wide range of technology to support group work. Guidelines for selecting groups for study as part of an overall research plan are provided in this document. These were taken from the literature and from persons for whom the information in this paper was targeted. Also, guidelines for facilitation training are discussed. Familiarity with known and accepted techniques are the principle duties of the facilitator and any form of training must include practice in using these techniques.

Web-Based Cancer Communication and Decision Making Systems: Connecting Patients, Caregivers, and Clinicians for Improved Health Outcomes

PubMed Central

DuBenske, Lori L.; Gustafson, David H.; Shaw, Bret R.; Cleary, James F.

2011-01-01

Over the cancer disease trajectory, from diagnosis and treatment to remission or end of life, patients and their families face difficult decisions. The provision of information and support when most relevant can optimize cancer decision making and coping. An interactive health communication system (IHCS) offers the potential to bridge the communication gaps that occur among patients, family, and clinicians and to empower each to actively engage in cancer care and shared decision making. This is a report of the authors' experience (with a discussion of relevant literature) in developing and testing a Web-based IHCS—the Comprehensive Health Enhancement Support System (CHESS)—for patients with advanced lung cancer and their family caregivers. CHESS provides information, communication, and coaching resources as well as a symptom tracking system that reports health status to the clinical team. Development of an IHCS includes a needs assessment of the target audience and applied theory informed by continued stakeholder involvement in early testing. Critical issues of IHCS implementation include 1) need for interventions that accommodate a variety of format preferences and technology comfort ranges; 2) IHCS user training, 3) clinician investment in IHCS promotion, and 4) IHCS integration with existing medical systems. In creating such comprehensive systems, development strategies need to be grounded in population needs with appropriate use of technology that serves the target users, including the patient/family, clinical team, and health care organization. Implementation strategies should address timing, personnel, and environmental factors to facilitate continued use and benefit from IHCS. An interactive health communication system (IHCS) offers one platform for providing the information, communication, and coaching resources that cancer patients and their families need to understand the disease, find support, and develop decision-making and coping skills. One such IHCS—the Comprehensive Health Enhancement Support System (CHESS)—has evolved over the past 20 years. Based on our recent experience creating and testing a new version of CHESS—“Coping with Lung Cancer: A Network of Support”—this article outlines the issues faced in developing and implementing such a system within the cancer context. PMID:21041539

A Computational Model of Reasoning from the Clinical Literature

PubMed Central

Rennels, Glenn D.

1986-01-01

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Imaging informatics-based multimedia ePR system for data management and decision support in rehabilitation research

NASA Astrophysics Data System (ADS)

Wang, Ximing; Verma, Sneha; Qin, Yi; Sterling, Josh; Zhou, Alyssa; Zhang, Jeffrey; Martinez, Clarisa; Casebeer, Narissa; Koh, Hyunwook; Winstein, Carolee; Liu, Brent

2013-03-01

With the rapid development of science and technology, large-scale rehabilitation centers and clinical rehabilitation trials usually involve significant volumes of multimedia data. Due to the global aging crisis, millions of new patients with age-related chronic diseases will produce huge amounts of data and contribute to soaring costs of medical care. Hence, a solution for effective data management and decision support will significantly reduce the expenditure and finally improve the patient life quality. Inspired from the concept of the electronic patient record (ePR), we developed a prototype system for the field of rehabilitation engineering. The system is subject or patient-oriented and customized for specific projects. The system components include data entry modules, multimedia data presentation and data retrieval. To process the multimedia data, the system includes a DICOM viewer with annotation tools and video/audio player. The system also serves as a platform for integrating decision-support tools and data mining tools. Based on the prototype system design, we developed two specific applications: 1) DOSE (a phase 1 randomized clinical trial to determine the optimal dose of therapy for rehabilitation of the arm and hand after stroke.); and 2) NEXUS project from the Rehabilitation Engineering Research Center(RERC, a NIDRR funded Rehabilitation Engineering Research Center). Currently, the system is being evaluated in the context of the DOSE trial with a projected enrollment of 60 participants over 5 years, and will be evaluated by the NEXUS project with 30 subjects. By applying the ePR concept, we developed a system in order to improve the current research workflow, reduce the cost of managing data, and provide a platform for the rapid development of future decision-support tools.

Computer Based Decision Support Tool for Helicopter Mission Planning in Disaster Relief and Military Operations (Outil informatique d’aide a la decision pour la planification des missions d’helicopteres dans des operations militaires et de secours en cas de catastrophe)

DTIC Science & Technology

2008-06-01

capacity planning; • Electrical generation capacity planning; • Machine scheduling; • Freight scheduling; • Dairy farm expansion planning...Support Systems and Multi Criteria Decision Analysis Products A.2.11.2.2.1 ELECTRE IS ELECTRE IS is a generalization of ELECTRE I. It is a...criteria, ELECTRE IS supports the user in the process of selecting one alternative or a subset of alternatives. The method consists of two parts

A web-based decision support tool for prognosis simulation in multiple sclerosis.

PubMed

Veloso, Mário

2014-09-01

A multiplicity of natural history studies of multiple sclerosis provides valuable knowledge of the disease progression but individualized prognosis remains elusive. A few decision support tools that assist the clinician in such task have emerged but have not received proper attention from clinicians and patients. The objective of the current work is to implement a web-based tool, conveying decision relevant prognostic scientific evidence, which will help clinicians discuss prognosis with individual patients. Data were extracted from a set of reference studies, especially those dealing with the natural history of multiple sclerosis. The web-based decision support tool for individualized prognosis simulation was implemented with NetLogo, a program environment suited for the development of complex adaptive systems. Its prototype has been launched online; it enables clinicians to predict both the likelihood of CIS to CDMS conversion, and the long-term prognosis of disability level and SPMS conversion, as well as assess and monitor the effects of treatment. More robust decision support tools, which convey scientific evidence and satisfy the needs of clinical practice by helping clinicians discuss prognosis expectations with individual patients, are required. The web-based simulation model herein introduced proposes to be a step forward toward this purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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

2009-01-01

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

A Decision Support System for Concrete Bridge Maintenance

NASA Astrophysics Data System (ADS)

Rashidi, Maria; Lemass, Brett; Gibson, Peter

2010-05-01

The maintenance of bridges as a key element in transportation infrastructure has become a major concern for asset managers and society due to increasing traffic volumes, deterioration of existing bridges and well-publicised bridge failures. A pivotal responsibility for asset managers in charge of bridge remediation is to identify the risks and assess the consequences of remediation programs to ensure that the decisions are transparent and lead to the lowest predicted losses in recognized constraint areas. The ranking of bridge remediation treatments can be quantitatively assessed using a weighted constraint approach to structure the otherwise ill-structured phases of problem definition, conceptualization and embodiment [1]. This Decision Support System helps asset managers in making the best decision with regards to financial limitations and other dominant constraints imposed upon the problem at hand. The risk management framework in this paper deals with the development of a quantitative intelligent decision support system for bridge maintenance which has the ability to provide a source for consistent decisions through selecting appropriate remediation treatments based upon cost, service life, product durability/sustainability, client preferences, legal and environmental constraints. Model verification and validation through industry case studies is ongoing.

Integration of evidence-based knowledge management in microsystems: a tele-ICU experience.

PubMed

Rincon, Teresa A

2012-01-01

The Institute of Medicine's proposed 6 aims to improve health care are timely, safe, effective, efficient, equitable, and patient-centered care. Unfortunately, it also asserts that improvements in these 6 dimensions cannot be achieved within the existing framework of care systems. These systems are based on unrealistic expectations on human cognition and vigilance, and demonstrate a lack of dependence on computerized systems to support care processes and put information at the point of use. Knowledge-based care and evidence-based clinical decision-making need to replace the unscientific care that is being delivered in health care. Building care practices on evidence within an information technology platform is needed to support sound clinical decision-making and to influence organizational adoption of evidence-based practice in health care. Despite medical advances and evidence-based recommendations for treatment of severe sepsis, it remains a significant cause of mortality and morbidity in the world. It is a complex disease state that has proven difficult to define, diagnose, and treat. Supporting bedside teams with real-time knowledge and expertise to target early identification of severe sepsis and compliance to Surviving Sepsis Campaign, evidence-based practice bundles are important to improving outcomes. Using a centralized, remote team of expert nurses and an open-source software application to advance clinical decision-making and execution of the severe sepsis bundle will be examined.

The Impact of Electronic Knowledge-Based Nursing Content and Decision-Support on Nursing-Sensitive Patient Outcomes

DTIC Science & Technology

2014-02-01

aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information...if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE February 2014 2... Akre , et al., 2006) content and evidence-based clinical decision support (CDS) tools were embedded into the EHR of one large health care system. Since

Development of a model-based flood emergency management system in Yujiang River Basin, South China

NASA Astrophysics Data System (ADS)

Zeng, Yong; Cai, Yanpeng; Jia, Peng; Mao, Jiansu

2014-06-01

Flooding is the most frequent disaster in China. It affects people's lives and properties, causing considerable economic loss. Flood forecast and operation of reservoirs are important in flood emergency management. Although great progress has been achieved in flood forecast and reservoir operation through using computer, network technology, and geographic information system technology in China, the prediction accuracy of models are not satisfactory due to the unavailability of real-time monitoring data. Also, real-time flood control scenario analysis is not effective in many regions and can seldom provide online decision support function. In this research, a decision support system for real-time flood forecasting in Yujiang River Basin, South China (DSS-YRB) is introduced in this paper. This system is based on hydrological and hydraulic mathematical models. The conceptual framework and detailed components of the proposed DSS-YRB is illustrated, which employs real-time rainfall data conversion, model-driven hydrologic forecasting, model calibration, data assimilation methods, and reservoir operational scenario analysis. Multi-tiered architecture offers great flexibility, portability, reusability, and reliability. The applied case study results show the development and application of a decision support system for real-time flood forecasting and operation is beneficial for flood control.

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

PubMed Central

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

2013-01-01

Objective To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. Materials and Methods A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. Results Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. Conclusions Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows. PMID:23467470

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

NASA Astrophysics Data System (ADS)

Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.

2011-12-01

A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.

Accounting for reasonableness: Exploring the personal internal framework affecting decisions about cancer drug funding.

PubMed

Sinclair, Shane; Hagen, Neil A; Chambers, Carole; Manns, Braden; Simon, Anita; Browman, George P

2008-05-01

Drug decision-makers are involved in developing and implementing policy, procedure and processes to support health resource allocation regarding drug treatment formularies. A variety of approaches to decision-making, including formal decision-making frameworks, have been developed to support transparent and fair priority setting. Recently, a decision tool, 'The 6-STEPPPs Tool', was developed to assist in making decisions about new cancer drugs within the public health care system. We conducted a qualitative study, utilizing focus groups and participant observation, in order to investigate the internal frameworks that supported and challenged individual participants as they applied this decision tool within a multi-stakeholder decision process. We discovered that health care resource allocation engaged not only the minds of decision-makers but profoundly called on the often conflicting values of the heart. Objective decision-making frameworks for new drug therapies need to consider the subjective internal frameworks of decision-makers that affect decisions. Understanding the very human, internal turmoil experienced by individuals involved in health care resource allocation, sheds additional insight into how to account for reasonableness and how to better support difficult decisions through transparent, values-based resource allocation policy, procedures and processes.

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

PubMed

Haynes, R Brian; Wilczynski, Nancy L

2010-02-05

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

A Decision Support System for Evaluating Systems of Undersea Sensors and Weapons

DTIC Science & Technology

2015-12-01

distribution is unlimited A DECISION SUPPORT SYSTEM FOR EVALUATING SYSTEMS OF UNDERSEA SENSORS AND WEAPONS by Team Mental Focus Cohort 142O...A DECISION SUPPORT SYSTEM FOR EVALUATING SYSTEMS OF UNDERSEA SENSORS AND WEAPONS 5. FUNDING NUMBERS 6. AUTHOR(S) Systems Engineering Cohort...undersea weapons, it requires the supporting tools to evaluate and predict the effectiveness of these system concepts. While current naval minefield

Using a Clinical Knowledge Base to Assess Comorbidity Interrelatedness Among Patients with Multiple Chronic Conditions.

PubMed

Zulman, Donna M; Martins, Susana B; Liu, Yan; Tu, Samson W; Hoffman, Brian B; Asch, Steven M; Goldstein, Mary K

2015-01-01

Decision support tools increasingly integrate clinical knowledge such as medication indications and contraindications with electronic health record (EHR) data to support clinical care and patient safety. The availability of this encoded information and patient data provides an opportunity to develop measures of clinical decision complexity that may be of value for quality improvement and research efforts. We investigated the feasibility of using encoded clinical knowledge and EHR data to develop a measure of comorbidity interrelatedness (the degree to which patients' co-occurring conditions interact to generate clinical complexity). Using a common clinical scenario-decisions about blood pressure medications in patients with hypertension-we quantified comorbidity interrelatedness by calculating the number of indications and contraindications to blood pressure medications that are generated by patients' comorbidities (e.g., diabetes, gout, depression). We examined properties of comorbidity interrelatedness using data from a decision support system for hypertension in the Veterans Affairs Health Care System.

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

Treesearch

Erin K. Noonan-Wright; Tonja S. Opperman

2015-01-01

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

Will Decision Support in Medications Order Entry Save Money? A Return On Investment Analysis of the Case of the Hong Kong Hospital Authority

PubMed Central

Fung, Kin Wah; Vogel, Lynn Harold

2003-01-01

The computerized medications order entry system currently used in the public hospitals of Hong Kong does not have decision support features. Plans are underway to add decision support to this system to alert physicians on drug-allergy conflicts, drug-lab result conflicts, drug-drug interactions and atypical dosages. A return on investment analysis is done on this enhancement, both as an examination of whether there is a positive return on the investment and as a contribution to the ongoing discussion of the use of return on investment models in health care information technology investments. It is estimated that the addition of decision support will reduce adverse drug events by 4.2 – 8.4%. Based on this estimate, a total net saving of $44,000 – $586,000 is expected over five years. The breakeven period is estimated to be between two to four years. PMID:14728171

An Integrated Decision Support System for Water Quality Management of Songhua River Basin

NASA Astrophysics Data System (ADS)

Zhang, Haiping; Yin, Qiuxiao; Chen, Ling

2010-11-01

In the Songhua River Basin of China, many water resource and water environment conflicts interact. A Decision Support System (DSS) for the water quality management has been established for the Basin. The System is featured by the incorporation of a numerical water quality model system into a conventional water quality management system which usually consists of geographic information system (GIS), WebGIS technology, database system and network technology. The model system is built based on DHI MIKE software comprising of a basin rainfall-runoff module, a basin pollution load evaluation module, a river hydrodynamic module and a river water quality module. The DSS provides a friendly graphical user interface that enables the rapid and transparent calculation of various water quality management scenarios, and also enables the convenient access and interpretation of the modeling results to assist the decision-making.

A GIS-based decision support system for regional eco-security assessment and its application on the Tibetan Plateau.

PubMed

Xiaodan, Wang; Xianghao, Zhong; Pan, Gao

2010-10-01

Regional eco-security assessment is an intricate, challenging task. In previous studies, the integration of eco-environmental models and geographical information systems (GIS) usually takes two approaches: loose coupling and tight coupling. However, the present study used a full coupling approach to develop a GIS-based regional eco-security assessment decision support system (ESDSS). This was achieved by merging the pressure-state-response (PSR) model and the analytic hierarchy process (AHP) into ArcGIS 9 as a dynamic link library (DLL) using ArcObjects in ArcGIS and Visual Basic for Applications. Such an approach makes it easy to capitalize on the GIS visualization and spatial analysis functions, thereby significantly supporting the dynamic estimation of regional eco-security. A case study is presented for the Tibetan Plateau, known as the world's "third pole" after the Arctic and Antarctic. Results verified the usefulness and feasibility of the developed method. As a useful tool, the ESDSS can also help local managers to make scientifically-based and effective decisions about Tibetan eco-environmental protection and land use. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Semantic technologies in a decision support system

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2015-10-01

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).

Airborne Tactical Intent-Based Conflict Resolution Capability

NASA Technical Reports Server (NTRS)

Wing, David J.; Vivona, Robert A.; Roscoe, David A.

2009-01-01

Trajectory-based operations with self-separation involve the aircraft taking the primary role in the management of its own trajectory in the presence of other traffic. In this role, the flight crew assumes the responsibility for ensuring that the aircraft remains separated from all other aircraft by at least a minimum separation standard. These operations are enabled by cooperative airborne surveillance and by airborne automation systems that provide essential monitoring and decision support functions for the flight crew. An airborne automation system developed and used by NASA for research investigations of required functionality is the Autonomous Operations Planner. It supports the flight crew in managing their trajectory when responsible for self-separation by providing monitoring and decision support functions for both strategic and tactical flight modes. The paper focuses on the latter of these modes by describing a capability for tactical intent-based conflict resolution and its role in a comprehensive suite of automation functions supporting trajectory-based operations with self-separation.

Hypothesis-confirming information search strategies and computerized information-retrieval systems

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

Jacobs, S.M.

A recent trend in information-retrieval systems technology is the development of on-line information retrieval systems. One objective of these systems has been to attempt to enhance decision effectiveness by allowing users to preferentially seek information, thereby facilitating the reduction or elimination of information overload. These systems do not necessarily lead to more-effective decision making, however. Recent research in information-search strategy suggests that when users are seeking information subsequent to forming initial beliefs, they may preferentially seek information to confirm these beliefs. It seems that effective computer-based decision support requires an information retrieval system capable of: (a) retrieving a subset ofmore » all available information, in order to reduce information overload, and (b) supporting an information search strategy that considers all relevant information, rather than merely hypothesis-confirming information. An information retrieval system with an expert component (i.e., a knowledge-based DSS) should be able to provide these capabilities. Results of this study are non conclusive; there was neither strong confirmatory evidence nor strong disconfirmatory evidence regarding the effectiveness of the KBDSS.« less

An Artificial Neural Network-Based Decision-Support System for Integrated Network Security

DTIC Science & Technology

2014-09-01

group that they need to know in order to make team-based decisions in real-time environments, (c) Employ secure cloud computing services to host mobile...THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force...out-of-the-loop syndrome and create complexity creep. As a result, full automation efforts can lead to inappropriate decision-making despite a

Perceptions of risk, risk aversion, and barriers to adoption of decision support systems and integrated pest management: an introduction.

PubMed

Gent, David H; De Wolf, Erick; Pethybridge, Sarah J

2011-06-01

Rational management of plant diseases, both economically and environmentally, involves assessing risks and the costs associated with both correct and incorrect tactical management decisions to determine when control measures are warranted. Decision support systems can help to inform users of plant disease risk and thus assist in accurately targeting events critical for management. However, in many instances adoption of these systems for use in routine disease management has been perceived as slow. The under-utilization of some decision support systems is likely due to both technical and perception constraints that have not been addressed adequately during development and implementation phases. Growers' perceptions of risk and their aversion to these perceived risks can be reasons for the "slow" uptake of decision support systems and, more broadly, integrated pest management (IPM). Decision theory provides some tools that may assist in quantifying and incorporating subjective and/or measured probabilities of disease occurrence or crop loss into decision support systems. Incorporation of subjective probabilities into IPM recommendations may be one means to reduce grower uncertainty and improve trust of these systems because management recommendations could be explicitly informed by growers' perceptions of risk and economic utility. Ultimately though, we suggest that an appropriate measure of the value and impact of decision support systems is grower education that enables more skillful and informed management decisions independent of consultation of the support tool outputs.

A decision support system and rule-based algorithm to augment the human interpretation of the 12-lead electrocardiogram.

PubMed

Cairns, Andrew W; Bond, Raymond R; Finlay, Dewar D; Guldenring, Daniel; Badilini, Fabio; Libretti, Guido; Peace, Aaron J; Leslie, Stephen J

The 12-lead Electrocardiogram (ECG) has been used to detect cardiac abnormalities in the same format for more than 70years. However, due to the complex nature of 12-lead ECG interpretation, there is a significant cognitive workload required from the interpreter. This complexity in ECG interpretation often leads to errors in diagnosis and subsequent treatment. We have previously reported on the development of an ECG interpretation support system designed to augment the human interpretation process. This computerised decision support system has been named 'Interactive Progressive based Interpretation' (IPI). In this study, a decision support algorithm was built into the IPI system to suggest potential diagnoses based on the interpreter's annotations of the 12-lead ECG. We hypothesise semi-automatic interpretation using a digital assistant can be an optimal man-machine model for ECG interpretation. To improve interpretation accuracy and reduce missed co-abnormalities. The Differential Diagnoses Algorithm (DDA) was developed using web technologies where diagnostic ECG criteria are defined in an open storage format, Javascript Object Notation (JSON), which is queried using a rule-based reasoning algorithm to suggest diagnoses. To test our hypothesis, a counterbalanced trial was designed where subjects interpreted ECGs using the conventional approach and using the IPI+DDA approach. A total of 375 interpretations were collected. The IPI+DDA approach was shown to improve diagnostic accuracy by 8.7% (although not statistically significant, p-value=0.1852), the IPI+DDA suggested the correct interpretation more often than the human interpreter in 7/10 cases (varying statistical significance). Human interpretation accuracy increased to 70% when seven suggestions were generated. Although results were not found to be statistically significant, we found; 1) our decision support tool increased the number of correct interpretations, 2) the DDA algorithm suggested the correct interpretation more often than humans, and 3) as many as 7 computerised diagnostic suggestions augmented human decision making in ECG interpretation. Statistical significance may be achieved by expanding sample size. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of Advanced Respiratory Support Onboard ISS and CCV

NASA Technical Reports Server (NTRS)

Shah, Ronak V.; Kertsman, Eric L.; Alexander, David J.; Duchesne, Ted; Law, Jennifer; Roden, Sean K.

2014-01-01

NASA is collaborating with private entities for the development of commercial space vehicles. The Space and Clinical Operations Division was tasked to review the oxygen and respiratory support system and recommend what capabilities, if any, the vehicle should have to support the return of an ill or injured crewmember. The Integrated Medical Model (IMM) was utilized as a data source for the development of these recommendations. The Integrated Medical Model (IMM) was used to simulate a six month, six crew, International Space Station (ISS) mission. Three medical system scenarios were considered based on the availability of (1) oxygen only, (2) oxygen and a ventilator, or (3) neither oxygen nor ventilator. The IMM analysis provided probability estimates of medical events that would require either oxygen or ventilator support. It also provided estimates of crew health, the probability of evacuation, and the probability of loss of crew life secondary to medical events for each of the three medical system scenarios. These IMM outputs were used as objective data to enable evidence-based decisions regarding oxygen and respiratory support system requirements for commercial crew vehicles. The IMM provides data that may be utilized to support informed decisions regarding the development of medical systems for commercial crew vehicles.

Research on tobacco enterprise spatial decision support system based on GIS

NASA Astrophysics Data System (ADS)

Mei, Xin; Cui, Weihong

2006-10-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique taking GIS as representation to construct spatial decision support system of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision is given. At last the example of tobacco enterprise spatial CRM (client relation management) system is set up.

“Smart Forms” in an Electronic Medical Record: Documentation-based Clinical Decision Support to Improve Disease Management

PubMed Central

Schnipper, Jeffrey L.; Linder, Jeffrey A.; Palchuk, Matvey B.; Einbinder, Jonathan S.; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing “Smart Forms” to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions. PMID:18436911

"Smart Forms" in an Electronic Medical Record: documentation-based clinical decision support to improve disease management.

PubMed

Schnipper, Jeffrey L; Linder, Jeffrey A; Palchuk, Matvey B; Einbinder, Jonathan S; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing "Smart Forms" to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions.

Neural network modeling for surgical decisions on traumatic brain injury patients.

PubMed

Li, Y C; Liu, L; Chiu, W T; Jian, W S

2000-01-01

Computerized medical decision support systems have been a major research topic in recent years. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. This report compares three different mathematical models for building a traumatic brain injury (TBI) medical decision support system (MDSS). These models were developed based on a large TBI patient database. This MDSS accepts a set of patient data such as the types of skull fracture, Glasgow Coma Scale (GCS), episode of convulsion and return the chance that a neurosurgeon would recommend an open-skull surgery for this patient. The three mathematical models described in this report including a logistic regression model, a multi-layer perceptron (MLP) neural network and a radial-basis-function (RBF) neural network. From the 12,640 patients selected from the database. A randomly drawn 9480 cases were used as the training group to develop/train our models. The other 3160 cases were in the validation group which we used to evaluate the performance of these models. We used sensitivity, specificity, areas under receiver-operating characteristics (ROC) curve and calibration curves as the indicator of how accurate these models are in predicting a neurosurgeon's decision on open-skull surgery. The results showed that, assuming equal importance of sensitivity and specificity, the logistic regression model had a (sensitivity, specificity) of (73%, 68%), compared to (80%, 80%) from the RBF model and (88%, 80%) from the MLP model. The resultant areas under ROC curve for logistic regression, RBF and MLP neural networks are 0.761, 0.880 and 0.897, respectively (P < 0.05). Among these models, the logistic regression has noticeably poorer calibration. This study demonstrated the feasibility of applying neural networks as the mechanism for TBI decision support systems based on clinical databases. The results also suggest that neural networks may be a better solution for complex, non-linear medical decision support systems than conventional statistical techniques such as logistic regression.

Comparison of Computer-based Clinical Decision Support Systems and Content for Diabetes Mellitus.

PubMed

Kantor, M; Wright, A; Burton, M; Fraser, G; Krall, M; Maviglia, S; Mohammed-Rajput, N; Simonaitis, L; Sonnenberg, F; Middleton, B

2011-01-01

Computer-based clinical decision support (CDS) systems have been shown to improve quality of care and workflow efficiency, and health care reform legislation relies on electronic health records and CDS systems to improve the cost and quality of health care in the United States; however, the heterogeneity of CDS content and infrastructure of CDS systems across sites is not well known. We aimed to determine the scope of CDS content in diabetes care at six sites, assess the capabilities of CDS in use at these sites, characterize the scope of CDS infrastructure at these sites, and determine how the sites use CDS beyond individual patient care in order to identify characteristics of CDS systems and content that have been successfully implemented in diabetes care. We compared CDS systems in six collaborating sites of the Clinical Decision Support Consortium. We gathered CDS content on care for patients with diabetes mellitus and surveyed institutions on characteristics of their site, the infrastructure of CDS at these sites, and the capabilities of CDS at these sites. The approach to CDS and the characteristics of CDS content varied among sites. Some commonalities included providing customizability by role or user, applying sophisticated exclusion criteria, and using CDS automatically at the time of decision-making. Many messages were actionable recommendations. Most sites had monitoring rules (e.g. assessing hemoglobin A1c), but few had rules to diagnose diabetes or suggest specific treatments. All sites had numerous prevention rules including reminders for providing eye examinations, influenza vaccines, lipid screenings, nephropathy screenings, and pneumococcal vaccines. Computer-based CDS systems vary widely across sites in content and scope, but both institution-created and purchased systems had many similar features and functionality, such as integration of alerts and reminders into the decision-making workflow of the provider and providing messages that are actionable recommendations.

US-German Cooperation For Further Development Of Decision Support Systems For Sustainable Contaminated Site Revitalization - Berlin, Germany, Sept. 24, 2008.

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools - electronic) is a web-based decision support tool developed by the Office of Research and Development (ORD) in partnership with the Office of Brownfields and Land Revital...

A multidisciplinary decision support system for forest fire crisis management.

PubMed

Keramitsoglou, Iphigenia; Kiranoudis, Chris T; Sarimveis, Haralambos; Sifakis, Nicolaos

2004-02-01

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The system's architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

Developing the U.S. Wildland Fire Decision Support System

Treesearch

Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler

2011-01-01

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...

A novel personal health system with integrated decision support and guidance for the management of chronic liver disease.

PubMed

Kiefer, Stephan; Schäfer, Michael; Bransch, Marco; Brimmers, Peter; Bartolomé, Diego; Baños, Janie; Orr, James; Jones, Dave; Jara, Maximilian; Stockmann, Martin

2014-01-01

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.

Detection of Hard Exudates in Colour Fundus Images Using Fuzzy Support Vector Machine-Based Expert System.

PubMed

Jaya, T; Dheeba, J; Singh, N Albert

2015-12-01

Diabetic retinopathy is a major cause of vision loss in diabetic patients. Currently, there is a need for making decisions using intelligent computer algorithms when screening a large volume of data. This paper presents an expert decision-making system designed using a fuzzy support vector machine (FSVM) classifier to detect hard exudates in fundus images. The optic discs in the colour fundus images are segmented to avoid false alarms using morphological operations and based on circular Hough transform. To discriminate between the exudates and the non-exudates pixels, colour and texture features are extracted from the images. These features are given as input to the FSVM classifier. The classifier analysed 200 retinal images collected from diabetic retinopathy screening programmes. The tests made on the retinal images show that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and features sets, the area under the receiver operating characteristic curve reached 0.9606, which corresponds to a sensitivity of 94.1% with a specificity of 90.0%. The results suggest that detecting hard exudates using FSVM contribute to computer-assisted detection of diabetic retinopathy and as a decision support system for ophthalmologists.

An Intelligent Decision Support System for Workforce Forecast

DTIC Science & Technology

2011-01-01

ARIMA ) model to forecast the demand for construction skills in Hong Kong. This model was based...Decision Trees ARIMA Rule Based Forecasting Segmentation Forecasting Regression Analysis Simulation Modeling Input-Output Models LP and NLP Markovian...data • When results are needed as a set of easily interpretable rules 4.1.4 ARIMA Auto-regressive, integrated, moving-average ( ARIMA ) models

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

PubMed Central

2010-01-01

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 EBDM/EBPM process can be improved. PMID:20504357

Rationality versus reality: the challenges of evidence-based decision making for health policy makers.

PubMed

McCaughey, Deirdre; Bruning, Nealia S

2010-05-26

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 improved.

Web-based GIS for collaborative planning and public participation: an application to the strategic planning of wind farm sites.

PubMed

Simão, Ana; Densham, Paul J; Haklay, Mordechai Muki

2009-05-01

Spatial planning typically involves multiple stakeholders. To any specific planning problem, stakeholders often bring different levels of knowledge about the components of the problem and make assumptions, reflecting their individual experiences, that yield conflicting views about desirable planning outcomes. Consequently, stakeholders need to learn about the likely outcomes that result from their stated preferences; this learning can be supported through enhanced access to information, increased public participation in spatial decision-making and support for distributed collaboration amongst planners, stakeholders and the public. This paper presents a conceptual system framework for web-based GIS that supports public participation in collaborative planning. The framework combines an information area, a Multi-Criteria Spatial Decision Support System (MC-SDSS) and an argumentation map to support distributed and asynchronous collaboration in spatial planning. After analysing the novel aspects of this framework, the paper describes its implementation, as a proof of concept, in a system for Web-based Participatory Wind Energy Planning (WePWEP). Details are provided on the specific implementation of each of WePWEP's four tiers, including technical and structural aspects. Throughout the paper, particular emphasis is placed on the need to support user learning throughout the planning process.

Fusion Analytics: A Data Integration System for Public Health and Medical Disaster Response Decision Support

PubMed Central

Passman, Dina B.

2013-01-01

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 to support leveraging this data for decision support with robust analytics and visualizations. Fusion Analytics provides an opportunity for attendees to see how various types of data are integrated into a single application for population health decision support. It also can provide them with ideas of how they can use their own staff to create analyses and reports that support their public health activities.

Visualization-based decision support for value-driven system design

NASA Astrophysics Data System (ADS)

Tibor, Elliott

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

Applications of Formal Methods to Specification and Safety of Avionics Software

NASA Technical Reports Server (NTRS)

Hoover, D. N.; Guaspari, David; Humenn, Polar

1996-01-01

This report treats several topics in applications of formal methods to avionics software development. Most of these topics concern decision tables, an orderly, easy-to-understand format for formally specifying complex choices among alternative courses of action. The topics relating to decision tables include: generalizations fo decision tables that are more concise and support the use of decision tables in a refinement-based formal software development process; a formalism for systems of decision tables with behaviors; an exposition of Parnas tables for users of decision tables; and test coverage criteria and decision tables. We outline features of a revised version of ORA's decision table tool, Tablewise, which will support many of the new ideas described in this report. We also survey formal safety analysis of specifications and software.

Interactive decision support in hepatic surgery

PubMed Central

Dugas, Martin; Schauer, Rolf; Volk, Andreas; Rau, Horst

2002-01-01

Background Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques. Methods To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient. Results The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996–2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases. Conclusion Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback. PMID:12003639

Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation.

PubMed

Linan, Margaret K; Sottara, Davide; Freimuth, Robert R

2015-01-01

Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines.

Developing a Software for Fuzzy Group Decision Support System: A Case Study

ERIC Educational Resources Information Center

Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem

2009-01-01

The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…

Decision support environment for medical product safety surveillance.

PubMed

Botsis, Taxiarchis; Jankosky, Christopher; Arya, Deepa; Kreimeyer, Kory; Foster, Matthew; Pandey, Abhishek; Wang, Wei; Zhang, Guangfan; Forshee, Richard; Goud, Ravi; Menschik, David; Walderhaug, Mark; Woo, Emily Jane; Scott, John

2016-12-01

We have developed a Decision Support Environment (DSE) for medical experts at the US Food and Drug Administration (FDA). The DSE contains two integrated systems: The Event-based Text-mining of Health Electronic Records (ETHER) and the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA). These systems assist medical experts in reviewing reports submitted to the Vaccine Adverse Event Reporting System (VAERS) and the FDA Adverse Event Reporting System (FAERS). In this manuscript, we describe the DSE architecture and key functionalities, and examine its potential contributions to the signal management process by focusing on four use cases: the identification of missing cases from a case series, the identification of duplicate case reports, retrieving cases for a case series analysis, and community detection for signal identification and characterization. Published by Elsevier Inc.

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

PubMed

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

2017-12-28

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

Computerised decision support in physical activity interventions: A systematic literature review.

PubMed

Triantafyllidis, Andreas; Filos, Dimitris; Claes, Jomme; Buys, Roselien; Cornelissen, Véronique; Kouidi, Evangelia; Chouvarda, Ioanna; Maglaveras, Nicos

2018-03-01

The benefits of regular physical activity for health and quality of life are unarguable. New information, sensing and communication technologies have the potential to play a critical role in computerised decision support and coaching for physical activity. We provide a literature review of recent research in the development of physical activity interventions employing computerised decision support, their feasibility and effectiveness in healthy and diseased individuals, and map out challenges and future research directions. We searched the bibliographic databases of PubMed and Scopus to identify physical activity interventions with computerised decision support utilised in a real-life context. Studies were synthesized according to the target user group, the technological format (e.g., web-based or mobile-based) and decision-support features of the intervention, the theoretical model for decision support in health behaviour change, the study design, the primary outcome, the number of participants and their engagement with the intervention, as well as the total follow-up duration. From the 24 studies included in the review, the highest percentage (n = 7, 29%) targeted sedentary healthy individuals followed by patients with prediabetes/diabetes (n = 4, 17%) or overweight individuals (n = 4, 17%). Most randomized controlled trials reported significantly positive effects of the interventions, i.e., increase in physical activity (n = 7, 100%) for 7 studies assessing physical activity measures, weight loss (n = 3, 75%) for 4 studies assessing diet, and reductions in glycosylated hemoglobin (n = 2, 66%) for 3 studies assessing glycose concentration. Accelerometers/pedometers were used in almost half of the studies (n = 11, 46%). Most adopted decision support features included personalised goal-setting (n = 16, 67%) and motivational feedback sent to the users (n = 15, 63%). Fewer adopted features were integration with electronic health records (n = 3, 13%) and alerts sent to caregivers (n = 4, 17%). Theoretical models of decision support in health behaviour to drive the development of the intervention were not reported in most studies (n = 14, 58%). Interventions employing computerised decision support have the potential to promote physical activity and result in health benefits for both diseased and healthy individuals, and help healthcare providers to monitor patients more closely. Objectively measured activity through sensing devices, integration with clinical systems used by healthcare providers and theoretical frameworks for health behaviour change need to be employed in a larger scale in future studies in order to realise the development of evidence-based computerised systems for physical activity monitoring and coaching. Copyright © 2017 Elsevier B.V. All rights reserved.

Knowledge representation and management enabling intelligent interoperability - principles and standards.

PubMed

Blobel, Bernd

2013-01-01

Based on the paradigm changes for health, health services and underlying technologies as well as the need for at best comprehensive and increasingly automated interoperability, the paper addresses the challenge of knowledge representation and management for medical decision support. After introducing related definitions, a system-theoretical, architecture-centric approach to decision support systems (DSSs) and appropriate ways for representing them using systems of ontologies is given. Finally, existing and emerging knowledge representation and management standards are presented. The paper focuses on the knowledge representation and management part of DSSs, excluding the reasoning part from consideration.

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

PubMed Central

Bau, Cho-Tsan; Huang, Chung-Yi

2014-01-01

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

Construction of a clinical decision support system for undergoing surgery based on domain ontology and rules reasoning.

PubMed

Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi

2014-05-01

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

Assessment for Operator Confidence in Automated Space Situational Awareness and Satellite Control Systems

NASA Astrophysics Data System (ADS)

Gorman, J.; Voshell, M.; Sliva, A.

2016-09-01

The United States is highly dependent on space resources to support military, government, commercial, and research activities. Satellites operate at great distances, observation capacity is limited, and operator actions and observations can be significantly delayed. Safe operations require support systems that provide situational understanding, enhance decision making, and facilitate collaboration between human operators and system automation both in-the-loop, and on-the-loop. Joint cognitive systems engineering (JCSE) provides a rich set of methods for analyzing and informing the design of complex systems that include both human decision-makers and autonomous elements as coordinating teammates. While, JCSE-based systems can enhance a system analysts' understanding of both existing and new system processes, JCSE activities typically occur outside of traditional systems engineering (SE) methods, providing sparse guidance about how systems should be implemented. In contrast, the Joint Director's Laboratory (JDL) information fusion model and extensions, such as the Dual Node Network (DNN) technical architecture, provide the means to divide and conquer such engineering and implementation complexity, but are loosely coupled to specialized organizational contexts and needs. We previously describe how Dual Node Decision Wheels (DNDW) extend the DNN to integrate JCSE analysis and design with the practicalities of system engineering and implementation using the DNN. Insights from Rasmussen's JCSE Decision Ladders align system implementation with organizational structures and processes. In the current work, we present a novel approach to assessing system performance based on patterns occurring in operational decisions that are documented by JCSE processes as traces in a decision ladder. In this way, system assessment is closely tied not just to system design, but the design of the joint cognitive system that includes human operators, decision-makers, information systems, and automated processes. Such operationally relevant and integrated testing provides a sound foundation for operator trust in system automation that is required to safely operate satellite systems.

Data-driven decision support for radiologists: re-using the National Lung Screening Trial dataset for pulmonary nodule management.

PubMed

Morrison, James J; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L

2015-02-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was converted into Structured Query Language (SQL) tables hosted on a web server, and a web-based JavaScript application was developed which performs real-time queries. JavaScript is used for both the server-side and client-side language, allowing for rapid development of a robust client interface and server-side data layer. Real-time data mining of user-specified patient cohorts achieved a rapid return of cohort cancer statistics and lung nodule distribution information. This system demonstrates the potential of individualized real-time data mining using large high-quality clinical trial datasets to drive evidence-based clinical decision-making.

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

PubMed

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

1995-06-01

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

Usability evaluation of the interactive Personal Patient Profile-Prostate decision support system with African American men.

PubMed

Jaja, Cheedy; Pares-Avila, Jose; Wolpin, Seth; Berry, Donna

2010-04-01

The Personal Patient Profile-Prostate (P4) program is an interactive Web-based decision support system that provides men with localized prostate cancer customized education and coaching with which to make the best personal treatment decision. This study assessed functionality and usability of the P4 program and identified problems in user-computer interaction in a sample of African American men. Usability testing was conducted with 12 community-dwelling African American adult men. The health status of participants was not known or collected by the research team. Each participant worked with the P4 program and provided simultaneous feedback using the "think aloud" technique. Handwritten field notes were collated and assigned to 3 standard coded categories. Aspects of P4 program usability was made based on common issues in the assigned categories. Summary statistics were derived for types and frequency of usability issues noted in the coded data. Twelve participants reported a total of 122 usability comments, with a mean of 9 usability comments. The most common usability issue by participant was completeness of information content, which comprised 53 (43%) of the total issues. Comprehensibility of text and graphics was second, comprising 51 (42%) of the total issues. This study provided initial inventory of usability issues for community African American men that may potentially interfere with application of the P4 system in the community setting and overall system usability, confirming the need for usability testing of a culturally appropriate Internet-based decision support system before community application.

Evolutionary and Neural Computing Based Decision Support System for Disease Diagnosis from Clinical Data Sets in Medical Practice.

PubMed

Sudha, M

2017-09-27

As a recent trend, various computational intelligence and machine learning approaches have been used for mining inferences hidden in the large clinical databases to assist the clinician in strategic decision making. In any target data the irrelevant information may be detrimental, causing confusion for the mining algorithm and degrades the prediction outcome. To address this issue, this study attempts to identify an intelligent approach to assist disease diagnostic procedure using an optimal set of attributes instead of all attributes present in the clinical data set. In this proposed Application Specific Intelligent Computing (ASIC) decision support system, a rough set based genetic algorithm is employed in pre-processing phase and a back propagation neural network is applied in training and testing phase. ASIC has two phases, the first phase handles outliers, noisy data, and missing values to obtain a qualitative target data to generate appropriate attribute reduct sets from the input data using rough computing based genetic algorithm centred on a relative fitness function measure. The succeeding phase of this system involves both training and testing of back propagation neural network classifier on the selected reducts. The model performance is evaluated with widely adopted existing classifiers. The proposed ASIC system for clinical decision support has been tested with breast cancer, fertility diagnosis and heart disease data set from the University of California at Irvine (UCI) machine learning repository. The proposed system outperformed the existing approaches attaining the accuracy rate of 95.33%, 97.61%, and 93.04% for breast cancer, fertility issue and heart disease diagnosis.

AppBuilder for DSSTools; an application development environment for developing decision support systems in Prolog

Treesearch

Geneho Kim; Donald Nute; H. Michael Rauscher; David L. Loftis

2000-01-01

A programming environment for developing complex decision support systems (DSSs) should support rapid prototyping and modular design, feature a flexible knowledge representation scheme and sound inference mechanisms, provide project management, and be domain independent. We have previously developed DSSTools (Decision Support System Tools), a reusable, domain-...

Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

ERIC Educational Resources Information Center

Erskine, Michael A.

2013-01-01

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…

Conformance Testing: Measurement Decision Rules

NASA Technical Reports Server (NTRS)

Mimbs, Scott M.

2010-01-01

The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to provide assurance to the customer that end products meet specifications. Measuring devices, often called measuring and test equipment (MTE), are used to provide the evidence of product conformity to specified requirements. Unfortunately, processes that employ MTE can become a weak link to the overall QMS if proper attention is not given to the measurement process design, capability, and implementation. Documented "decision rules" establish the requirements to ensure measurement processes provide the measurement data that supports the needs of the QMS. Measurement data are used to make the decisions that impact all areas of technology. Whether measurements support research, design, production, or maintenance, ensuring the data supports the decision is crucial. Measurement data quality can be critical to the resulting consequences of measurement-based decisions. Historically, most industries required simplistic, one-size-fits-all decision rules for measurements. One-size-fits-all rules in some cases are not rigorous enough to provide adequate measurement results, while in other cases are overly conservative and too costly to implement. Ideally, decision rules should be rigorous enough to match the criticality of the parameter being measured, while being flexible enough to be cost effective. The goal of a decision rule is to ensure that measurement processes provide data with a sufficient level of quality to support the decisions being made - no more, no less. This paper discusses the basic concepts of providing measurement-based evidence that end products meet specifications. Although relevant to all measurement-based conformance tests, the target audience is the MTE end-user, which is anyone using MTE other than calibration service providers. Topics include measurement fundamentals, the associated decision risks, verifying conformance to specifications, and basic measurement decisions rules.

Development the conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation

NASA Astrophysics Data System (ADS)

Milana; Khan, M. K.; Munive, J. E.

2014-07-01

The importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective.

Decision Support Systems for Research and Management in Advanced Life Support

NASA Technical Reports Server (NTRS)

Rodriquez, Luis F.

2004-01-01

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.

Interactive and Participatory Decision Support: Linking Cyberinfrastructure, Multi-Touch Interfaces, and Substantive Dialogue for Geothermal Systems

NASA Astrophysics Data System (ADS)

Malin, R.; Pierce, S. A.; Bass, B. J.

2012-12-01

Socio-technical approaches to complex, ill-structured decision problems are needed to identify adaptive responses for earth resource management. This research presents a hybrid approach to create decision tools and engender dialogue among stakeholders for geothermal development in Idaho, United States and El Tatio, Chile. Based on the scarcity of data, limited information availability, and tensions across stakeholder interests we designed and constructed a decision support model that allows stakeholders to rapidly collect, input, and visualize geoscientific data to assess geothermal system impacts and possible development strategies. We have integrated this decision support model into multi-touch interfaces that can be easily used by scientists and stakeholders alike. This toolkit is part of a larger cyberinfrastructure project designed to collect and present geoscientific information to support decision making processes. Consultation with stakeholders at the El Tatio geothermal complex of northern Chile—indigenous communities, local and national government agencies, developers, and geoscientists - informed the implementation of a sustained dialogue process. The El Tatio field case juxtaposes basic parameters such as pH, spring temperature, geochemical content, and FLIR imagery with stakeholder perceptions of risks due to mineral extraction and energy exploration efforts. The results of interviews and a participatory workshop are driving the creation of three initiatives within an indigenous community group; 1) microentrepreneurial efforts for science-based tourism, 2) design of a citizen-led environmental monitoring network in the Altiplano, and 3) business planning for an indigenous renewable energy cooperative. This toolkit is also being applied in the Snake River Plain of Idaho has as part of the DOE sponsored National Student Geothermal Competition. The Idaho case extends results from the Chilean case to implement a more streamlined system to analyze geothermal resource potential as well as integrate the decision support system with multi-touch interfaces which allow multiple stakeholders to view and interact with data. Beyond visual and tactile appeal, these interfaces also allow participants to dynamically update decision variables and decision preferences to create multiple scenarios and evaluate potential outcomes. Through this interactive scenario building, potential development sites can be targeted and stakeholders can interact with data to engage in substantive dialogue for related long-term planning or crisis response.

Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System.

PubMed

Zhang, Xueyan; Zhang, Jianwu; Li, Lin; Zhang, Yuzhu; Yang, Guocai

2017-02-23

Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer.

Use of decision support systems as a drought management tool

USGS Publications Warehouse

Frevert, D.; Lins, H.; ,

2005-01-01

Droughts present a unique challenge to water managers throughout the world and the current drought in the western United States is taxing facilities to the limit. Coping with this severe drought requires state of the art decision support systems including efficient and accurate hydrologic process models, detailed hydrologic data bases and effective river systems management modeling frameworks. This paper will outline a system of models developed by the Bureau of Reclamation, the US Geological Survey, the University of Colorado and a number of other governmental and university partners. The application of the technology to drought management in several key western river basins will be discussed.

Implementing an evidence-based computerized decision support system to improve patient care in a general hospital: the CODES study protocol for a randomized controlled trial.

PubMed

Moja, Lorenzo; Polo Friz, Hernan; Capobussi, Matteo; Kwag, Koren; Banzi, Rita; Ruggiero, Francesca; González-Lorenzo, Marien; Liberati, Elisa Giulia; Mangia, Massimo; Nyberg, Peter; Kunnamo, Ilkka; Cimminiello, Claudio; Vighi, Giuseppe; Grimshaw, Jeremy; Bonovas, Stefanos

2016-07-07

Computerized decision support systems (CDSSs) are information technology-based software that provide health professionals with actionable, patient-specific recommendations or guidelines for disease diagnosis, treatment, and management at the point-of-care. These messages are intelligently filtered to enhance the health and clinical care of patients. CDSSs may be integrated with patient electronic health records (EHRs) and evidence-based knowledge. We designed a pragmatic randomized controlled trial to evaluate the effectiveness of patient-specific, evidence-based reminders generated at the point-of-care by a multi-specialty decision support system on clinical practice and the quality of care. We will include all the patients admitted to the internal medicine department of one large general hospital. The primary outcome is the rate at which medical problems, which are detected by the decision support software and reported through the reminders, are resolved (i.e., resolution rates). Secondary outcomes are resolution rates for reminders specific to venous thromboembolism (VTE) prevention, in-hospital all causes and VTE-related mortality, and the length of hospital stay during the study period. The adoption of CDSSs is likely to increase across healthcare systems due to growing concerns about the quality of medical care and discrepancy between real and ideal practice, continuous demands for a meaningful use of health information technology, and the increasing use of and familiarity with advanced technology among new generations of physicians. The results of our study will contribute to the current understanding of the effectiveness of CDSSs in primary care and hospital settings, thereby informing future research and healthcare policy questions related to the feasibility and value of CDSS use in healthcare systems. This trial is seconded by a specialty trial randomizing patients in an oncology setting (ONCO-CODES). ClinicalTrials.gov, https://clinicaltrials.gov/ct2/show/NCT02577198?term=NCT02577198&rank=1.

Decision support for clinical laboratory capacity planning.

PubMed

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

1995-01-01

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

Development and implementation of an Integrated Water Resources Management System (IWRMS)

NASA Astrophysics Data System (ADS)

Flügel, W.-A.; Busch, C.

2011-04-01

One of the innovative objectives in the EC project BRAHMATWINN was the development of a stakeholder oriented Integrated Water Resources Management System (IWRMS). The toolset integrates the findings of the project and presents it in a user friendly way for decision support in sustainable integrated water resources management (IWRM) in river basins. IWRMS is a framework, which integrates different types of basin information and which supports the development of IWRM options for climate change mitigation. It is based on the River Basin Information System (RBIS) data models and delivers a graphical user interface for stakeholders. A special interface was developed for the integration of the enhanced DANUBIA model input and the NetSyMod model with its Mulino decision support system (mulino mDss) component. The web based IWRMS contains and combines different types of data and methods to provide river basin data and information for decision support. IWRMS is based on a three tier software framework which uses (i) html/javascript at the client tier, (ii) PHP programming language to realize the application tier, and (iii) a postgresql/postgis database tier to manage and storage all data, except the DANUBIA modelling raw data, which are file based and registered in the database tier. All three tiers can reside on one or different computers and are adapted to the local hardware infrastructure. IWRMS as well as RBIS are based on Open Source Software (OSS) components and flexible and time saving access to that database is guaranteed by web-based interfaces for data visualization and retrieval. The IWRMS is accessible via the BRAHMATWINN homepage: http://www.brahmatwinn.uni-jena.de and a user manual for the RBIS is available for download as well.

Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies.

PubMed

Samwald, Matthias; Miñarro Giménez, Jose Antonio; Boyce, Richard D; Freimuth, Robert R; Adlassnig, Klaus-Peter; Dumontier, Michel

2015-02-22

Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles. Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners. The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.

Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

NASA Astrophysics Data System (ADS)

Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

2005-02-01

An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

The Design and Use of Decision Support Systems by Academic Departments. AIR 1987 Annual Forum Paper.

ERIC Educational Resources Information Center

Johnson, F. Craig

The design and use of a departmental decision support system at Florida State University are described from the perspective of a department head. The decisions selected for study are ones of adequacy, equitability, quality, efficiency, and consistency. The complexity of the decision is related to the complexity of the support system. The major…

How updating textual clinical practice guidelines impacts clinical decision support systems: a case study with bladder cancer management.

PubMed

Bouaud, Jacques; Séroussi, Brigitte; Brizon, Ambre; Culty, Thibault; Mentré, France; Ravery, Vincent

2007-01-01

Guideline-based clinical decision support systems (CDSSs) can be effective in increasing physician compliance with recommendations. However, the ever growing pace at which medical knowledge is produced requires that clinical practice guidelines (CPGs) be updated regularly. It is therefore mandatory that CDSSs be revised accordingly. The French Association for Urology publishes CPGs on bladder cancer management every 2 years. We studied the impact of the 2004 revision of these guidelines, with respect to the 2002 version with a CDSS, UroDoc. We proposed a typology of knowledge base modifications resulting from the update of CPGs making the difference between practice, clinical conditions and recommendations refinement as opposed to new practice and new recommendations. The number of formalized recommendations increased from 577 in 2002 to 1,081 in 2004. We evaluated the two versions of UroDoc on a randomized sample of patient records. A single new practice that modifies a decision taken in 49% of all recorded decisions leads to a fall from 67% to 46% of the compliance rate of decisions.

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

Treesearch

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

2011-01-01

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

Data collection and information presentation for optimal decision making by clinical managers--the Autocontrol Project.

PubMed Central

Grant, A. M.; Richard, Y.; Deland, E.; Després, N.; de Lorenzi, F.; Dagenais, A.; Buteau, M.

1997-01-01

The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies. PMID:9357733

Data collection and information presentation for optimal decision making by clinical managers--the Autocontrol Project.

PubMed

Grant, A M; Richard, Y; Deland, E; Després, N; de Lorenzi, F; Dagenais, A; Buteau, M

1997-01-01

The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies.

Understanding clinical work practices for cross-boundary decision support in e-health.

PubMed

Tawfik, Hissam; Anya, Obinna; Nagar, Atulya K

2012-07-01

One of the major concerns of research in integrated healthcare information systems is to enable decision support among clinicians across boundaries of organizations and regional workgroups. A necessary precursor, however, is to facilitate the construction of appropriate awareness of local clinical practices, including a clinician's actual cognitive capabilities, peculiar workplace circumstances, and specific patient-centered needs based on real-world clinical contexts across work settings. In this paper, a user-centered study aimed to investigate clinical practices across three different geographical areas-the U.K., the UAE and Nigeria-is presented. The findings indicate that differences in clinical practices among clinicians are associated with differences in local work contexts across work settings, but are moderated by adherence to best practice guidelines and the need for patient-centered care. The study further reveals that an awareness especially of the ontological, stereotypical, and situated practices plays a crucial role in adapting knowledge for cross-boundary decision support. The paper then outlines a set of design guidelines for the development of enterprise information systems for e-health. Based on the guidelines, the paper proposes the conceptual design of CaDHealth, a practice-centered framework for making sense of clinical practices across work settings for effective cross-boundary e-health decision support.

A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

PubMed

Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

2015-01-01

Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.

Application of a web-based Decision Support System in risk management

NASA Astrophysics Data System (ADS)

Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2013-04-01

Increasingly, risk information is widely available with the help of advanced technologies such as earth observation satellites, global positioning technologies, coupled with hazard modeling and analysis, and geographical information systems (GIS). Even though it exists, no effort will be put into action if it is not properly presented to the decision makers. These information need to be communicated clearly and show its usefulness so that people can make better informed decision. Therefore, communicating available risk information has become an important challenge and decision support systems have been one of the significant approaches which can help not only in presenting risk information to the decision makers but also in making efficient decisions while reducing human resources and time needed. In this study, the conceptual framework of an internet-based decision support system is presented to highlight its importance role in risk management framework and how it can be applied in case study areas chosen. The main purpose of the proposed system is to facilitate the available risk information in risk reduction by taking into account of the changes in climate, land use and socio-economic along with the risk scenarios. It allows the users to formulate, compare and select risk reduction scenarios (mainly for floods and landslides) through an enhanced participatory platform with diverse stakeholders' involvement in the decision making process. It is based on the three-tier (client-server) architecture which integrates web-GIS plus DSS functionalities together with cost benefit analysis and other supporting tools. Embedding web-GIS provides its end users to make better planning and informed decisions referenced to a geographical location, which is the one of the essential factors in disaster risk reduction programs. Different risk reduction measures of a specific area (local scale) will be evaluated using this web-GIS tool, available risk scenarios obtained from Probabilistic Risk Assessment (PRA) model and the knowledge collected from experts. The visualization of the risk reduction scenarios can also be shared among the users on the web to support the on-line participatory process. In addition, cost-benefit ratios of the different risk reduction scenarios can be prepared in order to serve as inputs for high-level decision makers. The most appropriate risk reduction scenarios will be chosen using Multi-Criteria Evaluation (MCE) method by weighting different parameters according to the preferences and criteria defined by the users. The role of public participation has been changing from one-way communication between authorities, experts, stakeholders and citizens towards more intensive two-way interaction. Involving the affected public and interest groups can enhance the level of legitimacy, transparency, and confidence in the decision making process. Due to its important part in decision making, online participatory tool is included in the DSS in order to allow the involved stakeholders interactively in risk reduction and be aware of the existing vulnerability conditions of the community. Moreover, it aims to achieve a more transparent and better informed decision-making process. The system is under in progress and the first tools implemented will be presented showing the wide possibilities of new web technologies which can have a great impact on the decision making process. It will be applied in four pilot areas in Europe: French Alps, North Eastern Italy, Romania and Poland. Nevertheless, the framework will be designed and implemented in a way to be applicable in any other regions.

Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

PubMed

Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

2005-06-01

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.

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

NASA Astrophysics Data System (ADS)

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

2014-02-01

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

Direct and Electronic Health Record Access to the Clinical Decision Support for Immunizations in the Minnesota Immunization Information System.

PubMed

Rajamani, Sripriya; Bieringer, Aaron; Wallerius, Stephanie; Jensen, Daniel; Winden, Tamara; Muscoplat, Miriam Halstead

2016-01-01

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.

A Decision Making Methodology in Support of the Business Rules Lifecycle

NASA Technical Reports Server (NTRS)

Wild, Christopher; Rosca, Daniela

1998-01-01

The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.

A decision-supported outpatient practice system.

PubMed Central

Barrows, R. C.; Allen, B. A.; Smith, K. C.; Arni, V. V.; Sherman, E.

1996-01-01

We describe a Decision-supported Outpatient Practice (DOP) system developed and now in use at the Columbia-Presbyterian Medical Center. DOP is an automated ambulatory medical record system that integrates in-patient and ambulatory care data, and incorporates active and passive decision support mechanisms with a view towards improving the quality of primary care. Active decision support occurs in the form of event-driven reminders created within a remote clinical information system with its central data repository and decision support system (DSS). Novel features of DOP include patient specific health maintenance task lists calculated by the remote DSS. uses of a semantically structured controlled medical vocabulary to support clinical results review and provider data entry, and exploitation of an underlying ambulatory data model that provides for an explicit record of evolution of insight regarding patient management. Benefits, challenges, and plans are discussed. PMID:8947774

Representing Human Expertise by the OWL Web Ontology Language to Support Knowledge Engineering in Decision Support Systems.

PubMed

Ramzan, Asia; Wang, Hai; Buckingham, Christopher

2014-01-01

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Clinical decision support for whole genome sequence information leveraging a service-oriented architecture: a prototype.

PubMed

Welch, Brandon M; Rodriguez-Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

2014-01-01

Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time.

Prevention of and Early Intervention for Students with Emotional and Behavioral Disorders: Systems to Support Data-Based Decision Making

ERIC Educational Resources Information Center

Lewis, Timothy J.; Mitchell, Barbara S.

2012-01-01

Students with emotional and behavioral disorders are at great risk for long-term negative outcomes. Researchers and practitioners alike acknowledge the need for evidence-based, preventive, and early intervention strategies. Accordingly, in this chapter an expanded view of prevention is presented as a series of data driven decisions to guide…

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

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

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sitesmore » are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.« less

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

Wu, Qishi; Zhu, Mengxia; Rao, Nageswara S

We propose an intelligent decision support system based on sensor and computer networks that incorporates various component techniques for sensor deployment, data routing, distributed computing, and information fusion. The integrated system is deployed in a distributed environment composed of both wireless sensor networks for data collection and wired computer networks for data processing in support of homeland security defense. We present the system framework and formulate the analytical problems and develop approximate or exact solutions for the subtasks: (i) sensor deployment strategy based on a two-dimensional genetic algorithm to achieve maximum coverage with cost constraints; (ii) data routing scheme tomore » achieve maximum signal strength with minimum path loss, high energy efficiency, and effective fault tolerance; (iii) network mapping method to assign computing modules to network nodes for high-performance distributed data processing; and (iv) binary decision fusion rule that derive threshold bounds to improve system hit rate and false alarm rate. These component solutions are implemented and evaluated through either experiments or simulations in various application scenarios. The extensive results demonstrate that these component solutions imbue the integrated system with the desirable and useful quality of intelligence in decision making.« less

[Development and clinical evaluation of an anesthesia information management system].

PubMed

Feng, Jing-yi; Chen, Hua; Zhu, Sheng-mei

2010-09-21

To study the design, implementation and clinical evaluation of an anesthesia information management system. To record, process and store peri-operative patient data automatically, all kinds of bedside monitoring equipments are connected into the system based on information integrating technology; after a statistical analysis of those patient data by data mining technology, patient status can be evaluated automatically based on risk prediction standard and decision support system, and then anesthetist could perform reasonable and safe clinical processes; with clinical processes electronically recorded, standard record tables could be generated, and clinical workflow is optimized, as well. With the system, kinds of patient data could be collected, stored, analyzed and archived, kinds of anesthesia documents could be generated, and patient status could be evaluated to support clinic decision. The anesthesia information management system is useful for improving anesthesia quality, decreasing risk of patient and clinician, and aiding to provide clinical proof.

AQUATOOL, a generalized decision-support system for water-resources planning and operational management

NASA Astrophysics Data System (ADS)

Andreu, J.; Capilla, J.; Sanchís, E.

1996-04-01

This paper describes a generic decision-support system (DSS) which was originally designed for the planning stage of dicision-making associated with complex river basins. Subsequently, it was expanded to incorporate modules relating to the operational stage of decision-making. Computer-assisted design modules allow any complex water-resource system to be represented in graphical form, giving access to geographically referenced databases and knowledge bases. The modelling capability includes basin simulation and optimization modules, an aquifer flow modelling module and two modules for risk assessment. The Segura and Tagus river basins have been used as case studies in the development and validation phases. The value of this DSS is demonstrated by the fact that both River Basin Agencies currently use a version for the efficient management of their water resources.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

PubMed

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

Methods and decision making on a Mars rover for identification of fossils

NASA Technical Reports Server (NTRS)

Eberlein, Susan; Yates, Gigi

1989-01-01

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Integrating post-manufacturing issues into design and manufacturing decisions

NASA Technical Reports Server (NTRS)

Eubanks, Charles F.

1996-01-01

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

Moving toward climate-informed agricultural decision support - can we use PRISM data for more than just monthly averages?

USDA-ARS?s Scientific Manuscript database

Decision support systems/models for agriculture are varied in target application and complexity, ranging from simple worksheets to near real-time forecast systems requiring significant computational and manpower resources. Until recently, most such decision support systems have been constructed with...

Designing a Decision Support System (DSS) for Academic Library Managers Using Preprogrammed Application Software on a Microcomputer.

ERIC Educational Resources Information Center

McDonald, Joseph

1986-01-01

Focusing on management decisions in academic libraries, this article compares management information systems (MIS) with decision support systems (DSS) and discusses the decision-making process, information needs of library managers, sources of data, reasons for choosing microcomputer, preprogrammed application software, prototyping a system, and…

Decision Support System for Coastal Protection Layout Design (DSS4CPD) Using Genetic Algorithm (ga) and Multicriteria Analysis (mca)

NASA Astrophysics Data System (ADS)

Jinchai, Phinai; Chittaladakorn, Suwatana

This research has its objective to develop the decision support system on GIS to be used in the coastal erosion protection management. The developed model in this research is called Decision Support System for Coastal Protection Layout Design (DSS4CPD). It has created both for systematic protection and solution measures to the problem by using Genetic Algorithm (GA) and Multicriteria Analysis (MCA) for finding the coastal structure layout optimal solution. In this research, three types of coastal structures were used as structure alternatives for the layout, which are seawall, breakwater, and groin. The coastal area in Nakornsrithammaraj, Thailand was used as the case study. The studied result has found the appropriate position of coastal structures considering the suitable rock size relied on the wave energy, and the appropriate coastal structure position based on the wave breaking line. Using GA and MCA in DSS4CPD, it found the best layout in this project. This DSS4CPD will be used by the authorized decision makers to find the most suitable erosion problem solution.

A Web-Based Earth-Systems Knowledge Portal and Collaboration Platform

NASA Astrophysics Data System (ADS)

D'Agnese, F. A.; Turner, A. K.

2010-12-01

In support of complex water-resource sustainability projects in the Great Basin region of the United States, Earth Knowledge, Inc. has developed several web-based data management and analysis platforms that have been used by its scientists, clients, and public to facilitate information exchanges, collaborations, and decision making. These platforms support accurate water-resource decision-making by combining second-generation internet (Web 2.0) technologies with traditional 2D GIS and web-based 2D and 3D mapping systems such as Google Maps, and Google Earth. Most data management and analysis systems use traditional software systems to address the data needs and usage behavior of the scientific community. In contrast, these platforms employ more accessible open-source and “off-the-shelf” consumer-oriented, hosted web-services. They exploit familiar software tools using industry standard protocols, formats, and APIs to discover, process, fuse, and visualize earth, engineering, and social science datasets. Thus, they respond to the information needs and web-interface expectations of both subject-matter experts and the public. Because the platforms continue to gather and store all the contributions of their broad-spectrum of users, each new assessment leverages the data, information, and expertise derived from previous investigations. In the last year, Earth Knowledge completed a conceptual system design and feasibility study for a platform, which has a Knowledge Portal providing access to users wishing to retrieve information or knowledge developed by the science enterprise and a Collaboration Environment Module, a framework that links the user-access functions to a Technical Core supporting technical and scientific analyses including Data Management, Analysis and Modeling, and Decision Management, and to essential system administrative functions within an Administrative Module. The over-riding technical challenge is the design and development of a single technical platform that is accessed through a flexible series of knowledge portal and collaboration environment styles reflecting the information needs and user expectations of a diverse community of users. Recent investigations have defined the information needs and expectations of the major end-users and also have reviewed and assessed a wide variety of modern web-based technologies. Combining these efforts produced design specifications and recommendations for the selection and integration of web- and client-based tools. When fully developed, the resulting platform will: -Support new, advanced information systems and decision environments that take full advantage of multiple data sources and platforms; -Provide a distribution network tailored to the timely delivery of products to a broad range of users that are needed to support applications in disaster management, resource management, energy, and urban sustainability; -Establish new integrated multiple-user requirements and knowledge databases that support researchers and promote infusion of successful technologies into existing processes; and -Develop new decision support strategies and presentation methodologies for applied earth science applications to reduce risk, cost, and time.

A Decision Support System for effective use of probability forecasts

NASA Astrophysics Data System (ADS)

De Kleermaeker, Simone; Verkade, Jan

2013-04-01

Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.

Multiple memory systems as substrates for multiple decision systems

PubMed Central

Doll, Bradley B.; Shohamy, Daphna; Daw, Nathaniel D.

2014-01-01

It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and relational memory by comparing individual differences across behavioral tasks designed to measure either capacity. Human subjects performed two tasks, a learning and generalization task (acquired equivalence) which involves relational encoding and depends on the hippocampus; and a sequential RL task that could be solved by either a model-based or model-free strategy. We assessed the correlation between subjects’ use of flexible, relational memory, as measured by generalization in the acquired equivalence task, and their differential reliance on either RL strategy in the decision task. We observed a significant positive relationship between generalization and model-based, but not model-free, choice strategies. These results are consistent with the hypothesis that model-based RL, like acquired equivalence, relies on a more general-purpose relational memory system. PMID:24846190

Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

ERIC Educational Resources Information Center

Campbell, Merle Wayne

2013-01-01

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.…

A PC-Based Free Text DSS for Health Care

NASA Technical Reports Server (NTRS)

Grams, Ralph R.; Buchanan, Paul; Massey, James K.; Jin, Ming

1987-01-01

A free Decision Support System(DST) has been constructed for health care professional that allows the analysis of complex medical cases and the creation of diagnostic list of potential diseases for clinical evaluation.The system uses a PC-based text management system specifically designed for desktop operation. The texts employed in the decision support package include the Merck Manual (published by Merck Sharpe & Dohme) and Control of Communicable Diseas in Man (published by the American Public Health Association). The background and design of the database are discussed along with a structured analysis procedure for handling free text DSS system. A case study is presented to show the application of this technology and conclusions are drawn in the summary that point to expanded areas of professional intention and new frontiers yet to be explored in this rapidly progressing field.

Rapid decision support tool based on novel ecosystem service variables for retrofitting of permeable pavement systems in the presence of trees.

PubMed

Scholz, Miklas; Uzomah, Vincent C

2013-08-01

The retrofitting of sustainable drainage systems (SuDS) such as permeable pavements is currently undertaken ad hoc using expert experience supported by minimal guidance based predominantly on hard engineering variables. There is a lack of practical decision support tools useful for a rapid assessment of the potential of ecosystem services when retrofitting permeable pavements in urban areas that either feature existing trees or should be planted with trees in the near future. Thus the aim of this paper is to develop an innovative rapid decision support tool based on novel ecosystem service variables for retrofitting of permeable pavement systems close to trees. This unique tool proposes the retrofitting of permeable pavements that obtained the highest ecosystem service score for a specific urban site enhanced by the presence of trees. This approach is based on a novel ecosystem service philosophy adapted to permeable pavements rather than on traditional engineering judgement associated with variables based on quick community and environment assessments. For an example case study area such as Greater Manchester, which was dominated by Sycamore and Common Lime, a comparison with the traditional approach of determining community and environment variables indicates that permeable pavements are generally a preferred SuDS option. Permeable pavements combined with urban trees received relatively high scores, because of their great potential impact in terms of water and air quality improvement, and flood control, respectively. The outcomes of this paper are likely to lead to more combined permeable pavement and tree systems in the urban landscape, which are beneficial for humans and the environment. Copyright © 2013 Elsevier B.V. All rights reserved.

Chronic Motivational State Interacts with Task Reward Structure in Dynamic Decision-Making

PubMed Central

Cooper, Jessica A.; Worthy, Darrell A.; Maddox, W. Todd

2015-01-01

Research distinguishes between a habitual, model-free system motivated toward immediately rewarding actions, and a goal-directed, model-based system motivated toward actions that improve future state. We examined the balance of processing in these two systems during state-based decision-making. We tested a regulatory fit hypothesis (Maddox & Markman, 2010) that predicts that global trait motivation affects the balance of habitual- vs. goal-directed processing but only through its interaction with the task framing as gain-maximization or loss-minimization. We found support for the hypothesis that a match between an individual’s chronic motivational state and the task framing enhances goal-directed processing, and thus state-based decision-making. Specifically, chronic promotion-focused individuals under gain-maximization and chronic prevention-focused individuals under loss-minimization both showed enhanced state-based decision-making. Computational modeling indicates that individuals in a match between global chronic motivational state and local task reward structure engaged more goal-directed processing, whereas those in a mismatch engaged more habitual processing. PMID:26520256

Quick Fix for Managing Risks

NASA Technical Reports Server (NTRS)

2002-01-01

Under a Phase II SBIR contract, Kennedy and Lumina Decision Systems, Inc., jointly developed the Schedule and Cost Risk Analysis Modeling (SCRAM) system, based on a version of Lumina's flagship software product, Analytica(R). Acclaimed as "the best single decision-analysis program yet produced" by MacWorld magazine, Analytica is a "visual" tool used in decision-making environments worldwide to build, revise, and present business models, minus the time-consuming difficulty commonly associated with spreadsheets. With Analytica as their platform, Kennedy and Lumina created the SCRAM system in response to NASA's need to identify the importance of major delays in Shuttle ground processing, a critical function in project management and process improvement. As part of the SCRAM development project, Lumina designed a version of Analytica called the Analytica Design Engine (ADE) that can be easily incorporated into larger software systems. ADE was commercialized and utilized in many other developments, including web-based decision support.

Examining MTSS Implementation across Systems for SLD Identification: A Case Study

ERIC Educational Resources Information Center

Barrett, Courtenay A.; Newman, Daniel S.

2018-01-01

Although research supports the effectiveness of the multitiered system of supports (MTSS) on academic and behavioral outcomes, districts aim to engage in data-based decision making and examine the effectiveness of their own MTSS implementation. This case study describes how one regional education service agency (RESA) in the Midwest implemented…

Practical Considerations in Creating School-Wide Positive Behavior Support in Public Schools

ERIC Educational Resources Information Center

Handler, Marcie W.; Rey, Jannette; Connell, James; Thier, Kimberly; Feinberg, Adam; Putnam, Robert

2007-01-01

School-wide positive behavior support (SWPBS) has been identified as an effective and efficient method to teach students prosocial skills. It requires both effective behavior support practices and systems that will support these changes, including data-based decision making among the school leadership team. There are many practical and systemic…

Design and implementation of wireless dose logger network for radiological emergency decision support system.

PubMed

Gopalakrishnan, V; Baskaran, R; Venkatraman, B

2016-08-01

A decision support system (DSS) is implemented in Radiological Safety Division, Indira Gandhi Centre for Atomic Research for providing guidance for emergency decision making in case of an inadvertent nuclear accident. Real time gamma dose rate measurement around the stack is used for estimating the radioactive release rate (source term) by using inverse calculation. Wireless gamma dose logging network is designed, implemented, and installed around the Madras Atomic Power Station reactor stack to continuously acquire the environmental gamma dose rate and the details are presented in the paper. The network uses XBee-Pro wireless modules and PSoC controller for wireless interfacing, and the data are logged at the base station. A LabView based program is developed to receive the data, display it on the Google Map, plot the data over the time scale, and register the data in a file to share with DSS software. The DSS at the base station evaluates the real time source term to assess radiation impact.

Design and implementation of wireless dose logger network for radiological emergency decision support system

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

Gopalakrishnan, V.; Baskaran, R.; Venkatraman, B.

A decision support system (DSS) is implemented in Radiological Safety Division, Indira Gandhi Centre for Atomic Research for providing guidance for emergency decision making in case of an inadvertent nuclear accident. Real time gamma dose rate measurement around the stack is used for estimating the radioactive release rate (source term) by using inverse calculation. Wireless gamma dose logging network is designed, implemented, and installed around the Madras Atomic Power Station reactor stack to continuously acquire the environmental gamma dose rate and the details are presented in the paper. The network uses XBee–Pro wireless modules and PSoC controller for wireless interfacing,more » and the data are logged at the base station. A LabView based program is developed to receive the data, display it on the Google Map, plot the data over the time scale, and register the data in a file to share with DSS software. The DSS at the base station evaluates the real time source term to assess radiation impact.« less

Soft System Analysis to Integrate Technology & Human in Controller Workstation

DOT National Transportation Integrated Search

2011-10-16

Computer-based decision support tools (DST), : shared information, and other forms of automation : are increasingly being planned for use by controllers : and pilots to support Air Traffic Management (ATM) : and Air Traffic Control (ATC) in the Next ...

Advanced Satellite Workstation - An integrated workstation environment for operational support of satellite system planning and analysis

NASA Astrophysics Data System (ADS)

Hamilton, Marvin J.; Sutton, Stewart A.

A prototype integrated environment, the Advanced Satellite Workstation (ASW), which was developed and delivered for evaluation and operator feedback in an operational satellite control center, is described. The current ASW hardware consists of a Sun Workstation and Macintosh II Workstation connected via an ethernet Network Hardware and Software, Laser Disk System, Optical Storage System, and Telemetry Data File Interface. The central objective of ASW is to provide an intelligent decision support and training environment for operator/analysis of complex systems such as satellites. Compared to the many recent workstation implementations that incorporate graphical telemetry displays and expert systems, ASW provides a considerably broader look at intelligent, integrated environments for decision support, based on the premise that the central features of such an environment are intelligent data access and integrated toolsets.

Identifying Opportunities for Decision Support Systems in Support of Regional Resource Use Planning: An Approach Through Soft Systems Methodology.

PubMed

Zhu; Dale

2000-10-01

/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.

Effectiveness of electronic guideline-based implementation systems in ambulatory care settings - a systematic review

PubMed Central

2009-01-01

Background Electronic guideline-based decision support systems have been suggested to successfully deliver the knowledge embedded in clinical practice guidelines. A number of studies have already shown positive findings for decision support systems such as drug-dosing systems and computer-generated reminder systems for preventive care services. Methods A systematic literature search (1990 to December 2008) of the English literature indexed in the Medline database, Embase, the Cochrane Central Register of Controlled Trials, and CRD (DARE, HTA and NHS EED databases) was conducted to identify evaluation studies of electronic multi-step guideline implementation systems in ambulatory care settings. Important inclusion criterions were the multidimensionality of the guideline (the guideline needed to consist of several aspects or steps) and real-time interaction with the system during consultation. Clinical decision support systems such as one-time reminders for preventive care for which positive findings were shown in earlier reviews were excluded. Two comparisons were considered: electronic multidimensional guidelines versus usual care (comparison one) and electronic multidimensional guidelines versus other guideline implementation methods (comparison two). Results Twenty-seven publications were selected for analysis in this systematic review. Most designs were cluster randomized controlled trials investigating process outcomes more than patient outcomes. With success defined as at least 50% of the outcome variables being significant, none of the studies were successful in improving patient outcomes. Only seven of seventeen studies that investigated process outcomes showed improvements in process of care variables compared with the usual care group (comparison one). No incremental effect of the electronic implementation over the distribution of paper versions of the guideline was found, neither for the patient outcomes nor for the process outcomes (comparison two). Conclusions There is little evidence at the moment for the effectiveness of an increasingly used and commercialised instrument such as electronic multidimensional guidelines. After more than a decade of development of numerous electronic systems, research on the most effective implementation strategy for this kind of guideline-based decision support systems is still lacking. This conclusion implies a considerable risk towards inappropriate investments in ineffective implementation interventions and in suboptimal care. PMID:20042070

The process of development of a prioritization tool for a clinical decision support build within a computerized provider order entry system: Experiences from St Luke's Health System.

PubMed

Wolf, Matthew; Miller, Suzanne; DeJong, Doug; House, John A; Dirks, Carl; Beasley, Brent

2016-09-01

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.

Implementation of Computer Based Management Information Systems: A Behavioral Perspective.

ERIC Educational Resources Information Center

Lilly, Edward R.

In the past decade significant advances have taken place in the development of management information systems (MIS) to support managerial decision making. Recent literature has shown, however, that educators have yet to make full and efficient use of these computer-based systems. A number of authors have discussed factors that may affect…

Reliable binary cell-fate decisions based on oscillations

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2014-02-01

Biological systems have often to perform binary decisions under highly dynamic and noisy environments, such as during cell-fate determination. These decisions can be implemented by two main bifurcation mechanisms based on the transitions from either monostability or oscillation to bistability. We compare these two mechanisms by using stochastic models with time-varying fields and by establishing asymptotic formulas for the choice probabilities. Different scaling laws for decision sensitivity with respect to noise strength and signal timescale are obtained, supporting a role for oscillatory dynamics in performing noise-robust and temporally tunable binary decision-making. This result provides a rationale for recent experimental evidences showing that oscillatory expression of proteins often precedes binary cell-fate decisions.

A decision support system for drinking water production integrating health risks assessment.

PubMed

Delpla, Ianis; Monteith, Donald T; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier

2014-07-18

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.

Interactive Resource Planning—An Anticipative Concept in the Simulation-Based Decision Support System EXPOSIM

NASA Astrophysics Data System (ADS)

Leopold-Wildburger, Ulrike; Pickl, Stefan

2008-10-01

In our research we intend to use experiments to study human behavior in a simulation environment based on a simple Lotka-Volterra predator-prey ecology. The aim is to study the influence of participants' harvesting strategies and certain personality traits derived from [1] on the outcome in terms of sustainability and economic performance. Such an approach is embedded in a research program which intends to develop and understand interactive resource planning processes. We present the general framework as well as the new decision support system EXPOSIM. The key element is the combination of experimental design, analytical understanding of time-discrete systems (especially Lotka-Volterra systems) and economic performance. In the first part, the general role of laboratory experiments is discussed. The second part summarizes the concept of sustainable development. It is taken from [18]. As we use Lotka-Volterra systems as the basis for our simulations a theoretical framework is described afterwards. It is possible to determine optimal behavior for those systems. The empirical setting is based on the empirical approach that the subjects are put into the position of a decision-maker. They are able to model the environment in such a way that harvesting can be observed. We suggest an experimental setting which might lead to new insights in an anticipatory sense.

Leveraging the geospatial advantage

Treesearch

Ben Butler; Andrew Bailey

2013-01-01

The Wildland Fire Decision Support System (WFDSS) web-based application leverages geospatial data to inform strategic decisions on wildland fires. A specialized data team, working within the Wildland Fire Management Research Development and Application group (WFM RD&A), assembles authoritative national-level data sets defining values to be protected. The use of...

Decision support systems for robotic surgery and acute care

NASA Astrophysics Data System (ADS)

Kazanzides, Peter

2012-06-01

Doctors must frequently make decisions during medical treatment, whether in an acute care facility, such as an Intensive Care Unit (ICU), or in an operating room. These decisions rely on a various information sources, such as the patient's medical history, preoperative images, and general medical knowledge. Decision support systems can assist by facilitating access to this information when and where it is needed. This paper presents some research eorts that address the integration of information with clinical practice. The example systems include a clinical decision support system (CDSS) for pediatric traumatic brain injury, an augmented reality head- mounted display for neurosurgery, and an augmented reality telerobotic system for minimally-invasive surgery. While these are dierent systems and applications, they share the common theme of providing information to support clinical decisions and actions, whether the actions are performed with the surgeon's own hands or with robotic assistance.

A DICOM-RT radiation oncology ePR with decision support utilizing a quantified knowledge base from historical data

NASA Astrophysics Data System (ADS)

Documet, Jorge R.; Liu, Brent; Le, Anh; Law, Maria

2008-03-01

During the last 2 years we have been working on developing a DICOM-RT (Radiation Therapy) ePR (Electronic Patient Record) with decision support that will allow physicists and radiation oncologists during their decision-making process. This ePR allows offline treatment dose calculations and plan evaluation, while at the same time it compares and quantifies treatment planning algorithms using DICOM-RT objects. The ePR framework permits the addition of visualization, processing, and analysis tools, which combined with the core functionality of reporting, importing and exporting of medical studies, creates a very powerful application that can improve the efficiency while planning cancer treatments. Usually a Radiation Oncology department will have disparate and complex data generated by the RT modalities as well as data scattered in RT Information/Management systems, Record & Verify systems, and Treatment Planning Systems (TPS) which can compromise the efficiency of the clinical workflow since the data crucial for a clinical decision may be time-consuming to retrieve, temporarily missing, or even lost. To address these shortcomings, the ACR-NEMA Standards Committee extended its DICOM (Digital Imaging & Communications in Medicine) standard from Radiology to RT by ratifying seven DICOM RT objects starting in 1997 [1,2]. However, they are not broadly used yet by the RT community in daily clinical operations. In the past, the research focus of an RT department has primarily been developing new protocols and devices to improve treatment process and outcomes of cancer patients with minimal effort dedicated to integration of imaging and information systems. Our attempt is to show a proof-of-concept that a DICOM-RT ePR system can be developed as a foundation to perform medical imaging informatics research in developing decision-support tools and knowledge base for future data mining applications.

Music and Video Gaming during Breaks: Influence on Habitual versus Goal-Directed Decision Making.

PubMed

Liu, Shuyan; Schad, Daniel J; Kuschpel, Maxim S; Rapp, Michael A; Heinz, Andreas

2016-01-01

Different systems for habitual versus goal-directed control are thought to underlie human decision-making. Working memory is known to shape these decision-making systems and their interplay, and is known to support goal-directed decision making even under stress. Here, we investigated if and how decision systems are differentially influenced by breaks filled with diverse everyday life activities known to modulate working memory performance. We used a within-subject design where young adults listened to music and played a video game during breaks interleaved with trials of a sequential two-step Markov decision task, designed to assess habitual as well as goal-directed decision making. Based on a neurocomputational model of task performance, we observed that for individuals with a rather limited working memory capacity video gaming as compared to music reduced reliance on the goal-directed decision-making system, while a rather large working memory capacity prevented such a decline. Our findings suggest differential effects of everyday activities on key decision-making processes.

Music and Video Gaming during Breaks: Influence on Habitual versus Goal-Directed Decision Making

PubMed Central

Kuschpel, Maxim S.; Rapp, Michael A.; Heinz, Andreas

2016-01-01

Different systems for habitual versus goal-directed control are thought to underlie human decision-making. Working memory is known to shape these decision-making systems and their interplay, and is known to support goal-directed decision making even under stress. Here, we investigated if and how decision systems are differentially influenced by breaks filled with diverse everyday life activities known to modulate working memory performance. We used a within-subject design where young adults listened to music and played a video game during breaks interleaved with trials of a sequential two-step Markov decision task, designed to assess habitual as well as goal-directed decision making. Based on a neurocomputational model of task performance, we observed that for individuals with a rather limited working memory capacity video gaming as compared to music reduced reliance on the goal-directed decision-making system, while a rather large working memory capacity prevented such a decline. Our findings suggest differential effects of everyday activities on key decision-making processes. PMID:26982326

Research design of decision support system for team sport

NASA Astrophysics Data System (ADS)

Abidin, Mohammad Zukuwwan Zainol; Nawawi, Mohd Kamal Mohd; Kasim, Maznah Mat

2016-10-01

This paper proposes a suitable research procedure that can be referred to while conducting a Decision Support System (DSS) study, especially when the development activity of system artifacts becomes one of the research objectives. The design of the research procedure was based on the completion of a football DSS development that can help in determining the position of a player and the best team formation to be used during a game. After studying the relevant literature, we found that it is necessary to combine the conventional rainfall System Development Life Cycle (SDLC) approach with Case Study approach to help in structuring the research task and phases, which can contribute to the fulfillment of the research aim and objectives.

Comparison of risk-based decision-support systems for brownfield site rehabilitation: DESYRE and SADA applied to a Romanian case study.

PubMed

Stezar, I C; Pizzol, L; Critto, A; Ozunu, A; Marcomini, A

2013-12-15

Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options. Copyright © 2013 Elsevier Ltd. All rights reserved.

An integrative model for in-silico clinical-genomics discovery science.

PubMed

Lussier, Yves A; Sarkar, Indra Nell; Cantor, Michael

2002-01-01

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

Developing Cost Accounting and Decision Support Software for Comprehensive Community-Based Support Systems: An Analysis of Needs, Interest, and Readiness in the Field.

ERIC Educational Resources Information Center

Harrington, Robert; Jenkins, Peter; Marzke, Carolyn; Cohen, Carol

Prominent among the new models of social service delivery are organizations providing comprehensive, community-based supports and services (CCBSS) to children and their families. A needs analysis explored CCBSS sites' interest in and readiness to use a software tool designed to help them make more effective internal resource allocation decisions…

Modelling and Decision Support of Clinical Pathways

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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

2015-01-01

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

Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology.

PubMed

Syeda-Mahmood, Tanveer

2018-03-01

The field of diagnostic decision support in radiology is undergoing rapid transformation with the availability of large amounts of patient data and the development of new artificial intelligence methods of machine learning such as deep learning. They hold the promise of providing imaging specialists with tools for improving the accuracy and efficiency of diagnosis and treatment. In this article, we will describe the growth of this field for radiology and outline general trends highlighting progress in the field of diagnostic decision support from the early days of rule-based expert systems to cognitive assistants of the modern era. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Performance improvement of 64-QAM coherent optical communication system by optimizing symbol decision boundary based on support vector machine

NASA Astrophysics Data System (ADS)

Chen, Wei; Zhang, Junfeng; Gao, Mingyi; Shen, Gangxiang

2018-03-01

High-order modulation signals are suited for high-capacity communication systems because of their high spectral efficiency, but they are more vulnerable to various impairments. For the signals that experience degradation, when symbol points overlap on the constellation diagram, the original linear decision boundary cannot be used to distinguish the classification of symbol. Therefore, it is advantageous to create an optimum symbol decision boundary for the degraded signals. In this work, we experimentally demonstrated the 64-quadrature-amplitude modulation (64-QAM) coherent optical communication system using support-vector machine (SVM) decision boundary algorithm to create the optimum symbol decision boundary for improving the system performance. We investigated the influence of various impairments on the 64-QAM coherent optical communication systems, such as the impairments caused by modulator nonlinearity, phase skew between in-phase (I) arm and quadrature-phase (Q) arm of the modulator, fiber Kerr nonlinearity and amplified spontaneous emission (ASE) noise. We measured the bit-error-ratio (BER) performance of 75-Gb/s 64-QAM signals in the back-to-back and 50-km transmission. By using SVM to optimize symbol decision boundary, the impairments caused by I/Q phase skew of the modulator, fiber Kerr nonlinearity and ASE noise are greatly mitigated.

Decision support system for drinking water management

NASA Astrophysics Data System (ADS)

Janža, M.

2012-04-01

The problems in drinking water management are complex and often solutions must be reached under strict time constrains. This is especially distinct in case of environmental accidents in the catchment areas of the wells that are used for drinking water supply. The beneficial tools that can help decision makers and make program of activities more efficient are decision support systems (DSS). In general they are defined as computer-based support systems that help decision makers utilize data and models to solve unstructured problems. The presented DSS was developed in the frame of INCOME project which is focused on the long-term stable and safe drinking water supply in Ljubljana. The two main water resources Ljubljana polje and Barje alluvial aquifers are characterized by a strong interconnection of surface and groundwater, high vulnerability, high velocities of groundwater flow and pollutant transport. In case of sudden pollution, reactions should be very fast to avoid serious impact to the water supply. In the area high pressures arising from urbanization, industry, traffic, agriculture and old environmental burdens. The aim of the developed DSS is to optimize the activities in cases of emergency water management and to optimize the administrative work regarding the activities that can improve groundwater quality status. The DSS is an interactive computer system that utilizes data base, hydrological modelling, and experts' and stakeholders' knowledge. It consists of three components, tackling the different abovementioned issues in water management. The first one utilizes the work on identification, cleaning up and restoration of illegal dumpsites that are a serious threat to the qualitative status of groundwater. The other two components utilize the predictive capability of the hydrological model and scenario analysis. The user interacts with the system by a graphical interface that guides the user step-by-step to the recommended remedial measures. Consequently, the acquisition of information to support the water management's decisions is simplified and faster, thus contributing to more efficient water management and a safer supply of drinking water.

Cardiological database management system as a mediator to clinical decision support.

PubMed

Pappas, C; Mavromatis, A; Maglaveras, N; Tsikotis, A; Pangalos, G; Ambrosiadou, V

1996-03-01

An object-oriented medical database management system is presented for a typical cardiologic center, facilitating epidemiological trials. Object-oriented analysis and design were used for the system design, offering advantages for the integrity and extendibility of medical information systems. The system was developed using object-oriented design and programming methodology, the C++ language and the Borland Paradox Relational Data Base Management System on an MS-Windows NT environment. Particular attention was paid to system compatibility, portability, the ease of use, and the suitable design of the patient record so as to support the decisions of medical personnel in cardiovascular centers. The system was designed to accept complex, heterogeneous, distributed data in various formats and from different kinds of examinations such as Holter, Doppler and electrocardiography.

Life insurance risk assessment using a fuzzy logic expert system

NASA Technical Reports Server (NTRS)

Carreno, Luis A.; Steel, Roy A.

1992-01-01

In this paper, we present a knowledge based system that combines fuzzy processing with rule-based processing to form an improved decision aid for evaluating risk for life insurance. This application illustrates the use of FuzzyCLIPS to build a knowledge based decision support system possessing fuzzy components to improve user interactions and KBS performance. The results employing FuzzyCLIPS are compared with the results obtained from the solution of the problem using traditional numerical equations. The design of the fuzzy solution consists of a CLIPS rule-based system for some factors combined with fuzzy logic rules for others. This paper describes the problem, proposes a solution, presents the results, and provides a sample output of the software product.

Models, Measurements, and Local Decisions: Assessing and ...

EPA Pesticide Factsheets

This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include either exposure or emissions reduction, and a host of stakeholders, including residents, academics, NGOs, local and federal agencies. This presentation includes results from the C-PORT modeling system, and from a citizen science project from the local area. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Investigation and design of a Project Management Decision Support System for the 4950th Test Wing.

DTIC Science & Technology

1986-03-01

all decision makers is the need for memory aids (reports, hand written notes, mental memory joggers, etc.). 4. Even in similar decision making ... memories to synthesize a decision- making process based on their individual styles, skills, and knowledge (Sprague, 1982: 106). Control mechanisms...representations shown in Figures 4.9 and 4.10 provide a means to this objective. By enabling a manager to make and record reasonable changes to

Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

PubMed

Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

2017-11-01

Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Decision Support Systems Project. Design Review Conference, October 14-15, 1984. Summary Report of Findings.

ERIC Educational Resources Information Center

Tetlow, William L.

Findings of a conference that reviewed and evaluated design decisions concerning the Decision Support System (DSS) Demonstrator are summarized. The DSS Demonstrator was designed by the National Center for Higher Education Management Systems as an example of the way in which microcomputer technology can support and make more effective planning and…

Bladder cancer treatment response assessment with radiomic, clinical, and radiologist semantic features

NASA Astrophysics Data System (ADS)

Gordon, Marshall N.; Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z.

2018-02-01

We are developing a decision support system for assisting clinicians in assessment of response to neoadjuvant chemotherapy for bladder cancer. Accurate treatment response assessment is crucial for identifying responders and improving quality of life for non-responders. An objective machine learning decision support system may help reduce variability and inaccuracy in treatment response assessment. We developed a predictive model to assess the likelihood that a patient will respond based on image and clinical features. With IRB approval, we retrospectively collected a data set of pre- and post- treatment CT scans along with clinical information from surgical pathology from 98 patients. A linear discriminant analysis (LDA) classifier was used to predict the likelihood that a patient would respond to treatment based on radiomic features extracted from CT urography (CTU), a radiologist's semantic feature, and a clinical feature extracted from surgical and pathology reports. The classification accuracy was evaluated using the area under the ROC curve (AUC) with a leave-one-case-out cross validation. The classification accuracy was compared for the systems based on radiomic features, clinical feature, and radiologist's semantic feature. For the system based on only radiomic features the AUC was 0.75. With the addition of clinical information from examination under anesthesia (EUA) the AUC was improved to 0.78. Our study demonstrated the potential of designing a decision support system to assist in treatment response assessment. The combination of clinical features, radiologist semantic features and CTU radiomic features improved the performance of the classifier and the accuracy of treatment response assessment.

Clinical decision support systems: data quality management and governance.

PubMed

Liaw, Siaw-Teng

2013-01-01

This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. The scope of DQM & IG should range from data creation and collection in clinical settings, through cleaning and, where obtained from multiple sources, linkage, storage, use by the EDS logic engine and algorithms, knowledge base and guidance provided, to curation and presentation. It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care.

Putting flow-ecology relationships into practice: A decision-support system to assess fish community response to water-management scenarios

USGS Publications Warehouse

Cartwright, Jennifer M.; Caldwell, Casey; Nebiker, Steven; Knight, Rodney

2017-01-01

This paper presents a conceptual framework to operationalize flow–ecology relationships into decision-support systems of practical use to water-resource managers, who are commonly tasked with balancing multiple competing socioeconomic and environmental priorities. We illustrate this framework with a case study, whereby fish community responses to various water-management scenarios were predicted in a partially regulated river system at a local watershed scale. This case study simulates management scenarios based on interactive effects of dam operation protocols, withdrawals for municipal water supply, effluent discharges from wastewater treatment, and inter-basin water transfers. Modeled streamflow was integrated with flow–ecology relationships relating hydrologic departure from reference conditions to fish species richness, stratified by trophic, reproductive, and habitat characteristics. Adding a hypothetical new water-withdrawal site was predicted to increase the frequency of low-flow conditions with adverse effects for several fish groups. Imposition of new reservoir release requirements was predicted to enhance flow and fish species richness immediately downstream of the reservoir, but these effects were dissipated further downstream. The framework presented here can be used to translate flow–ecology relationships into evidence-based management by developing decision-support systems for conservation of riverine biodiversity while optimizing water availability for human use.

PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data.

PubMed

Shaban-Nejad, Arash; Lavigne, Maxime; Okhmatovskaia, Anya; Buckeridge, David L

2017-01-01

Population health decision makers must consider complex relationships between multiple concepts measured with differential accuracy from heterogeneous data sources. Population health information systems are currently limited in their ability to integrate data and present a coherent portrait of population health. Consequentially, these systems can provide only basic support for decision makers. The Population Health Record (PopHR) is a semantic web application that automates the integration and extraction of massive amounts of heterogeneous data from multiple distributed sources (e.g., administrative data, clinical records, and survey responses) to support the measurement and monitoring of population health and health system performance for a defined population. The design of the PopHR draws on the theories of the determinants of health and evidence-based public health to harmonize and explicitly link information about a population with evidence about the epidemiology and control of chronic diseases. Organizing information in this manner and linking it explicitly to evidence is expected to improve decision making related to the planning, implementation, and evaluation of population health and health system interventions. In this paper, we describe the PopHR platform and discuss the architecture, design, key modules, and its implementation and use. © 2016 New York Academy of Sciences.

Clinical decision support systems in child and adolescent psychiatry: a systematic review.

PubMed

Koposov, Roman; Fossum, Sturla; Frodl, Thomas; Nytrø, Øystein; Leventhal, Bennett; Sourander, Andre; Quaglini, Silvana; Molteni, Massimo; de la Iglesia Vayá, María; Prokosch, Hans-Ulrich; Barbarini, Nicola; Milham, Michael Peter; Castellanos, Francisco Xavier; Skokauskas, Norbert

2017-11-01

Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.

The role of risk-based prioritization in total quality management

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

Bennett, C.T.

1994-10-01

The climate in which government managers must make decisions grows more complex and uncertain. All stakeholders - the public, industry, and Congress - are demanding greater consciousness, responsibility, and accountability of programs and their budgets. Yet, managerial decisions have become multifaceted, involve greater risk, and operate over much longer time periods. Over the last four or five decades, as policy analysis and decisions became more complex, scientists from psychology, operations research, systems science, and economics have developed a more or less coherent process called decision analysis to aid program management. The process of decision analysis - a systems theoretic approachmore » - provides the backdrop for this paper. The Laboratory Integrated Prioritization System (LIPS) has been developed as a systems analytic and risk-based prioritization tool to aid the management of the Tri-Labs` (Lawrence Livermore, Los Alamos, and Sandia) operating resources. Preliminary analyses of the effects of LIPS has confirmed the practical benefits of decision and systems sciences - the systematic, quantitative reduction in uncertainty. To date, the use of LIPS - and, hence, its value - has been restricted to resource allocation within the Tri-Labs` operations budgets. This report extends the role of risk-based prioritization to the support of DOE Total Quality Management (TQM) programs. Furthermore, this paper will argue for the requirement to institutionalize an evolutionary, decision theoretic approach to the policy analysis of the Department of Energy`s Program Budget.« less

Coordinated management of combined sewer overflows by means of environmental decision support systems.

PubMed

Murla, Damian; Gutierrez, Oriol; Martinez, Montse; Suñer, David; Malgrat, Pere; Poch, Manel

2016-04-15

During heavy rainfall, the capacity of sewer systems and wastewater treatment plants may be surcharged producing uncontrolled wastewater discharges and a depletion of the environmental quality. Therefore there is a need of advanced management tools to tackle with these complex problems. In this paper an environmental decision support system (EDSS), based on the integration of mathematical modeling and knowledge-based systems, has been developed for the coordinated management of urban wastewater systems (UWS) to control and minimize uncontrolled wastewater spills. Effectiveness of the EDSS has been tested in a specially designed virtual UWS, including two sewers systems, two WWTP and one river subjected to typical Mediterranean rain conditions. Results show that sewer systems, retention tanks and wastewater treatment plants improve their performance under wet weather conditions and that EDSS can be very effective tools to improve the management and prevent the system from possible uncontrolled wastewater discharges. Copyright © 2016 Elsevier B.V. All rights reserved.

A Hyperknowledge Framework of Decision Support Systems.

ERIC Educational Resources Information Center

Chang, Ai-Mei; And Others

1994-01-01

Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…

Heuristic-based information acquisition and decision making among pilots.

PubMed

Wiggins, Mark W; Bollwerk, Sandra

2006-01-01

This research was designed to examine the impact of heuristic-based approaches to the acquisition of task-related information on the selection of an optimal alternative during simulated in-flight decision making. The work integrated features of naturalistic and normative decision making and strategies of information acquisition within a computer-based, decision support framework. The study comprised two phases, the first of which involved familiarizing pilots with three different heuristic-based strategies of information acquisition: frequency, elimination by aspects, and majority of confirming decisions. The second stage enabled participants to choose one of the three strategies of information acquisition to resolve a fourth (choice) scenario. The results indicated that task-oriented experience, rather than the information acquisition strategies, predicted the selection of the optimal alternative. It was also evident that of the three strategies available, the elimination by aspects information acquisition strategy was preferred by most participants. It was concluded that task-oriented experience, rather than the process of information acquisition, predicted task accuracy during the decision-making task. It was also concluded that pilots have a preference for one particular approach to information acquisition. Applications of outcomes of this research include the development of decision support systems that adapt to the information-processing capabilities and preferences of users.

SAMS--a systems architecture for developing intelligent health information systems.

PubMed

Yılmaz, Özgün; Erdur, Rıza Cenk; Türksever, Mustafa

2013-12-01

In this paper, SAMS, a novel health information system architecture for developing intelligent health information systems is proposed and also some strategies for developing such systems are discussed. The systems fulfilling this architecture will be able to store electronic health records of the patients using OWL ontologies, share patient records among different hospitals and provide physicians expertise to assist them in making decisions. The system is intelligent because it is rule-based, makes use of rule-based reasoning and has the ability to learn and evolve itself. The learning capability is provided by extracting rules from previously given decisions by the physicians and then adding the extracted rules to the system. The proposed system is novel and original in all of these aspects. As a case study, a system is implemented conforming to SAMS architecture for use by dentists in the dental domain. The use of the developed system is described with a scenario. For evaluation, the developed dental information system will be used and tried by a group of dentists. The development of this system proves the applicability of SAMS architecture. By getting decision support from a system derived from this architecture, the cognitive gap between experienced and inexperienced physicians can be compensated. Thus, patient satisfaction can be achieved, inexperienced physicians are supported in decision making and the personnel can improve their knowledge. A physician can diagnose a case, which he/she has never diagnosed before, using this system. With the help of this system, it will be possible to store general domain knowledge in this system and the personnel's need to medical guideline documents will be reduced.

A Medical Decision Support System for the Space Station Health Maintenance Facility

PubMed Central

Ostler, David V.; Gardner, Reed M.; Logan, James S.

1988-01-01

NASA is developing a Health Maintenance Facility (HMF) to provide the equipment and supplies necessary to deliver medical care in the Space Station. An essential part of the Health Maintenance Facility is a computerized Medical Decision Support System (MDSS) that will enhance the ability of the medical officer (“paramedic” or “physician”) to maintain the crew's health, and to provide emergency medical care. The computer system has four major functions: 1) collect and integrate medical information into an electronic medical record from Space Station medical officers, HMF instrumentation, and exercise equipment; 2) provide an integrated medical record and medical reference information management system; 3) manage inventory for logistical support of supplies and secure pharmaceuticals; 4) supply audio and electronic mail communications between the medical officer and ground based flight surgeons. ImagesFigure 1

Development of a digital clinical pathway for emergency medicine: Lessons from usability testing and implementation failure.

PubMed

Gutenstein, Marc; Pickering, John W; Than, Martin

2018-06-01

Clinical pathways are used to support the management of patients in emergency departments. An existing document-based clinical pathway was used as the foundation on which to design and build a digital clinical pathway for acute chest pain, with the aim of improving clinical calculations, clinician decision-making, documentation, and data collection. Established principles of decision support system design were used to build an application within the existing electronic health record, before testing with a multidisciplinary team of doctors using a think-aloud protocol. Technical authoring was successful, however, usability testing revealed that the user experience and the flexibility of workflow within the application were critical barriers to implementation. Emergency medicine and acute care decision support systems face particular challenges to existing models of linear workflow that should be deliberately addressed in digital pathway design. We make key recommendations regarding digital pathway design in emergency medicine.

Simulating rotational grazing management.

PubMed

Cros, M J; Duru, M; Garcia, F; Martin-Clouaire, R

2001-09-01

Dairy systems predominantly based on rotational grazing are notoriously hard to manage. In order to ensure profitability, this type of production requires quite good organisation, planning, and operating capability on the part of the farmer. A simulation-based decision support system, called SEPATOU, has been developed for this purpose. At the core of the decision support approach lies an explicit and rigorous modelling of the management strategy that underlies a dairy farmer's decision-making behaviour (real or hypothetical). The SEPATOU system is a discrete-event simulator that reproduces the day-to-day dynamics of the farmer's decision process and the response of the controlled biophysical system for which models of grass growth, animal consumption, and milk production are used. SEPATOU provides the means to evaluate and compare tentative strategies by simulating their application throughout the production season under different hypothetical weather conditions. The relative worth of a strategy can be assessed by analysing the effects on the biophysical system and their variability across the representative range of possible conditions that is considered. The activities to be managed concern the type and amount of conserved feed, where to fertilise and how much, the choice of fields to harvest, and most importantly, which field to graze next. Typically, SEPATOU is designed to be used by extension services and farming system scientists. It is implemented in C++ and is currently undergoing a validation process with the intended users.

[Implementation of ontology-based clinical decision support system for management of interactions between antihypertensive drugs and diet].

PubMed

Park, Jeong Eun; Kim, Hwa Sun; Chang, Min Jung; Hong, Hae Sook

2014-06-01

The influence of dietary composition on blood pressure is an important subject in healthcare. Interactions between antihypertensive drugs and diet (IBADD) is the most important factor in the management of hypertension. It is therefore essential to support healthcare providers' decision making role in active and continuous interaction control in hypertension management. The aim of this study was to implement an ontology-based clinical decision support system (CDSS) for IBADD management (IBADDM). We considered the concepts of antihypertensive drugs and foods, and focused on the interchangeability between the database and the CDSS when providing tailored information. An ontology-based CDSS for IBADDM was implemented in eight phases: (1) determining the domain and scope of ontology, (2) reviewing existing ontology, (3) extracting and defining the concepts, (4) assigning relationships between concepts, (5) creating a conceptual map with CmapTools, (6) selecting upper ontology, (7) formally representing the ontology with Protégé (ver.4.3), (8) implementing an ontology-based CDSS as a JAVA prototype application. We extracted 5,926 concepts, 15 properties, and formally represented them using Protégé. An ontology-based CDSS for IBADDM was implemented and the evaluation score was 4.60 out of 5. We endeavored to map functions of a CDSS and implement an ontology-based CDSS for IBADDM.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods.

PubMed

Skjerdal, Taran; Gefferth, Andras; Spajic, Miroslav; Estanga, Edurne Gaston; de Cecare, Alessandra; Vitali, Silvia; Pasquali, Frederique; Bovo, Federica; Manfreda, Gerardo; Mancusi, Rocco; Trevisiani, Marcello; Tessema, Girum Tadesse; Fagereng, Tone; Moen, Lena Haugland; Lyshaug, Lars; Koidis, Anastasios; Delgado-Pando, Gonzalo; Stratakos, Alexandros Ch; Boeri, Marco; From, Cecilie; Syed, Hyat; Muccioli, Mirko; Mulazzani, Roberto; Halbert, Catherine

2017-01-01

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes , quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as "good"; "sufficient"; or "corrective action needed" based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods

PubMed Central

Gefferth, Andras; Spajic, Miroslav; Estanga, Edurne Gaston; Vitali, Silvia; Pasquali, Frederique; Bovo, Federica; Manfreda, Gerardo; Mancusi, Rocco; Tessema, Girum Tadesse; Fagereng, Tone; Moen, Lena Haugland; Lyshaug, Lars; Koidis, Anastasios; Delgado-Pando, Gonzalo; Stratakos, Alexandros Ch.; Boeri, Marco; From, Cecilie; Syed, Hyat; Muccioli, Mirko; Mulazzani, Roberto; Halbert, Catherine

2017-01-01

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as “good”; “sufficient”; or “corrective action needed” based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users. PMID:29457031

A public health decision support system model using reasoning methods.

PubMed

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

E-Estuary: Developing a Decision-support System for Coastal Management in the Conterminous United States

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The United States Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E...

The Use of the Integrated Medical Model for Forecasting and Mitigating Medical Risks for a Near-Earth Asteroid Mission

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Saile, Lynn; Freire de Carvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

2011-01-01

Introduction The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission managers and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight. Methods Stochastic computational methods are used to forecast probability distributions of medical events, crew health metrics, medical resource utilization, and probability estimates of medical evacuation and loss of crew life. The IMM can also optimize medical kits within the constraints of mass and volume for specified missions. The IMM was used to forecast medical evacuation and loss of crew life probabilities, as well as crew health metrics for a near-earth asteroid (NEA) mission. An optimized medical kit for this mission was proposed based on the IMM simulation. Discussion The IMM can provide information to the space program regarding medical risks, including crew medical impairment, medical evacuation and loss of crew life. This information is valuable to mission managers and the space medicine community in assessing risk and developing mitigation strategies. Exploration missions such as NEA missions will have significant mass and volume constraints applied to the medical system. Appropriate allocation of medical resources will be critical to mission success. The IMM capability of optimizing medical systems based on specific crew and mission profiles will be advantageous to medical system designers. Conclusion The IMM is a decision support tool that can provide estimates of the impact of medical events on human space flight missions, such as crew impairment, evacuation, and loss of crew life. It can be used to support the development of mitigation strategies and to propose optimized medical systems for specified space flight missions. Learning Objectives The audience will learn how an evidence-based decision support tool can be used to help assess risk, develop mitigation strategies, and optimize medical systems for exploration space flight missions.

The Contribution of a Decision Support System to Educational Decision-Making Processes

ERIC Educational Resources Information Center

Klein, Joseph; Ronen, Herman

2003-01-01

In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…

Design of a Multi-mode Flight Deck Decision Support System for Airborne Conflict Management

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Krishnamurthy, Karthik

2004-01-01

NASA Langley has developed a multi-mode decision support system for pilots operating in a Distributed Air-Ground Traffic Management (DAG-TM) environment. An Autonomous Operations Planner (AOP) assists pilots in performing separation assurance functions, including conflict detection, prevention, and resolution. Ongoing AOP design has been based on a comprehensive human factors analysis and evaluation results from previous human-in-the-loop experiments with airline pilot test subjects. AOP considers complex flight mode interactions and provides flight guidance to pilots consistent with the current aircraft control state. Pilots communicate goals to AOP by setting system preferences and actively probing potential trajectories for conflicts. To minimize training requirements and improve operational use, AOP design leverages existing alerting philosophies, displays, and crew interfaces common on commercial aircraft. Future work will consider trajectory prediction uncertainties, integration with the TCAS collision avoidance system, and will incorporate enhancements based on an upcoming air-ground coordination experiment.

Towards ontology-based decision support systems for complex ultrasound diagnosis in obstetrics and gynecology.

PubMed

Maurice, P; Dhombres, F; Blondiaux, E; Friszer, S; Guilbaud, L; Lelong, N; Khoshnood, B; Charlet, J; Perrot, N; Jauniaux, E; Jurkovic, D; Jouannic, J-M

2017-05-01

We have developed a new knowledge base intelligent system for obstetrics and gynecology ultrasound imaging, based on an ontology and a reference image collection. This study evaluates the new system to support accurate annotations of ultrasound images. We have used the early ultrasound diagnosis of ectopic pregnancies as a model clinical issue. The ectopic pregnancy ontology was derived from medical texts (4260 ultrasound reports of ectopic pregnancy from a specialist center in the UK and 2795 Pubmed abstracts indexed with the MeSH term "Pregnancy, Ectopic") and the reference image collection was built on a selection from 106 publications. We conducted a retrospective analysis of the signs in 35 scans of ectopic pregnancy by six observers using the new system. The resulting ectopic pregnancy ontology consisted of 1395 terms, and 80 images were collected for the reference collection. The observers used the knowledge base intelligent system to provide a total of 1486 sign annotations. The precision, recall and F-measure for the annotations were 0.83, 0.62 and 0.71, respectively. The global proportion of agreement was 40.35% 95% CI [38.64-42.05]. The ontology-based intelligent system provides accurate annotations of ultrasound images and suggests that it may benefit non-expert operators. The precision rate is appropriate for accurate input of a computer-based clinical decision support and could be used to support medical imaging diagnosis of complex conditions in obstetrics and gynecology. Copyright © 2017. Published by Elsevier Masson SAS.

EPA MODELING TOOLS FOR CAPTURE ZONE DELINEATION

EPA Science Inventory

The EPA Office of Research and Development supports a step-wise modeling approach for design of wellhead protection areas for water supply wells. A web-based WellHEDSS (wellhead decision support system) is under development for determining when simple capture zones (e.g., centri...

A Web-Based Treatment Decision Support Tool for Patients With Advanced Knee Arthritis: Evaluation of User Interface and Content Design

PubMed Central

Zheng, Hua; Rosal, Milagros C; Li, Wenjun; Borg, Amy; Yang, Wenyun; Ayers, David C

2018-01-01

Background Data-driven surgical decisions will ensure proper use and timing of surgical care. We developed a Web-based patient-centered treatment decision and assessment tool to guide treatment decisions among patients with advanced knee osteoarthritis who are considering total knee replacement surgery. Objective The aim of this study was to examine user experience and acceptance of the Web-based treatment decision support tool among older adults. Methods User-centered formative and summative evaluations were conducted for the tool. A sample of 28 patients who were considering total knee replacement participated in the study. Participants’ responses to the user interface design, the clarity of information, as well as usefulness, satisfaction, and acceptance of the tool were collected through qualitative (ie, individual patient interviews) and quantitative (ie, standardized Computer System Usability Questionnaire) methods. Results Participants were older adults with a mean age of 63 (SD 11) years. Three-quarters of them had no technical questions using the tool. User interface design recommendations included larger fonts, bigger buttons, less colors, simpler navigation without extra “next page” click, less mouse movement, and clearer illustrations with simple graphs. Color-coded bar charts and outcome-specific graphs with positive action were easiest for them to understand the outcomes data. Questionnaire data revealed high satisfaction with the tool usefulness and interface quality, and also showed ease of use of the tool, regardless of age or educational status. Conclusions We evaluated the usability of a patient-centered decision support tool designed for advanced knee arthritis patients to facilitate their knee osteoarthritis treatment decision making. The lessons learned can inform other decision support tools to improve interface and content design for older patients’ use. PMID:29712620

A Knowledge-Based Information Management System for Watershed Analysis in the Pacific Northwest U.S.

Treesearch

Keith Reynolds; Patrick Cunningham; Larry Bednar; Michael Saunders; Michael Foster; Richard Olson; Daniel Schmoldt; Donald Latham; Bruce Miller; John Steffenson

1996-01-01

The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis. The system includes: (1) a GIS interface that allows users to navigate graphically to specific provinces and watersheds and display a variety of themes (vegetation, streams, roads, topography, etc...

DXplain: a Web-based diagnostic decision support system for medical students.

PubMed

London, S

1998-01-01

DXplain is a diagnostic decision support program, with a new World Wide Web interface, designed to help medical students and physicians formulate differential diagnoses based on clinical findings. It covers over 2000 diseases and 5000 clinical manifestations. DXplain suggests possible diagnoses, and provides brief descriptions of every disease in the database. Not all diseases are included, nor does DXplain take into account preexisting conditions or the chronological sequence of clinical manifestations. Despite these limitations, it is a useful educational tool, particularly for problem-based learning (PBL) cases and for students in clinical rotations, as it fills a niche not adequately covered by MEDLINE or medical texts. The system is relatively self-explanatory, requiring little or no end-user training. Medical libraries offering, or planning to offer, their users access to Web-based materials and resources may find this system a valuable addition to their electronic collections. Should it prove popular with the local users, provision of access may also establish or enhance the library's image as a partner in medical education.

Decision support at home (DS@HOME) – system architectures and requirements

PubMed Central

2012-01-01

Background Demographic change with its consequences of an aging society and an increase in the demand for care in the home environment has triggered intensive research activities in sensor devices and smart home technologies. While many advanced technologies are already available, there is still a lack of decision support systems (DSS) for the interpretation of data generated in home environments. The aim of the research for this paper is to present the state-of-the-art in DSS for these data, to define characteristic properties of such systems, and to define the requirements for successful home care DSS implementations. Methods A literature review was performed along with the analysis of cross-references. Characteristic properties are proposed and requirements are derived from the available body of literature. Results 79 papers were identified and analyzed, of which 20 describe implementations of decision components. Most authors mention server-based decision support components, but only few papers provide details about the system architecture or the knowledge base. A list of requirements derived from the analysis is presented. Among the primary drawbacks of current systems are the missing integration of DSS in current health information system architectures including interfaces, the missing agreement among developers with regard to the formalization and customization of medical knowledge and a lack of intelligent algorithms to interpret data from multiple sources including clinical application systems. Conclusions Future research needs to address these issues in order to provide useful information – and not only large amounts of data – for both the patient and the caregiver. Furthermore, there is a need for outcome studies allowing for identifying successful implementation concepts. PMID:22640470

Basic physiological systems indicator's informative assessment for children and adolescents obesity diagnosis tasks

NASA Astrophysics Data System (ADS)

Marukhina, O. V.; Berestneva, O. G.; Emelyanova, Yu A.; Romanchukov, S. V.; Petrova, L.; Lombardo, C.; Kozlova, N. V.

2018-05-01

The healthcare computerization creates opportunities to the clinical decision support system development. In the course of diagnosis, doctor manipulates a considerable amount of data and makes a decision in the context of uncertainty basing upon the first-hand experience and knowledge. The situation is exacerbated by the fact that the knowledge scope in medicine is incrementally growing, but the decision-making time does not increase. The amount of medical malpractice is growing and it leads to various negative effects, even the mortality rate increase. IT-solution's development for clinical purposes is one of the most promising and efficient ways to prevent these effects. That is why the efforts of many IT specialists are directed to the doctor's heuristics simulating software or expert-based medical decision-making algorithms development. Thus, the objective of this study is to develop techniques and approaches for the body physiological system's informative value assessment index for the obesity degree evaluation based on the diagnostic findings.

Design and implementation of a risk assessment module in a spatial decision support system

NASA Astrophysics Data System (ADS)

Zhang, Kaixi; van Westen, Cees; Bakker, Wim

2014-05-01

The spatial decision support system named 'Changes SDSS' is currently under development. The goal of this system is to analyze changing hydro-meteorological hazards and the effect of risk reduction alternatives to support decision makers in choosing the best alternatives. The risk assessment module within the system is to assess the current risk, analyze the risk after implementations of risk reduction alternatives, and analyze the risk in different future years when considering scenarios such as climate change, land use change and population growth. The objective of this work is to present the detailed design and implementation plan of the risk assessment module. The main challenges faced consist of how to shift the risk assessment from traditional desktop software to an open source web-based platform, the availability of input data and the inclusion of uncertainties in the risk analysis. The risk assessment module is developed using Ext JS library for the implementation of user interface on the client side, using Python for scripting, as well as PostGIS spatial functions for complex computations on the server side. The comprehensive consideration of the underlying uncertainties in input data can lead to a better quantification of risk assessment and a more reliable Changes SDSS, since the outputs of risk assessment module are the basis for decision making module within the system. The implementation of this module will contribute to the development of open source web-based modules for multi-hazard risk assessment in the future. This work is part of the "CHANGES SDSS" project, funded by the European Community's 7th Framework Program.

Development of a SNOMED CT based national medication decision support system.

PubMed

Greibe, Kell

2013-01-01

Physicians often lack the time to familiarize themselves with the details of particular allergies or other drug restrictions. Clinical Decision Support (CDS), based on a structured terminology as SNOMED CT (SCT), can help physicians get an overview, by automatically alerting allergy, interactions and other important information. The centralized CDS platform based on SCT, controls Allergy, Interactions, Risk Situation Drugs and Max Dose restrictions by the help of databases developed for these specific purposes. The CDS will respond to automatic web service requests from the hospital or GP electronic medication system (EMS) during prescription, and return alerts and information. The CDS also contains a Physicians Preference Database where the physicians individually can set which kind of alerts they want to see. The result is clinically useful information physicians can use as a base for a more effective and safer treatment, without developing alert fatigue.

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

Analyzing Information Systems Development: A Comparison and Analysis of Eight IS Development Approaches.

ERIC Educational Resources Information Center

Iivari, Juhani; Hirschheim, Rudy

1996-01-01

Analyzes and compares eight information systems (IS) development approaches: Information Modelling, Decision Support Systems, the Socio-Technical approach, the Infological approach, the Interactionist approach, the Speech Act-based approach, Soft Systems Methodology, and the Scandinavian Trade Unionist approach. Discusses the organizational roles…

E-Estuary: Developing a Decision Support System for Coastal Management in the Conterminous United States (IAHR)

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

E-Estuary: Developing a Decision-support System for Coastal Management in the Counterminous Untied States (Coastal Geotools 09)

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

E-estuary: A Decision Support System for Coastal Water and Ecosystem Management in the US (CZ09)

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

Towards integration of clinical decision support in commercial hospital information systems using distributed, reusable software and knowledge components.

PubMed

Müller, M L; Ganslandt, T; Eich, H P; Lang, K; Ohmann, C; Prokosch, H U

2001-12-01

Clinicians' acceptance of clinical decision support depends on its workflow-oriented, context-sensitive accessibility and availability at the point of care, integrated into the Electronic Patient Record (EPR). Commercially available Hospital Information Systems (HIS) often focus on administrative tasks and mostly do not provide additional knowledge based functionality. Their traditionally monolithic and closed software architecture encumbers integration of and interaction with external software modules. Our aim was to develop methods and interfaces to integrate knowledge sources into two different commercial hospital information systems to provide the best decision support possible within the context of available patient data. An existing, proven standalone scoring system for acute abdominal pain was supplemented by a communication interface. In both HIS we defined data entry forms and developed individual and reusable mechanisms for data exchange with external software modules. We designed an additional knowledge support frontend which controls data exchange between HIS and the knowledge modules. Finally, we added guidelines and algorithms to the knowledge library. Despite some major drawbacks which resulted mainly from the HIS' closed software architectures we showed exemplary, how external knowledge support can be integrated almost seamlessly into different commercial HIS. This paper describes the prototypical design and current implementation and discusses our experiences.

A knowledge engineering framework towards clinical support for adverse drug event prevention: the PSIP approach.

PubMed

Koutkias, Vassilis; Stalidis, George; Chouvarda, Ioanna; Lazou, Katerina; Kilintzis, Vassilis; Maglaveras, Nicos

2009-01-01

Adverse Drug Events (ADEs) are currently considered as a major public health issue, endangering patients' safety and causing significant healthcare costs. Several research efforts are currently concentrating on the reduction of preventable ADEs by employing Information Technology (IT) solutions, which aim to provide healthcare professionals and patients with relevant knowledge and decision support tools. In this context, we present a knowledge engineering approach towards the construction of a Knowledge-based System (KBS) regarded as the core part of a CDSS (Clinical Decision Support System) for ADE prevention, all developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the knowledge sources considered in PSIP and the implications they pose to knowledge engineering, the methodological approach followed, as well as the components defining the knowledge engineering framework based on relevant state-of-the-art technologies and representation formalisms.

Women's health nursing in the context of the National Health Information Infrastructure.

PubMed

Jenkins, Melinda L; Hewitt, Caroline; Bakken, Suzanne

2006-01-01

Nurses must be prepared to participate in the evolving National Health Information Infrastructure and the changes that will consequently occur in health care practice and documentation. Informatics technologies will be used to develop electronic health records with integrated decision support features that will likely lead to enhanced health care quality and safety. This paper provides a summary of the National Health Information Infrastructure and highlights electronic health records and decision support systems within the context of evidence-based practice. Activities at the Columbia University School of Nursing designed to prepare nurses with the necessary informatics competencies to practice in a National Health Information Infrastructure-enabled health care system are described. Data are presented from electronic (personal digital assistant) encounter logs used in our Women's Health Nurse Practitioner program to support evidence-based advanced practice nursing care. Implications for nursing practice, education, and research in the evolving National Health Information Infrastructure are discussed.

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

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

Luo, Y; McShan, D; Schipper, M

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity tomore » different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.« less

System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Goienetxea Uriarte, A.; Ruiz Zúñiga, E.; Urenda Moris, M.; Ng, A. H. C.

2015-05-01

Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

The Invasive Species Forecasting System

NASA Technical Reports Server (NTRS)

Schnase, John; Most, Neal; Gill, Roger; Ma, Peter

2011-01-01

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

GIS-based integrated assessment and decision support system for land use planning in consideration of carbon sequestration benefits

NASA Astrophysics Data System (ADS)

Wang, Jun; Chen, J. M.; Li, Manchun; Ju, Weimin

2007-06-01

As the major eligible land use activities in the Clean Development Mechanism (CDM), afforestation and reforestation offer opportunities and potential economic benefits for developing countries to participate in carbon-trade in the potential international carbon (C) sink markets. However, the design and selection of appropriate afforestation and reforestation locations in CDM are complex processes which need integrated assessment (IA) of C sequestration (CS) potential, environmental effects, and socio-economic impacts. This paper promotes the consideration of CS benefits in local land use planning and presents a GIS-based integrated assessment and spatial decision support system (IA-SDSS) to support decision-making on 'where' and 'how' to afforest. It integrates an Integrated Terrestrial Ecosystem Carbon Model (InTEC) and a GIS platform for modeling regional long-term CS potential and assessment of geo-referenced land use criteria including CS consequence, and produces ranking of plantation schemes with different tree species using the Analytic hierarchy process (AHP) method. Three land use scenarios are investigated: (i) traditional land use planning criteria without C benefits, (ii) land use for CS with low C price, and (iii) land use for CS with high price. Different scenarios and consequences will influence the weights of tree-species selection in the AHP decision process.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

Developing and Evaluating Communication Strategies to Support Informed Decisions and Practice Based on Evidence (DECIDE): protocol and preliminary results.

PubMed

Treweek, Shaun; Oxman, Andrew D; Alderson, Philip; Bossuyt, Patrick M; Brandt, Linn; Brożek, Jan; Davoli, Marina; Flottorp, Signe; Harbour, Robin; Hill, Suzanne; Liberati, Alessandro; Liira, Helena; Schünemann, Holger J; Rosenbaum, Sarah; Thornton, Judith; Vandvik, Per Olav; Alonso-Coello, Pablo

2013-01-09

Healthcare decision makers face challenges when using guidelines, including understanding the quality of the evidence or the values and preferences upon which recommendations are made, which are often not clear. GRADE is a systematic approach towards assessing the quality of evidence and the strength of recommendations in healthcare. GRADE also gives advice on how to go from evidence to decisions. It has been developed to address the weaknesses of other grading systems and is now widely used internationally. The Developing and Evaluating Communication Strategies to Support Informed Decisions and Practice Based on Evidence (DECIDE) consortium (http://www.decide-collaboration.eu/), which includes members of the GRADE Working Group and other partners, will explore methods to ensure effective communication of evidence-based recommendations targeted at key stakeholders: healthcare professionals, policymakers, and managers, as well as patients and the general public. Surveys and interviews with guideline producers and other stakeholders will explore how presentation of the evidence could be improved to better meet their information needs. We will collect further stakeholder input from advisory groups, via consultations and user testing; this will be done across a wide range of healthcare systems in Europe, North America, and other countries. Targeted communication strategies will be developed, evaluated in randomized trials, refined, and assessed during the development of real guidelines. Results of the DECIDE project will improve the communication of evidence-based healthcare recommendations. Building on the work of the GRADE Working Group, DECIDE will develop and evaluate methods that address communication needs of guideline users. The project will produce strategies for communicating recommendations that have been rigorously evaluated in diverse settings, and it will support the transfer of research into practice in healthcare systems globally.

E-DECIDER Decision Support Gateway For Earthquake Disaster Response

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

2013-12-01

Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that delivers map data products including deformation modeling results (slope change and strain magnitude) and aftershock forecasts, with remote sensing change detection results under development. These products are event triggered (from the USGS earthquake feed) and will be posted to event feeds on the E-DECIDER webpage and accessible via the mobile interface and UICDS. E-DECIDER also features a KML service that provides infrastructure information from the FEMA HAZUS database through UICDS and the mobile interface. The back-end GIS service architecture and front-end gateway components form a decision support system that is designed for ease-of-use and extensibility for end-users.

Transit Operations Decision Support System (TODSS) core requirements evaluation and update recommendations.

DOT National Transportation Integrated Search

2009-10-01

Transit Operations Decision Support Systems (TODSS) are systems designed to support dispatchers and others in real-time operations : management in response to incidents, special events, and other changing conditions in order to improve operating spee...

CAESAR : an expert system for evaluation of scour and stream stability

DOT National Transportation Integrated Search

1999-01-01

This report documents the development and testing of a field-deployable, knowledge-based decision support system that assists bridge inspectors by acquiring, cataloging, storing, and retrieving information necessary for the evaluation of a bridge for...

Developing a model-based decision support system for call-a-ride paratransit service problems.

DOT National Transportation Integrated Search

2011-02-01

Paratransit is the transportation service that supplements larger public transportation : systems by providing individualized rides without fixed routes or timetables. In 1990, : the Americans with Disabilities Act (ADA) was passed which allows passe...

Evaluation of the Effectiveness of Stormwater Decision Support Tools for Infrastructure Selection and the Barriers to Implementation

NASA Astrophysics Data System (ADS)

Spahr, K.; Hogue, T. S.

2016-12-01

Selecting the most appropriate green, gray, and / or hybrid system for stormwater treatment and conveyance can prove challenging to decision markers across all scales, from site managers to large municipalities. To help streamline the selection process, a multi-disciplinary team of academics and professionals is developing an industry standard for selecting and evaluating the most appropriate stormwater management technology for different regions. To make the tool more robust and comprehensive, life-cycle cost assessment and optimization modules will be included to evaluate non-monetized and ecosystem benefits of selected technologies. Initial work includes surveying advisory board members based in cities that use existing decision support tools in their infrastructure planning process. These surveys will qualify the decisions currently being made and identify challenges within the current planning process across a range of hydroclimatic regions and city size. Analysis of social and other non-technical barriers to adoption of the existing tools is also being performed, with identification of regional differences and institutional challenges. Surveys will also gage the regional appropriateness of certain stormwater technologies based off experiences in implementing stormwater treatment and conveyance plans. In additional to compiling qualitative data on existing decision support tools, a technical review of components of the decision support tool used will be performed. Gaps in each tool's analysis, like the lack of certain critical functionalities, will be identified and ease of use will be evaluated. Conclusions drawn from both the qualitative and quantitative analyses will be used to inform the development of the new decision support tool and its eventual dissemination.

The Research of Spatial-Temporal Analysis and Decision-Making Assistant System for Disabled Person Affairs Based on Mapworld

NASA Astrophysics Data System (ADS)

Zhang, J. H.; Yang, J.; Sun, Y. S.

2015-06-01

This system combines the Mapworld platform and informationization of disabled person affairs, uses the basic information of disabled person as center frame. Based on the disabled person population database, the affairs management system and the statistical account system, the data were effectively integrated and the united information resource database was built. Though the data analysis and mining, the system provides powerful data support to the decision making, the affairs managing and the public serving. It finally realizes the rationalization, normalization and scientization of disabled person affairs management. It also makes significant contributions to the great-leap-forward development of the informationization of China Disabled Person's Federation.

Fews-Risk: A step towards risk-based flood forecasting

NASA Astrophysics Data System (ADS)

Bachmann, Daniel; Eilander, Dirk; de Leeuw, Annemargreet; Diermanse, Ferdinand; Weerts, Albrecht; de Bruijn, Karin; Beckers, Joost; Boelee, Leonore; Brown, Emma; Hazlewood, Caroline

2015-04-01

Operational flood prediction and the assessment of flood risk are important components of flood management. Currently, the model-based prediction of discharge and/or water level in a river is common practice for operational flood forecasting. Based on the prediction of these values decisions about specific emergency measures are made within operational flood management. However, the information provided for decision support is restricted to pure hydrological or hydraulic aspects of a flood. Information about weak sections within the flood defences, flood prone areas and assets at risk in the protected areas are rarely used in a model-based flood forecasting system. This information is often available for strategic planning, but is not in an appropriate format for operational purposes. The idea of FEWS-Risk is the extension of existing flood forecasting systems with elements of strategic flood risk analysis, such as probabilistic failure analysis, two dimensional flood spreading simulation and the analysis of flood impacts and consequences. Thus, additional information is provided to the decision makers, such as: • Location, timing and probability of failure of defined sections of the flood defence line; • Flood spreading, extent and hydraulic values in the hinterland caused by an overflow or a breach flow • Impacts and consequences in case of flooding in the protected areas, such as injuries or casualties and/or damages to critical infrastructure or economy. In contrast with purely hydraulic-based operational information, these additional data focus upon decision support for answering crucial questions within an operational flood forecasting framework, such as: • Where should I reinforce my flood defence system? • What type of action can I take to mend a weak spot in my flood defences? • What are the consequences of a breach? • Which areas should I evacuate first? This presentation outlines the additional required workflows towards risk-based flood forecasting systems. In a cooperation between HR Wallingford and Deltares, the extended workflows are being integrated into the Delft-FEWS software system. Delft-FEWS provides modules for managing the data handling and forecasting process. Results of a pilot study that demonstrates the new tools are presented. The value of the newly generated information for decision support during a flood event is discussed.

A Decision Support System for Drinking Water Production Integrating Health Risks Assessment

PubMed Central

Delpla, Ianis; Monteith, Donald T.; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G.; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier

2014-01-01

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

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

PubMed

Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

2016-08-15

Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. Copyright © 2016 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

System for decision analysis support on complex waste management issues

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

Shropshire, D.E.

1997-10-01

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,more » 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.« less

A web based spatial decision supporting system for land management and soil conservation

NASA Astrophysics Data System (ADS)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-02-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) but also many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a Spatial Decision Support System based on geospatial cyber-infrastructure (GCI) can embody all of the above, so producing a smart system for supporting decision making for agriculture, forestry and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on soil and land conservation (SOILCONSWEB-LIFE+ project). The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry and urban planning issues through the web. The system has been applied to and tested in an area of about 20 000 ha in the South of Italy, within the framework of a European LIFE+ project. The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart web based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (http://www.landconsultingweb.eu). This may help bridge the last much important divide between scientists working on the landscape and end users.

A Web-based spatial decision supporting system for land management and soil conservation

NASA Astrophysics Data System (ADS)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-07-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) as well as many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a spatial decision support system based on geospatial cyberinfrastructure (GCI) can address all of the above, so producing a smart system for supporting decision making for agriculture, forestry, and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on land management and soil conservation. The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry, and urban planning issues through the Web. The system has been applied to and tested in an area of about 20 000 ha in the south of Italy, within the framework of a European LIFE+ project (SOILCONSWEB). The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart Web-based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (www.landconsultingweb.eu). This may help bridge the last very important divide between scientists working on the landscape and end users.

Toward a Multilingual, Experiential Environment for Learning Decision Technology.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Tan, Seng Teen

1999-01-01

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

A Legal Negotiatiton Support System Based on A Diagram

NASA Astrophysics Data System (ADS)

Nitta, Katsumi; Shibasaki, Masato; Yasumura, Yoshiaki; Hasegawa, Ryuzo; Fujita, Hiroshi; Koshimura, Miyuki; Inoue, Katsumi; Shirai, Yasuyuki; Komatsu, Hiroshi

We present an overview of a legal negotiation support system, ANS (Argumentation based Negotiation support System). ANS consists of a user interface, three inference engines, a database of old cases, and two decision support modules. The ANS users negotiates or disputes with others via a computer network. The negotiation status is managed in the form of the negotiation diagram. The negotiation diagram is an extension of Toulmin’s argument diagram, and it contains all arguments insisted by participants. The negotiation protocols are defined as operations to the negotiation diagram. By exchanging counter arguments each other, the negotiation diagram grows up. Nonmonotonic reasoning using rule priorities are applied to the negotiation diagram.

Measuring the impact of diagnostic decision support on the quality of clinical decision making: development of a reliable and valid composite score.

PubMed

Ramnarayan, Padmanabhan; Kapoor, Ritika R; Coren, Michael; Nanduri, Vasantha; Tomlinson, Amanda L; Taylor, Paul M; Wyatt, Jeremy C; Britto, Joseph F

2003-01-01

Few previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful. Sets of differential diagnoses and clinical management plans generated by 71 clinicians for six simulated cases, before and after decision support from a Web-based pediatric differential diagnostic tool (ISABEL), were used. A composite quality score was calculated separately for each diagnostic and management plan by considering the appropriateness value of each component diagnostic or management suggestion, a weighted sum of individual suggestion ratings, relevance of the entire plan, and its comprehensiveness. The reliability and validity (face, concurrent, construct, and content) of these two final scores were examined. Two hundred fifty-two diagnostic and 350 management suggestions were included in the interrater reliability analysis. There was good agreement between raters (intraclass correlation coefficient, 0.79 for diagnoses, and 0.72 for management). No counterintuitive scores were demonstrated on visual inspection of the sets. Content validity was verified by a consultation process with pediatricians. Both scores discriminated adequately between the plans of consultants and medical students and correlated well with clinicians' subjective opinions of overall plan quality (Spearman rho 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51). The scores described can be used as key outcome measures in a larger study to fully assess the value of diagnostic decision aids, such as the ISABEL system.

A GIS-based decision support system for determining the shortest and safest route to forest fires: a case study in Mediterranean Region of Turkey.

PubMed

Akay, Abdullah E; Wing, Michael G; Sivrikaya, Fatih; Sakar, Dursun

2012-03-01

The ability of firefighting vehicles and staff to reach a fire area as quickly as possible is critical in fighting against forest fires. In this study, a Geographical Information System-based decision support system was developed to assist fire managers in determining the fastest and the safest or more reliable access routes from firefighting headquarters to fire areas. The decision support system was tested in the Kahramanmaras Forestry Regional Directoratein the Mediterranean region of Turkey. The study area consisted of forested lands which had been classified according to fire sensitivity. The fire response routing simulations considered firefighting teams located in 20 firefighting headquarter locations. The road network, the locations of the firefighting headquarters, and possible fire locations were mapped for simulation analysis. In alternative application simulations, inaccessible roads which might be closed due to fire or other reasons were indicated in the network analysis so that the optimum route was not only the fastest but also the safest and most reliable path. The selection of which firefighting headquarters to use was evaluated by considering critical response time to potential fire areas based on fire sensitivity levels. Results indicated that new firefighting headquarters should be established in the region in order to provide sufficient firefighting response to all forested lands. In addition, building new fire access roads and increasing the design speed on current roads could also increase firefighting response capabilities within the study area.

An Expertise Based Energy Information System.

ERIC Educational Resources Information Center

Rosenberg, S.

This paper describes an intelligent decision support system for information on petroleum resources and use currently being designed by the Information Methodology Research Project as the first step in the development of a comprehensive intelligent information system for dealing with energy resources in the United States. The system draws on…

A quantitative risk-based model for reasoning over critical system properties

NASA Technical Reports Server (NTRS)

Feather, M. S.

2002-01-01

This position paper suggests the use of a quantitative risk-based model to help support reeasoning and decision making that spans many of the critical properties such as security, safety, survivability, fault tolerance, and real-time.

Chronic motivational state interacts with task reward structure in dynamic decision-making.

PubMed

Cooper, Jessica A; Worthy, Darrell A; Maddox, W Todd

2015-12-01

Research distinguishes between a habitual, model-free system motivated toward immediately rewarding actions, and a goal-directed, model-based system motivated toward actions that improve future state. We examined the balance of processing in these two systems during state-based decision-making. We tested a regulatory fit hypothesis (Maddox & Markman, 2010) that predicts that global trait motivation affects the balance of habitual- vs. goal-directed processing but only through its interaction with the task framing as gain-maximization or loss-minimization. We found support for the hypothesis that a match between an individual's chronic motivational state and the task framing enhances goal-directed processing, and thus state-based decision-making. Specifically, chronic promotion-focused individuals under gain-maximization and chronic prevention-focused individuals under loss-minimization both showed enhanced state-based decision-making. Computational modeling indicates that individuals in a match between global chronic motivational state and local task reward structure engaged more goal-directed processing, whereas those in a mismatch engaged more habitual processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Temporal reasoning for decision support in medicine.

PubMed

Augusto, Juan Carlos

2005-01-01

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.

The Operational Movement Planning System: A Prototype for the Strategic Command Function

DTIC Science & Technology

1993-06-01

environment. The White Paper identifies "computer based systems to support the decision making of operational and higher level commanders" as an important...exist and objective decisions can be made. When extending the application of computers into the upper levels of an organisation higher productivity...thCtaspot. aiinssetstnttt dtrm In his magstepatecapsables tran lsptort O assets o ahie umr r dniid eemnn capabilty is avery coplex prcess . Cpabilit reuie

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

USGS Publications Warehouse

Booth, N.L.; Everman, E.J.; Kuo, I.-L.; Sprague, L.; Murphy, L.

2011-01-01

The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water-quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water-quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow-weighted concentration, or load of constituents in water under various land-use condition, change, or resource management scenarios. A web-based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

Management Information Systems for Faculty Allocations in Institutions of Higher Education: A Case Study for the Universidad de Santiago de Chile.

ERIC Educational Resources Information Center

Karadima, Oscar

The transformation of the present manual system of data manipulation at the Universidad de Santiago de Chile into a computer-based information system capable of supporting decision making is proposed. The information system would be used to determine the number of faculty required by each academic department, based on the number of weekly hours…

A pattern-based analysis of clinical computer-interpretable guideline modeling languages.

PubMed

Mulyar, Nataliya; van der Aalst, Wil M P; Peleg, Mor

2007-01-01

Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all. PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.

A web-based spatial decision support system for spatial planning and governance in the Guangdong Province

NASA Astrophysics Data System (ADS)

Wu, Qitao; Zhang, Hong-ou; Chen, Fengui; Dou, Jie

2008-10-01

After three decades' rapid economic development, Guangdong province faces to thorny problems related to pollution, resource shortage and environmental deterioration. What is worse, the future accelerated development, urbanization and industrialization also comes at the cost of regional imbalance with economic gaps growing and the quality of life in different regions degrading. Development and Reform Commission of Guangdong Province (GDDRC) started a spatial planning project under the national frame in 2007. The prospective project is expected to enhance the equality of different regions and balance the economic development with environmental protection and improved sustainability. This manuscript presents the results of scientific research aiming to develop a Spatial Decision Support System (SDSS) for this spatial planning project. The system composes four modules include the User interface module (UIM), Spatial Analyze module (SAM), Database management module (DMM) and Help module (HM) base on ArcInfo, JSP/Servlet, JavaScript, MapServer, Visual C++ and Visual Basic technologies. The web-based SDSS provides a user-friendly tool for local decision makers, regional planners and other stakeholders in understanding and visualizing the different territorial dimensions of economic development against sustainable environmental and exhausted resources, and in defining, comparing and prioritizing specific territorially-based actions in order to prevent non-sustainable development and implement relevant politics.

A Fuzzy Rule Based Decision Support System for Identifying Location of Water Harvesting Technologies in Rainfed Agricultural Regions

NASA Astrophysics Data System (ADS)

Chaubey, I.; Vema, V. K.; Sudheer, K.

2016-12-01

Site suitability evaluation of water conservation structures in water scarce rainfed agricultural areas consist of assessment of various landscape characteristics and various criterion. Many of these landscape characteristic attributes are conveyed through linguistic terms rather than precise numeric values. Fuzzy rule based system are capable of incorporating uncertainty and vagueness, when various decision making criteria expressed in linguistic terms are expressed as fuzzy rules. In this study a fuzzy rule based decision support system is developed, for optimal site selection of water harvesting technologies. Water conservation technologies like farm ponds, Check dams, Rock filled dams and percolation ponds aid in conserving water for irrigation and recharging aquifers and development of such a system will aid in improving the efficiency of the structures. Attributes and criteria involved in decision making are classified into different groups to estimate the suitability of the particular technology. The developed model is applied and tested on an Indian watershed. The input attributes are prepared in raster format in ArcGIS software and suitability of each raster cell is calculated and output is generated in the form of a thematic map showing the suitability of the cells pertaining to different technologies. The output of the developed model is compared against the already existing structures and results are satisfactory. This developed model will aid in improving the sustainability and efficiency of the watershed management programs aimed at enhancing in situ moisture content.

Building an Intelligent Water Information System - American River Prototype

NASA Astrophysics Data System (ADS)

Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

With better management, California's existing water supplies could go further to meeting the needs of the state's urban and agricultural uses. For example, California's water reservoirs are currently controlled and regulated using forecasts based upon more than 75 years of historical data. In the face of global climate change, these forecasts are becoming increasingly inadequate to precisely manage water resources. We propose implementing Leveraging the newest frontiers of information technology, we are developing a basin-scale real-time intelligent water infrastructure system that enables more information-intensive decision support. The complete system is made up of four key components. First, a strategically deployed ground-observation system will complement satellite measurements and provide continuous and accurate estimates of snowpack, soil moisture, vegetation state and energy balance across watersheds. Using our recently developed but mature technologies, we deliver measurements of hydrologic variables over a multi- tiered network of wireless sensor arrays, with a granularity of time and space previously unheard of. Second, satellite and aircraft remote sensing provide the only practical means of spatially continuous basin-wide measurement and monitoring of snow properties, vegetation characteristics and other watershed conditions. The ground-based system is designed to blend with remote sensing data on Sierra Nevada snow properties, and provide value-added products of unprecedented spatial detail and accuracy that are useable on a watershed level. Third, together the satellite and ground-based data make possible the updating of forecast tools, and routine use of physically based hydrologic models. The decision-support framework will provide tools to extract and visualize information of interest from the measured and modeled data, to assess uncertainties, and to optimize operations. Fourth, the advanced cyber infrastructure blends and transforms the numbers recorded by sensors into information in the form that is useful for decision-making. In a sense it 'monetizes' the data. It is the cyber infrastructure that links measurements, data processing, models and users. System software must provide flexibility for multiple types of access from user queries to automated and direct links with analysis tools and decision-support systems. We are currently installing a basin-scale ground-based sensor network focusing on measurements of snowpack, solar radiation, temperature, rH and soil moisture across the American River basin. Although this is a research network, it also provides core elements of a full ground-based operational system.

Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts

NASA Astrophysics Data System (ADS)

Tsou, Ming-Cheng; Kao, Sheng-Long; Su, Chien-Min

When an officer of the watch (OOW) faces complicated marine traffic, a suitable decision support tool could be employed in support of collision avoidance decisions, to reduce the burden and greatly improve the safety of marine traffic. Decisions on routes to avoid collisions could also consider economy as well as safety. Through simulating the biological evolution model, this research adopts the genetic algorithm used in artificial intelligence to find a theoretically safety-critical recommendation for the shortest route of collision avoidance from an economic viewpoint, combining the international regulations for preventing collisions at sea (COLREGS) and the safety domain of a ship. Based on this recommendation, an optimal safe avoidance turning angle, navigation restoration time and navigational restoration angle will also be provided. A Geographic Information System (GIS) will be used as the platform for display and operation. In order to achieve advance notice of alerts and due preparation for collision avoidance, a Vessel Traffic Services (VTS) operator and the OOW can use this system as a reference to assess collision avoidance at present location.

Clinical genomics information management software linking cancer genome sequence and clinical decisions.

PubMed

Watt, Stuart; Jiao, Wei; Brown, Andrew M K; Petrocelli, Teresa; Tran, Ben; Zhang, Tong; McPherson, John D; Kamel-Reid, Suzanne; Bedard, Philippe L; Onetto, Nicole; Hudson, Thomas J; Dancey, Janet; Siu, Lillian L; Stein, Lincoln; Ferretti, Vincent

2013-09-01

Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician. Copyright © 2013 Elsevier Inc. All rights reserved.

Electronic Risk Assessment System as an Appropriate Tool for the Prevention of Cancer: a Qualitative Study.

PubMed

Javan Amoli, Amir Hossein; Maserat, Elham; Safdari, Reza; Zali, Mohammad Reza

2015-01-01

Decision making modalities for screening for many cancer conditions and different stages have become increasingly complex. Computer-based risk assessment systems facilitate scheduling and decision making and support the delivery of cancer screening services. The aim of this article was to survey electronic risk assessment system as an appropriate tool for the prevention of cancer. A qualitative design was used involving 21 face-to-face interviews. Interviewing involved asking questions and getting answers from exclusive managers of cancer screening. Of the participants 6 were female and 15 were male, and ages ranged from 32 to 78 years. The study was based on a grounded theory approach and the tool was a semi- structured interview. Researchers studied 5 dimensions, comprising electronic guideline standards of colorectal cancer screening, work flow of clinical and genetic activities, pathways of colorectal cancer screening and functionality of computer based guidelines and barriers. Electronic guideline standards of colorectal cancer screening were described in the s3 categories of content standard, telecommunications and technical standards and nomenclature and classification standards. According to the participations' views, workflow and genetic pathways of colorectal cancer screening were identified. The study demonstrated an effective role of computer-guided consultation for screening management. Electronic based systems facilitate real-time decision making during a clinical interaction. Electronic pathways have been applied for clinical and genetic decision support, workflow management, update recommendation and resource estimates. A suitable technical and clinical infrastructure is an integral part of clinical practice guidline of screening. As a conclusion, it is recommended to consider the necessity of architecture assessment and also integration standards.

Intelligent instrumentation applied in environment management

NASA Astrophysics Data System (ADS)

Magheti, Mihnea I.; Walsh, Patrick; Delassus, Patrick

2005-06-01

The use of information and communications technology in environment management and research has witnessed a renaissance in recent years. From optical sensor technology, expert systems, GIS and communications technologies to computer aided harvesting and yield prediction, these systems are increasable used for applications developing in the management sector of natural resources and biodiversity. This paper presents an environmental decision support system, used to monitor biodiversity and present a risk rating for the invasion of pests into the particular systems being examined. This system will utilise expert mobile technology coupled with artificial intelligence and predictive modelling, and will emphasize the potential for expansion into many areas of intelligent remote sensing and computer aided decision-making for environment management or certification. Monitoring and prediction in natural systems, harnessing the potential of computing and communication technologies is an emerging technology within the area of environmental management. This research will lead to the initiation of a hardware and software multi tier decision support system for environment management allowing an evaluation of areas for biodiversity or areas at risk from invasive species, based upon environmental factors/systems.

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

PubMed

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

2008-02-12

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

Flood Forecast Accuracy and Decision Support System Approach: the Venice Case

NASA Astrophysics Data System (ADS)

Canestrelli, A.; Di Donato, M.

2016-02-01

In the recent years numerical models for weather predictions have experienced continuous advances in technology. As a result, all the disciplines making use of weather forecasts have made significant steps forward. In the case of the Safeguard of Venice, a large effort has been put in order to improve the forecast of tidal levels. In this context, the Istituzione Centro Previsioni e Segnalazioni Maree (ICPSM) of the Venice Municipality has developed and tested many different forecast models, both of the statistical and deterministic type, and has shown to produce very accurate forecasts. For Venice, the maximum admissible forecast error should be (ideally) of the order of ten centimeters at 24 hours. The entity of the forecast error clearly affects the decisional process, which mainly consists of alerting the population, activating the movable barriers installed at the three tidal inlets and contacting the port authority. This process becomes more challenging whenever the weather predictions, and therefore the water level forecasts, suddenly change. These new forecasts have to be quickly transformed into operational tasks. Therefore, it is of the utter importance to set up scheduled alerts and emergency plans by means of easy-to-follow procedures. On this direction, Technital has set up a Decision Support System based on expert procedures that minimizes the human mistakes and, as a consequence, reduces the risk of flooding of the historical center. Moreover, the Decision Support System can communicate predefined alerts to all the interested subjects. The System uses the water levels forecasts produced by the ICPSM by taking into account the accuracy at different leading times. The Decision Support System has been successfully tested with 8 years of data, 6 of them in real time. Venice experience shows that the Decision Support System is an essential tool which assesses the risks associated with a particular event, provides clear operational procedures and minimizes the impact of natural floods on human lives, private properties and historical monuments.

Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review.

PubMed

Liedlgruber, Michael; Uhl, Andreas

2011-01-01

Today, medical endoscopy is a widely used procedure to inspect the inner cavities of the human body. The advent of endoscopic imaging techniques-allowing the acquisition of images or videos-created the possibility for the development of the whole new branch of computer-aided decision support systems. Such systems aim at helping physicians to identify possibly malignant abnormalities more accurately. At the beginning of this paper, we give a brief introduction to the history of endoscopy, followed by introducing the main types of endoscopes which emerged so far (flexible endoscope, wireless capsule endoscope, and confocal laser endomicroscope). We then give a brief introduction to computer-aided decision support systems specifically targeted at endoscopy in the gastrointestinal tract. Then we present general facts and figures concerning computer-aided decision support systems and summarize work specifically targeted at computer-aided decision support in the gastrointestinal tract. This summary is followed by a discussion of some common issues concerning the approaches reviewed and suggestions of possible ways to resolve them.

Keeping Teachers in the Center: A Framework of Data-Driven Decision-Making

ERIC Educational Resources Information Center

Light, Daniel; Wexler, Dara H.; Heinze, Juliette

2004-01-01

The Education Development Center's Center for Children and Technology (CCT) conducted a three year study of a large-scale data reporting system, developed by the Grow Network for New York City's Department of Education. This paper presents a framework based on two years of research exploring the intersection of decision-support technologies,…

Transit Operations Decision Support System (TODSS) core requirements prototype development case study and lessons learned.

DOT National Transportation Integrated Search

2010-02-01

Transit Operations Decision Support Systems (TODSS) are systems designed to support dispatchers and others in real-time operations : management in response to incidents, special events, and other changing conditions. As part of a joint Federal Transi...

Probabilistic Risk Assessment for Decision Making During Spacecraft Operations

NASA Technical Reports Server (NTRS)

Meshkat, Leila

2009-01-01

Decisions made during the operational phase of a space mission often have significant and immediate consequences. Without the explicit consideration of the risks involved and their representation in a solid model, it is very likely that these risks are not considered systematically in trade studies. Wrong decisions during the operational phase of a space mission can lead to immediate system failure whereas correct decisions can help recover the system even from faulty conditions. A problem of special interest is the determination of the system fault protection strategies upon the occurrence of faults within the system. Decisions regarding the fault protection strategy also heavily rely on a correct understanding of the state of the system and an integrated risk model that represents the various possible scenarios and their respective likelihoods. Probabilistic Risk Assessment (PRA) modeling is applicable to the full lifecycle of a space mission project, from concept development to preliminary design, detailed design, development and operations. The benefits and utilities of the model, however, depend on the phase of the mission for which it is used. This is because of the difference in the key strategic decisions that support each mission phase. The focus of this paper is on describing the particular methods used for PRA modeling during the operational phase of a spacecraft by gleaning insight from recently conducted case studies on two operational Mars orbiters. During operations, the key decisions relate to the commands sent to the spacecraft for any kind of diagnostics, anomaly resolution, trajectory changes, or planning. Often, faults and failures occur in the parts of the spacecraft but are contained or mitigated before they can cause serious damage. The failure behavior of the system during operations provides valuable data for updating and adjusting the related PRA models that are built primarily based on historical failure data. The PRA models, in turn, provide insight into the effect of various faults or failures on the risk and failure drivers of the system and the likelihood of possible end case scenarios, thereby facilitating the decision making process during operations. This paper describes the process of adjusting PRA models based on observed spacecraft data, on one hand, and utilizing the models for insight into the future system behavior on the other hand. While PRA models are typically used as a decision aid during the design phase of a space mission, we advocate adjusting them based on the observed behavior of the spacecraft and utilizing them for decision support during the operations phase.

Multi-model-based interactive authoring environment for creating shareable medical knowledge.

PubMed

Ali, Taqdir; Hussain, Maqbool; Ali Khan, Wajahat; Afzal, Muhammad; Hussain, Jamil; Ali, Rahman; Hassan, Waseem; Jamshed, Arif; Kang, Byeong Ho; Lee, Sungyoung

2017-10-01

Technologically integrated healthcare environments can be realized if physicians are encouraged to use smart systems for the creation and sharing of knowledge used in clinical decision support systems (CDSS). While CDSSs are heading toward smart environments, they lack support for abstraction of technology-oriented knowledge from physicians. Therefore, abstraction in the form of a user-friendly and flexible authoring environment is required in order for physicians to create shareable and interoperable knowledge for CDSS workflows. Our proposed system provides a user-friendly authoring environment to create Arden Syntax MLM (Medical Logic Module) as shareable knowledge rules for intelligent decision-making by CDSS. Existing systems are not physician friendly and lack interoperability and shareability of knowledge. In this paper, we proposed Intelligent-Knowledge Authoring Tool (I-KAT), a knowledge authoring environment that overcomes the above mentioned limitations. Shareability is achieved by creating a knowledge base from MLMs using Arden Syntax. Interoperability is enhanced using standard data models and terminologies. However, creation of shareable and interoperable knowledge using Arden Syntax without abstraction increases complexity, which ultimately makes it difficult for physicians to use the authoring environment. Therefore, physician friendliness is provided by abstraction at the application layer to reduce complexity. This abstraction is regulated by mappings created between legacy system concepts, which are modeled as domain clinical model (DCM) and decision support standards such as virtual medical record (vMR) and Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). We represent these mappings with a semantic reconciliation model (SRM). The objective of the study is the creation of shareable and interoperable knowledge using a user-friendly and flexible I-KAT. Therefore we evaluated our system using completeness and user satisfaction criteria, which we assessed through the system- and user-centric evaluation processes. For system-centric evaluation, we compared the implementation of clinical information modelling system requirements in our proposed system and in existing systems. The results suggested that 82.05% of the requirements were fully supported, 7.69% were partially supported, and 10.25% were not supported by our system. In the existing systems, 35.89% of requirements were fully supported, 28.20% were partially supported, and 35.89% were not supported. For user-centric evaluation, the assessment criterion was 'ease of use'. Our proposed system showed 15 times better results with respect to MLM creation time than the existing systems. Moreover, on average, the participants made only one error in MLM creation using our proposed system, but 13 errors per MLM using the existing systems. We provide a user-friendly authoring environment for creation of shareable and interoperable knowledge for CDSS to overcome knowledge acquisition complexity. The authoring environment uses state-of-the-art decision support-related clinical standards with increased ease of use. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

Greenes, R A

1991-11-01

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