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.

What is a “good” treatment decision?: Decisional control, knowledge, treatment decision-making, and quality of life in men with clinically localized prostate cancer

PubMed Central

Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J.; Homish, D. Lynn

2016-01-01

Objective We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision-making is an advantageous model for studying patient treatment decision-making dynamics as there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Methods Men with newly diagnosed clinically localized prostate cancer (N=1529) completed measures of decisional control, prostate cancer knowledge, and their decision-making experience (decisional conflict, and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed 6-months after treatment. Results More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction, but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control predicted better QOL 6-months post-treatment. Conclusion Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. PMID:26957566

What Is a "Good" Treatment Decision? Decisional Control, Knowledge, Treatment Decision Making, and Quality of Life in Men with Clinically Localized Prostate Cancer.

PubMed

Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J; Homish, D Lynn

2016-08-01

We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision-making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision making is an advantageous model for studying patient treatment decision-making dynamics because there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Men with newly diagnosed clinically localized prostate cancer (N = 1529) completed measures of decisional control, prostate cancer knowledge, and decision-making experiences (decisional conflict and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed at 6 months after treatment. More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control, predicted better QOL 6 months after treatment. Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time that they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. © The Author(s) 2016.

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.

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 (...

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.

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.

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...

Towards ethical decision support and knowledge management in neonatal intensive care.

PubMed

Yang, L; Frize, M; Eng, P; Walker, R; Catley, C

2004-01-01

Recent studies in neonatal medicine, clinical nursing, and cognitive psychology have indicated the need to augment current decision-making practice in neonatal intensive care units with computerized, intelligent decision support systems. Rapid progress in artificial intelligence and knowledge management facilitates the design of collaborative ethical decision-support tools that allow clinicians to provide better support for parents facing inherently difficult choices, such as when to withdraw aggressive treatment. The appropriateness of using computers to support ethical decision-making is critically analyzed through research and literature review. In ethical dilemmas, multiple diverse participants need to communicate and function as a team to select the best treatment plan. In order to do this, physicians require reliable estimations of prognosis, while parents need a highly useable tool to help them assimilate complex medical issues and address their own value system. Our goal is to improve and structuralize the ethical decision-making that has become an inevitable part of modern neonatal care units. The paper contributes to clinical decision support by outlining the needs and basis for ethical decision support and justifying the proposed development efforts.

Home care decision support using an Arden engine--merging smart home and vital signs data.

PubMed

Marschollek, Michael; Bott, Oliver J; Wolf, Klaus-H; Gietzelt, Matthias; Plischke, Maik; Madiesh, Moaaz; Song, Bianying; Haux, Reinhold

2009-01-01

The demographic change with a rising proportion of very old people and diminishing resources leads to an intensification of the use of telemedicine and home care concepts. To provide individualized decision support, data from different sources, e.g. vital signs sensors and home environmental sensors, need to be combined and analyzed together. Furthermore, a standardized decision support approach is necessary. The aim of our research work is to present a laboratory prototype home care architecture that integrates data from different sources and uses a decision support system based on the HL7 standard Arden Syntax for Medical Logical Modules. Data from environmental sensors connected to a home bus system are stored in a data base along with data from wireless medical sensors. All data are analyzed using an Arden engine with the medical knowledge represented in Medical Logic Modules. Multi-modal data from four different sensors in the home environment are stored in a single data base and are analyzed using an HL7 standard conformant decision support system. Individualized home care decision support must be based on all data available, including context data from smart home systems and medical data from electronic health records. Our prototype implementation shows the feasibility of using an Arden engine for decision support in a home setting. Our future work will include the utilization of medical background knowledge for individualized decision support, as there is no one-size-fits-all knowledge base in medicine.

Decision Support and Shared Decision Making About Active Surveillance Versus Active Treatment Among Men Diagnosed with Low-Risk Prostate Cancer: a Pilot Study.

PubMed

Myers, Ronald E; Leader, Amy E; Censits, Jean Hoffman; Trabulsi, Edouard J; Keith, Scott W; Petrich, Anett M; Quinn, Anna M; Den, Robert B; Hurwitz, Mark D; Lallas, Costas D; Hegarty, Sarah E; Dicker, Adam P; Zeigler-Johnson, Charnita M; Giri, Veda N; Ayaz, Hasan; Gomella, Leonard G

2018-02-01

This study aimed to explore the effects of a decision support intervention (DSI) and shared decision making (SDM) on knowledge, perceptions about treatment, and treatment choice among men diagnosed with localized low-risk prostate cancer (PCa). At a multidisciplinary clinic visit, 30 consenting men with localized low-risk PCa completed a baseline survey, had a nurse-mediated online DS session to clarify preference for active surveillance (AS) or active treatment (AT), and met with clinicians for SDM. Participants also completed a follow-up survey at 30 days. We assessed change in treatment knowledge, decisional conflict, and perceptions and identified predictors of AS. At follow-up, participants exhibited increased knowledge (p < 0.001), decreased decisional conflict (p < 0.001), and more favorable perceptions of AS (p = 0.001). Furthermore, 25 of the 30 participants (83 %) initiated AS. Increased family and clinician support predicted this choice (p < 0.001). DSI/SDM prepared patients to make an informed decision. Perceived support of the decision facilitated patient choice of AS.

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.

Knowledge Requirements and Management in Expert Decision Support Systems for (Military) Situation Assessment

DTIC Science & Technology

1983-08-01

constitutes a fundamental problem in many decision making processes. In business management we face this problem when determining the status of an...Tehiical Report 576 ( 1 ) 4 KNOWLEDGE REQUIREMENTS AND MANAGEMENT IN EXPERT DECISION SUPPORT SYSTEMS FOR (MILITARY) SITUATION ASSESSMENT MOOM sen...accomplished under contract for the Department of the Army The Israel Institute of Business Research Technical review by Robert H. Sasmor Joseph M

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.

Why older adults make more immediate treatment decisions about cancer than younger adults.

PubMed

Meyer, Bonnie J F; Talbot, Andrew P; Ranalli, Carlee

2007-09-01

Literature relevant to medical decision making was reviewed, and a model was outlined for testing. Two studies examined whether older adults make more immediate decisions than younger adults about treatments for prostate or breast cancer in authentic scenarios. Findings clearly showed that older adults were more likely to make immediate decisions than younger adults. The research is important because it not only demonstrates the consistency of this age-related effect across disease domains, gender, ethnic groups, and prevalent education levels but begins to investigate a model to explain the effect. Major reasons for the effect focus on treatment knowledge, interest and engagement, and cognitive resources. Treatment knowledge, general cancer knowledge, interest, and cognitive resources relate to different ways of processing treatment information and preferences for immediate versus delayed decision making. Adults with high knowledge of treatments on a reliable test tended to make immediate treatment decisions, which supports the knowledge explanation. Adults with more cognitive resources and more interest tended to delay their treatment decisions. Little support was found for a cohort explanation for the relationship between age and preference for immediate medical decision making. (PsycINFO Database Record (c) 2007 APA, all rights reserved).

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-...

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.

Barriers, facilitators and views about next steps to implementing supports for evidence-informed decision-making in health systems: a qualitative study.

PubMed

Ellen, Moriah E; Léon, Grégory; Bouchard, Gisèle; Ouimet, Mathieu; Grimshaw, Jeremy M; Lavis, John N

2014-12-05

Mobilizing research evidence for daily decision-making is challenging for health system decision-makers. In a previous qualitative paper, we showed the current mix of supports that Canadian health-care organizations have in place and the ones that are perceived to be helpful to facilitate the use of research evidence in health system decision-making. Factors influencing the implementation of such supports remain poorly described in the literature. Identifying the barriers to and facilitators of different interventions is essential for implementation of effective, context-specific, supports for evidence-informed decision-making (EIDM) in health systems. The purpose of this study was to identify (a) barriers and facilitators to implementing supports for EIDM in Canadian health-care organizations, (b) views about emerging development of supports for EIDM, and (c) views about the priorities to bridge the gaps in the current mix of supports that these organizations have in place. This qualitative study was conducted in three types of health-care organizations (regional health authorities, hospitals, and primary care practices) in two Canadian provinces (Ontario and Quebec). Fifty-seven in-depth semi-structured telephone interviews were conducted with senior managers, library managers, and knowledge brokers from health-care organizations that have already undertaken strategic initiatives in knowledge translation. The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Limited resources (i.e., money or staff), time constraints, and negative attitudes (or resistance) toward change were the most frequently identified barriers to implementing supports for EIDM. Genuine interest from health system decision-makers, notably their willingness to invest money and resources and to create a knowledge translation culture over time in health-care organizations, was the most frequently identified facilitator to implementing supports for EIDM. The most frequently cited views about emerging development of supports for EIDM were implementing accessible and efficient systems to support the use of research in decision-making (e.g., documentation and reporting tools, communication tools, and decision support tools) and developing and implementing an infrastructure or position where the accountability for encouraging knowledge use lies. The most frequently stated priorities for bridging the gaps in the current mix of supports that these organizations have in place were implementing technical infrastructures to support research use and to ensure access to research evidence and establishing formal or informal ties to researchers and knowledge brokers outside the organization who can assist in EIDM. These results provide insights on the type of practical implementation imperatives involved in supporting EIDM.

Developing genomic knowledge bases and databases to support clinical management: current perspectives.

PubMed

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.

Developing genomic knowledge bases and databases to support clinical management: current perspectives

PubMed Central

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward. PMID:25276091

Decision support system for nursing management control

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

Ernst, C.J.

A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

Information/Knowledge Acquisition Methods for Decision Support Systems and Expert Systems.

ERIC Educational Resources Information Center

Yang, Heng-Li

1995-01-01

Compares information requirement-elicitation (IRE) methods for decision support systems (DSS) with knowledge acquisition (KA) methods for expert systems (ES) development. The definition and architectures of ES and DSS are compared and the systems' development cycles and IRE/KA methods are discussed. Differences are noted between ES and DSS…

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.

An innovative approach to addressing childhood obesity: a knowledge-based infrastructure for supporting multi-stakeholder partnership decision-making in Quebec, Canada.

PubMed

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L; Dubé, Laurette

2015-01-23

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a "portrait", which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity.

An Innovative Approach to Addressing Childhood Obesity: A Knowledge-Based Infrastructure for Supporting Multi-Stakeholder Partnership Decision-Making in Quebec, Canada

PubMed Central

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L.; Dubé, Laurette

2015-01-01

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a “portrait”, which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity. PMID:25625409

Applying evidence to support ethical decisions: is the placebo really powerless?.

PubMed

Porzsolt, Franz; Schlotz-Gorton, Nicole; Biller-Andorno, Nikola; Thim, Anke; Meissner, Karin; Roeckl-Wiedmann, Irmgard; Herzberger, Barbara; Ziegler, Renatus; Gaus, Wilhelm; Pöppe, Ernst

2004-01-01

Using placebos in day-to-day practice is an ethical problem. This paper summarises the available epidemiological evidence to support this difficult decision. Based on these data we propose to differentiate between placebo and "knowledge framing". While the use of placebo should be confined to experimental settings in clinical trials, knowledge framing--which is only conceptually different from placebo--is a desired, expected and necessary component of any doctor-patient encounter. Examples from daily practice demonstrate both, the need to investigate the effects of knowledge framing and its impact on ethical, medical, economical and legal decisions.

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.

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles.

PubMed

Horne, Avril C; Szemis, Joanna M; Webb, J Angus; Kaur, Simranjit; Stewardson, Michael J; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles

NASA Astrophysics Data System (ADS)

Horne, Avril C.; Szemis, Joanna M.; Webb, J. Angus; Kaur, Simranjit; Stewardson, Michael J.; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

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.

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 Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

PubMed

Abidi, Samina

2017-10-26

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.

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.

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.

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.

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.

Biomedical Ontologies in Action: Role in Knowledge Management, Data Integration and Decision Support

PubMed Central

Bodenreider, O.

2008-01-01

Summary Objectives To provide typical examples of biomedical ontologies in action, emphasizing the role played by biomedical ontologies in knowledge management, data integration and decision support. Methods Biomedical ontologies selected for their practical impact are examined from a functional perspective. Examples of applications are taken from operational systems and the biomedical literature, with a bias towards recent journal articles. Results The ontologies under investigation in this survey include SNOMED CT, the Logical Observation Identifiers, Names, and Codes (LOINC), the Foundational Model of Anatomy, the Gene Ontology, RxNorm, the National Cancer Institute Thesaurus, the International Classification of Diseases, the Medical Subject Headings (MeSH) and the Unified Medical Language System (UMLS). The roles played by biomedical ontologies are classified into three major categories: knowledge management (indexing and retrieval of data and information, access to information, mapping among ontologies); data integration, exchange and semantic interoperability; and decision support and reasoning (data selection and aggregation, decision support, natural language processing applications, knowledge discovery). Conclusions Ontologies play an important role in biomedical research through a variety of applications. While ontologies are used primarily as a source of vocabulary for standardization and integration purposes, many applications also use them as a source of computable knowledge. Barriers to the use of ontologies in biomedical applications are discussed. PMID:18660879

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.

A Synthesis Of Knowledge About Caregiver Decision Making Finds Gaps In Support For Those Who Care For Aging Loved Ones.

PubMed

Garvelink, Mirjam M; Ngangue, Patrice A G; Adekpedjou, Rheda; Diouf, Ndeye T; Goh, Larissa; Blair, Louisa; Légaré, France

2016-04-01

We conducted a mixed-methods knowledge synthesis to assess the effectiveness of interventions to improve caregivers' involvement in decision making with seniors, and to describe caregivers' experiences of decision making in the absence of interventions. We analyzed forty-nine qualitative, fourteen quantitative, and three mixed-methods studies. The qualitative studies indicated that caregivers had unmet needs for information, discussions of values and needs, and decision support, which led to negative sentiments after decision making. Our results indicate that there have been insufficient quantitative evaluations of interventions to involve caregivers in decision making with seniors and that the evaluations that do exist found few clinically significant effects. Elements of usual care that received positive evaluations were the availability of a decision coach and a supportive decision-making environment. Additional rigorously evaluated interventions are needed to help caregivers be more involved in decision making with seniors. Project HOPE—The People-to-People Health Foundation, Inc.

The experience of physicians in pharmacogenomic clinical decision support within eight German university hospitals.

PubMed

Hinderer, Marc; Boeker, Martin; Wagner, Sebastian A; Binder, Harald; Ückert, Frank; Newe, Stephanie; Hülsemann, Jan L; Neumaier, Michael; Schade-Brittinger, Carmen; Acker, Till; Prokosch, Hans-Ulrich; Sedlmayr, Brita

2017-06-01

The aim of this study was to assess the physicians' attitude, their knowledge and their experience in pharmacogenomic clinical decision support in German hospitals. We conducted an online survey to address physicians of 13 different medical specialties across eight German university hospitals. In total, 564 returned questionnaires were analyzed. The remaining knowledge gap, the uncertainty of test reimbursement and the physicians' lack of awareness of existing pharmacogenomic clinical decision support systems (CDSS) are the major barriers for implementing pharmacogenomic CDSS into German hospitals. Furthermore, pharmacogenomic CDSS are most effective in the form of real-time decision support for internists. Physicians in German hospitals require additional education of both genetics and pharmacogenomics. They need to be provided with access to relevant pharmacogenomic CDSS.

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.

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.

Modelling Situation Awareness Information for Naval Decision Support Design

DTIC Science & Technology

2003-10-01

Modelling Situation Awareness Information for Naval Decision Support Design Dr.-Ing. Bernhard Doering, Dipl.-Ing. Gert Doerfel, Dipl.-Ing... knowledge -based user interfaces. For developing such interfaces information of the three different SA levels which operators need in performing their...large scale on situation awareness of operators which is defined as the state of operator knowledge about the external environment resulting from

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.

Better Decisions through Consultation and Collaboration

EPA Pesticide Factsheets

This manual discusses the benefits of public involvement to agency decision makers, including expanding shared baseline knowledge, generating support for the decision, and developing ongoing relationships that will help in implementing decisions.

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.

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.

A knowledge infrastructure for occupational safety and health.

PubMed

van Dijk, Frank J H; Verbeek, Jos H; Hoving, Jan L; Hulshof, Carel T J

2010-12-01

Occupational Safety and Health (OSH) professionals should use scientific evidence to support their decisions in policy and practice. Although examples from practice show that progress has been made in evidence-based decision making, there is a challenge to improve and extend the facilities that support knowledge translation in practice. A knowledge infrastructure that supports OSH practice should include scientific research, systematic reviews, practice guidelines, and other tools for professionals such as well accessible virtual libraries and databases providing knowledge, quality tools, and good learning materials. A good infrastructure connects facilities with each other and with practice. Training and education is needed for OSH professionals in the use of evidence to improve effectiveness and efficiency. New initiatives show that occupational health can profit from intensified international collaboration to establish a good functioning knowledge infrastructure.

Systematic review of the empirical investigation of resources to support decision-making regarding BRCA1 and BRCA2 genetic testing in women with breast cancer.

PubMed

Grimmett, Chloe; Pickett, Karen; Shepherd, Jonathan; Welch, Karen; Recio-Saucedo, Alejandra; Streit, Elke; Seers, Helen; Armstrong, Anne; Cutress, Ramsey I; Evans, D Gareth; Copson, Ellen; Meiser, Bettina; Eccles, Diana; Foster, Claire

2018-05-01

Identify existing resources developed and/or evaluated empirically in the published literature designed to support women with breast cancer making decisions regarding genetic testing for BRCA1/2 mutations. Systematic review of seven electronic databases. Studies were included if they described or evaluated resources that were designed to support women with breast cancer in making a decision to have genetic counselling or testing for familial breast cancer. Outcome and process evaluations, using any type of study design, as well as articles reporting the development of decision aids, were eligible for inclusion. Total of 9 publications, describing 6 resources were identified. Resources were effective at increasing knowledge or understanding of hereditary breast cancer. Satisfaction with resources was high. There was no evidence that any resource increased distress, worry or decisional conflict. Few resources included active functionalities for example, values-based exercises, to support decision-making. Tailored resources supporting decision-making may be helpful and valued by patients and increase knowledge of hereditary breast cancer, without causing additional distress. Clinicians should provide supportive written information to patients where it is available. However, there is a need for robustly developed decision tools to support decision-making around genetic testing in women with breast cancer. Copyright © 2017 Elsevier B.V. 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

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

Use of Indigenous Knowledge in Environmental Decision-Making by Communities in the Kumaon Himalayas

ERIC Educational Resources Information Center

Honwad, Sameer

2010-01-01

This study is designed to find out how people in rural communities residing in the middle Himalayas use indigenous knowledge to support environmental decisions while addressing water and land use related concerns. The study not only serves to enrich our understanding of community decision-making, especially as connected to land use and ecological…

Boundary work for implementing adaptive management: A water sector application.

PubMed

Adem Esmail, Blal; Geneletti, Davide; Albert, Christian

2017-09-01

Boundary work, defined as effort to mediate between knowledge and action, is a promising approach for facilitating knowledge co-production for sustainable development. Here, we investigate a case study of knowledge co-production, to assess the applicability of boundary work as a conceptual framework to support implementing adaptive management in the water sector. We refer to a boundary work classification recently proposed by Clark et al., (2016), based on three types of knowledge uses, i.e. enlightenment, decision-, and negotiation-support, and three types of sources, i.e. personal expertise, single, and multiple communities of expertise. Our empirical results confirm boundary work has been crucial for the three types of knowledge use. For enlightenment and decision-support, effective interaction among knowledge producers and users was achieved through diverse boundary work practices, including joint agenda setting, and sharing of data and expertise. This initial boundary work eased subsequent knowledge co-production for decision-support and negotiations, in combination with stepping up of cooperation between relevant actors, suitable legislation and pressure for problem solving. Our analysis highlighted the temporal dimension matters - building trust around enlightenment first, and then using this as a basis for managing knowledge co-production for decision-, and negotiation support. We reconfirmed that boundary work is not a single time achievement, rather is a dynamic process, and we emphasized the importance of key actors driving the process, such as water utilities. Our results provide a rich case study of how strategic boundary work can facilitate knowledge co-production for adaptive management in the water sector. The boundary work practices employed here could also be transferred to other cases. Water utilities, as intermediaries between providers and beneficiaries of the important water-related ecosystem service of clean water provision, can indeed serve as key actors for initiating such boundary work practices. Copyright © 2017 Elsevier B.V. All rights reserved.

Implementing interactive decision support: A case for combining cyberinfrastructure, data fusion, and social process to mobilize scientific knowledge in sustainability problems

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2014-12-01

Geosciences are becoming increasingly data intensive, particularly in relation to sustainability problems, which are multi-dimensional, weakly structured and characterized by high levels of uncertainty. In the case of complex resource management problems, the challenge is to extract meaningful information from data and make sense of it. Simultaneously, scientific knowledge alone is insufficient to change practice. Creating tools, and group decision support processes for end users to interact with data are key challenges to transforming science-based information into actionable knowledge. The ENCOMPASS project began as a multi-year case study in the Atacama Desert of Chile to design and implement a knowledge transfer model for energy-water-mining conflicts in the region. ENCOMPASS combines the use of cyberinfrastructure (CI), automated data collection, interactive interfaces for dynamic decision support, and participatory modelling to support social learning. A pilot version of the ENCOMPASS CI uses open source systems and serves as a structure to integrate and store multiple forms of data and knowledge, such as DEM, meteorological, water quality, geomicrobiological, energy demand, and groundwater models. In the case study, informatics and data fusion needs related to scientific uncertainty around deep groundwater flowpaths and energy-water connections. Users may upload data from field sites with handheld devices or desktops. Once uploaded, data assets are accessible for a variety of uses. To address multi-attributed decision problems in the Atacama region a standalone application with touch-enabled interfaces was created to improve real-time interactions with datasets by groups. The tool was used to merge datasets from the ENCOMPASS CI to support exploration among alternatives and build shared understanding among stakeholders. To date, the project has increased technical capacity among stakeholders, resulted in the creation of both for-profit and non-profit entities, enabled cross-sector collaboration with mining-indigenous stakeholders, and produced an interactive application for group decision support. ENCOMPASS leverages advances in computational tools to deliver data and models for group decision support applied to sustainability science problems.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

PubMed

Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally

2017-10-02

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Evidence and Obesity Prevention: Developing Evidence Summaries to Support Decision Making

ERIC Educational Resources Information Center

Clark, Rachel; Waters, Elizabeth; Armstrong, Rebecca; Conning, Rebecca; Allender, Steven; Swinburn, Boyd

2013-01-01

Public health practitioners make decisions based on research evidence in combination with a variety of other influences. Evidence summaries are one of a range of knowledge translation options used to support evidence-informed decision making. The literature relevant to obesity prevention requires synthesis for it to be accessible and relevant to…

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 integrated strategy of knowledge application for optimal e-health implementation: A multi-method study protocol

PubMed Central

Gagnon, Marie-Pierre; Légaré, France; Fortin, Jean-Paul; Lamothe, Lise; Labrecque, Michel; Duplantie, Julie

2008-01-01

Background E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system. Methods A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels. Results This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects. Conclusion These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must. PMID:18435853

Situationally-Sensitive Knowledge Translation and Relational Decision Making in Hyperacute Stroke: A Qualitative Study

PubMed Central

Murtagh, Madeleine J.; Burges Watson, Duika L.; Jenkings, K. Neil; Lie, Mabel L. S.; Mackintosh, Joan E.; Ford, Gary A.; Thomson, Richard G.

2012-01-01

Stroke is a leading cause of disability. Early treatment of acute ischaemic stroke with rtPA reduces the risk of longer term dependency but carries an increased risk of causing immediate bleeding complications. To understand the challenges of knowledge translation and decision making about treatment with rtPA in hyperacute stroke and hence to inform development of appropriate decision support we interviewed patients, their family and health professionals. The emergency setting and the symptomatic effects of hyper-acute stroke shaped the form, content and manner of knowledge translation to support decision making. Decision making about rtPA in hyperacute stroke presented three conundrums for patients, family and clinicians. 1) How to allow time for reflection in a severely time-limited setting. 2) How to facilitate knowledge translation regarding important treatment risks and benefits when patient and family capacity is blunted by the effects and shock of stroke. 3) How to ensure patient and family views are taken into account when the situation produces reliance on the expertise of clinicians. Strategies adopted to meet these conundrums were fourfold: face to face communication; shaping decisions; incremental provision of information; and communication tailored to the individual patient. Relational forms of interaction were understood to engender trust and allay anxiety. Shaping decisions with patients was understood as an expression of confidence by clinicians that helped alleviate anxiety and offered hope and reassurance to patients and their family experiencing the shock of the stroke event. Neutral presentations of information and treatment options promoted uncertainty and contributed to anxiety. ‘Drip feeding’ information created moments for reflection: clinicians literally made time. Tailoring information to the particular patient and family situation allowed clinicians to account for social and emotional contexts. The principal responses to the challenges of decision making about rtPA in hyperacute stroke were relational decision support and situationally-sensitive knowledge translation. PMID:22675477

Situationally-sensitive knowledge translation and relational decision making in hyperacute stroke: a qualitative study.

PubMed

Murtagh, Madeleine J; Burges Watson, Duika L; Jenkings, K Neil; Lie, Mabel L S; Mackintosh, Joan E; Ford, Gary A; Thomson, Richard G

2012-01-01

Stroke is a leading cause of disability. Early treatment of acute ischaemic stroke with rtPA reduces the risk of longer term dependency but carries an increased risk of causing immediate bleeding complications. To understand the challenges of knowledge translation and decision making about treatment with rtPA in hyperacute stroke and hence to inform development of appropriate decision support we interviewed patients, their family and health professionals. The emergency setting and the symptomatic effects of hyper-acute stroke shaped the form, content and manner of knowledge translation to support decision making. Decision making about rtPA in hyperacute stroke presented three conundrums for patients, family and clinicians. 1) How to allow time for reflection in a severely time-limited setting. 2) How to facilitate knowledge translation regarding important treatment risks and benefits when patient and family capacity is blunted by the effects and shock of stroke. 3) How to ensure patient and family views are taken into account when the situation produces reliance on the expertise of clinicians. Strategies adopted to meet these conundrums were fourfold: face to face communication; shaping decisions; incremental provision of information; and communication tailored to the individual patient. Relational forms of interaction were understood to engender trust and allay anxiety. Shaping decisions with patients was understood as an expression of confidence by clinicians that helped alleviate anxiety and offered hope and reassurance to patients and their family experiencing the shock of the stroke event. Neutral presentations of information and treatment options promoted uncertainty and contributed to anxiety. 'Drip feeding' information created moments for reflection: clinicians literally made time. Tailoring information to the particular patient and family situation allowed clinicians to account for social and emotional contexts. The principal responses to the challenges of decision making about rtPA in hyperacute stroke were relational decision support and situationally-sensitive knowledge translation.

Tools to support evidence-informed public health decision making

PubMed Central

2014-01-01

Background Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. Methods As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Results Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the ‘actionable message(s)’ from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing and sustaining evidence-informed decision making. Conclusion Tools are available to support the process of evidence-informed decision making among public health professionals. The usability and usefulness of these tools for advancing and sustaining evidence-informed decision making are discussed, including recommendations for the tools’ application in other public health settings beyond this study. Knowledge and awareness of these tools may assist other health professionals in their efforts to implement evidence-informed practice. PMID:25034534

Tools to support evidence-informed public health decision making.

PubMed

Yost, Jennifer; Dobbins, Maureen; Traynor, Robyn; DeCorby, Kara; Workentine, Stephanie; Greco, Lori

2014-07-18

Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the 'actionable message(s)' from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing and sustaining evidence-informed decision making. Tools are available to support the process of evidence-informed decision making among public health professionals. The usability and usefulness of these tools for advancing and sustaining evidence-informed decision making are discussed, including recommendations for the tools' application in other public health settings beyond this study. Knowledge and awareness of these tools may assist other health professionals in their efforts to implement evidence-informed practice.

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.

Automating Guidelines for Clinical Decision Support: Knowledge Engineering and Implementation.

PubMed

Tso, Geoffrey J; Tu, Samson W; Oshiro, Connie; Martins, Susana; Ashcraft, Michael; Yuen, Kaeli W; Wang, Dan; Robinson, Amy; Heidenreich, Paul A; Goldstein, Mary K

2016-01-01

As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al. 5 identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology.

Shared Decision Making for Better Schools.

ERIC Educational Resources Information Center

Brost, Paul

2000-01-01

Delegating decision making to those closest to implementation can result in better decisions, more support for improvement initiatives, and increased student performance. Shared decision making depends on capable school leadership, a professional community, instructional guidance mechanisms, knowledge and skills, information sharing, power, and…

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.

Supporting end of life decision making: Case studies of relational closeness in supported decision making for people with severe or profound intellectual disability.

PubMed

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-11-01

The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions. Five people with severe or profound intellectual disability's experiences of supported decision making were examined. This article is particularly focused on one participant's experiences at the end of his life. All five case studies identified that supporters were most effective in providing decision-making support for participants when they were relationally close to the person and had knowledge of the person's life story, particularly in relation to events that demonstrated preference. Findings from this study provide new understandings of supported decision making for people with severe or profound intellectual disability and have particular relevance for supporting decision making at the end of life. © 2017 John Wiley & Sons Ltd.

Augmenting communication and decision making in the intensive care unit with a cardiopulmonary resuscitation video decision support tool: a temporal intervention study.

PubMed

McCannon, Jessica B; O'Donnell, Walter J; Thompson, B Taylor; El-Jawahri, Areej; Chang, Yuchiao; Ananian, Lillian; Bajwa, Ednan K; Currier, Paul F; Parikh, Mihir; Temel, Jennifer S; Cooper, Zara; Wiener, Renda Soylemez; Volandes, Angelo E

2012-12-01

Effective communication between intensive care unit (ICU) providers and families is crucial given the complexity of decisions made regarding goals of therapy. Using video images to supplement medical discussions is an innovative process to standardize and improve communication. In this six-month, quasi-experimental, pre-post intervention study we investigated the impact of a cardiopulmonary resuscitation (CPR) video decision support tool upon knowledge about CPR among surrogate decision makers for critically ill adults. We interviewed surrogate decision makers for patients aged 50 and over, using a structured questionnaire that included a four-question CPR knowledge assessment similar to those used in previous studies. Surrogates in the post-intervention arm viewed a three-minute video decision support tool about CPR before completing the knowledge assessment and completed questions about perceived value of the video. We recruited 23 surrogates during the first three months (pre-intervention arm) and 27 surrogates during the latter three months of the study (post-intervention arm). Surrogates viewing the video had more knowledge about CPR (p=0.008); average scores were 2.0 (SD 1.1) and 2.9 (SD 1.2) (out of a total of 4) in pre-intervention and post-intervention arms. Surrogates who viewed the video were comfortable with its content (81% very) and 81% would recommend the video. CPR preferences for patients at the time of ICU discharge/death were distributed as follows: pre-intervention: full code 78%, DNR 22%; post-intervention: full code 59%, DNR 41% (p=0.23).

Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

PubMed

Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

2014-01-01

The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

PubMed

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.

Effects of a decision support intervention on decisional conflict associated with microsatellite instability testing.

PubMed

Hall, Michael J; Manne, Sharon L; Winkel, Gary; Chung, Daniel S; Weinberg, David S; Meropol, Neal J

2011-02-01

Decision support to facilitate informed consent is increasingly important for complicated medical tests. Here, we test a theoretical model of factors influencing decisional conflict in a study examining the effects of a decision support aid that was designed to assist patients at high risk for hereditary nonpolyposis colorectal cancer (CRC) deciding whether to pursue the microsatellite instability (MSI) test. Participants were 239 CRC patients at high familial risk for a genetic mutation who completed surveys before and after exposure to the intervention. Half of the sample was assigned to the CD-ROM aid and half received a brief description of the test. Structural equation modeling was employed to examine associations among the intervention, knowledge, pros and cons to having MSI testing, self-efficacy, preparedness, and decisional conflict. The goodness of fit for the model was acceptable [FIML, full information maximum likelihood, χ(2) (df = 280) = 392.24; P = 0.00]. As expected, the paths to decisional conflict were significant for postintervention pros of MSI testing (t = -2.43; P < 0.05), cons of MSI testing (t = 2.78; P < 0.05), and preparedness (t = -7.27; P < 0.01). The intervention impacted decisional conflict by increasing knowledge about the MSI test and knowledge exerted its effects on decisional conflict by increasing preparedness to make a decision about the test and by increases in perceived benefits of having the test. Increasing knowledge, preparedness, and perceived benefits of undergoing the MSI test facilitate informed decision making for this test. Understanding mechanisms underlying health decisions is critical for improving decisional support. Individuals with Lynch syndrome have an elevated lifetime risk of CRC. Risk of Lynch syndrome may be assessed with a tumor-based screening test (MSI testing or immunohistochemical tissue staining). ©2011 AACR.

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 national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine.

PubMed

Kawamoto, Kensaku; Lobach, David F; Willard, Huntington F; Ginsburg, Geoffrey S

2009-03-23

In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs. Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government. A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.

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.

The conceptual foundation of environmental decision support.

PubMed

Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

2015-05-01

Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

Emergency physicians' attitudes and preferences regarding computed tomography, radiation exposure, and imaging decision support.

PubMed

Griffey, Richard T; Jeffe, Donna B; Bailey, Thomas

2014-07-01

Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians' (EPs') preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. A 42-item, Web-based survey of EPs was developed and used to measure EPs' attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach's alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient's cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients' cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients' cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs' greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP's decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. © 2014 by the Society for Academic Emergency Medicine.

Emergency Physicians’ Attitudes and Preferences Regarding Computed Tomography, Radiation Exposure, and Imaging Decision Support

PubMed Central

Griffey, Richard T.; Jeffe, Donna B.; Bailey, Thomas

2014-01-01

Objectives Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians’ (EPs’) preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. Methods A 42-item, Web-based survey of EPs was developed and used to measure EPs’ attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach’s alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Results Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient’s cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients’ cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients’ cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs’ greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP’s decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Conclusions Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. PMID:25125272

The integration of quantitative information with an intelligent decision support system for residential energy retrofits

NASA Astrophysics Data System (ADS)

Mo, Yunjeong

The purpose of this research is to support the development of an intelligent Decision Support System (DSS) by integrating quantitative information with expert knowledge in order to facilitate effective retrofit decision-making. To achieve this goal, the Energy Retrofit Decision Process Framework is analyzed. Expert system shell software, a retrofit measure cost database, and energy simulation software are needed for developing the DSS; Exsys Corvid, the NREM database and BEopt were chosen for implementing an integration model. This integration model demonstrates the holistic function of a residential energy retrofit system for existing homes, by providing a prioritized list of retrofit measures with cost information, energy simulation and expert advice. The users, such as homeowners and energy auditors, can acquire all of the necessary retrofit information from this unified system without having to explore several separate systems. The integration model plays the role of a prototype for the finalized intelligent decision support system. It implements all of the necessary functions for the finalized DSS, including integration of the database, energy simulation and expert knowledge.

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).

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.

Neuro-Fuzzy Support of Knowledge Management in Social Regulation

NASA Astrophysics Data System (ADS)

Petrovic-Lazarevic, Sonja; Coghill, Ken; Abraham, Ajith

2002-09-01

The aim of the paper is to demonstrate the neuro-fuzzy support of knowledge management in social regulation. Knowledge could be understood for social regulation purposes as explicit and tacit. Explicit knowledge relates to the community culture indicating how things work in the community based on social policies and procedures. Tacit knowledge is ethics and norms of the community. The former could be codified, stored and transferable in order to support decision making, while the latter being based on personal knowledge, experience and judgments is difficult to codify and store. Tacit knowledge expressed through linguistic information can be stored and used to support knowledge management in social regulation through the application of fuzzy and neuro-fuzzy logic.

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.

Knowledge as a Service at the Point of Care.

PubMed

Shellum, Jane L; Freimuth, Robert R; Peters, Steve G; Nishimura, Rick A; Chaudhry, Rajeev; Demuth, Steve J; Knopp, Amy L; Miksch, Timothy A; Milliner, Dawn S

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources.

Knowledge as a Service at the Point of Care

PubMed Central

Shellum, Jane L.; Freimuth, Robert R.; Peters, Steve G.; Nishimura, Rick A.; Chaudhry, Rajeev; Demuth, Steve J.; Knopp, Amy L.; Miksch, Timothy A.; Milliner, Dawn S.

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources. PMID:28269911

A gaze through the lens of decision theory toward knowledge translation science.

PubMed

Bucknall, Tracey

2007-01-01

Research findings become evidence when an individual decides that the information is relevant and useful to a particular circumstance. Prior to that point, they are unrelated facts. For research translation to occur, research evidence needs filtering, interpretation, and application by individuals to the specific situation. For this reason, decision science is complementary to knowledge translation science. Both aim to support the individual in deciding the most appropriate action in a dynamic environment where there are masses of uncensored and nonprioritized information readily available. Decision science employs research theories to study the cognitive processes underpinning the filtering and integration of current scientific information into changing contexts. Two meta-theories, coherence and correspondence theories, have been used to provide alternative views and prompt significant debate to advance the science. The aim of this article is to stimulate debate about the relationship between decision theory and knowledge translation. Discussed is the critical role of cognition in clinical decision making, with a focus on knowledge translation. A critical commentary of the knowledge utilization modeling papers is presented from a decision science perspective. The article concludes with a discussion on the implications for knowledge translation when viewed through the lens of decision science.

Implementation of workflow engine technology to deliver basic clinical decision support functionality

PubMed Central

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364

Making Just Tenure and Promotion Decisions Using the Objective Knowledge Growth Framework

ERIC Educational Resources Information Center

Chitpin, Stephanie

2015-01-01

Purpose: The purpose of this paper is to utilize the Objective Knowledge Growth Framework (OKGF) to promote a better understanding of the evaluating tenure and promotion processes. Design/Methodology/Approach: A scenario is created to illustrate the concept of using OKGF. Findings: The framework aims to support decision makers in identifying the…

Evaluating the effectiveness of the Emergency Neurological Life Support educational framework in low-income countries

PubMed Central

McCredie, Victoria A; Shrestha, Gentle S; Acharya, Subhash; Bellini, Antonio; Singh, Jeffrey M; Hemphill, J Claude; Goffi, Alberto

2018-01-01

Abstract Background The Emergency Neurological Life Support (ENLS) is an educational initiative designed to improve the acute management of neurological injuries. However, the applicability of the course in low-income countries in unknown. We evaluated the impact of the course on knowledge, decision-making skills and preparedness to manage neurological emergencies in a resource-limited country. Methods A prospective cohort study design was implemented for the first ENLS course held in Asia. Knowledge and decision-making skills for neurological emergencies were assessed at baseline, post-course and at 6 months following course completion. To determine perceived knowledge and preparedness, data were collected using surveys administered immediately post-course and 6 months later. Results A total of 34 acute care physicians from across Nepal attended the course. Knowledge and decision-making skills significantly improved following the course (p=0.0008). Knowledge and decision-making skills remained significantly improved after 6 months, compared with before the course (p=0.02), with no significant loss of skills immediately following the course to the 6-month follow-up (p=0.16). At 6 months, the willingness to participate in continuing medical education activities remained evident, with 77% (10/13) of participants reporting a change in their clinical practice and decision-making, with the repeated use of ENLS protocols as the main driver of change. Conclusions Using the ENLS framework, neurocritical care education can be delivered in low-income countries to improve knowledge uptake, with evidence of knowledge retention up to 6 months. PMID:29506188

A study of diverse clinical decision support rule authoring environments and requirements for integration

PubMed Central

2012-01-01

Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting. PMID:23145874

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.

How can knowledge exchange portals assist in knowledge management for evidence-informed decision making in public health?

PubMed Central

2014-01-01

Background Knowledge exchange portals are emerging as web tools that can help facilitate knowledge management in public health. We conducted a review to better understand the nature of these portals and their contribution to knowledge management in public health, with the aim of informing future development of portals in this field. Methods A systematic literature search was conducted of the peer-reviewed and grey literature to identify articles that described the design, development or evaluation of Knowledge Exchange Portals KEPs in the public health field. The content of the articles was analysed, interpreted and synthesised in light of the objectives of the review. Results The systematic search yielded 2223 articles, of which fifteen were deemed eligible for review, including eight case studies, six evaluation studies and one commentary article. Knowledge exchange portals mainly included design features to support knowledge access and creation, but formative evaluation studies examining user needs suggested collaborative features supporting knowledge exchange would also be useful. Overall web usage statistics revealed increasing use of some of these portals over time; however difficulties remain in retaining users. There is some evidence to suggest that the use of a knowledge exchange portal in combination with tailored and targeted messaging can increase the use of evidence in policy and program decision making at the organisational level. Conclusions Knowledge exchange portals can be a platform for providing integrated access to relevant content and resources in one location, for sharing and distributing information and for bringing people together for knowledge exchange. However more performance evaluation studies are needed to determine how they can best support evidence-informed decision making in public health. PMID:24884530

How can knowledge exchange portals assist in knowledge management for evidence-informed decision making in public health?

PubMed

Quinn, Emma; Huckel-Schneider, Carmen; Campbell, Danielle; Seale, Holly; Milat, Andrew J

2014-05-12

Knowledge exchange portals are emerging as web tools that can help facilitate knowledge management in public health. We conducted a review to better understand the nature of these portals and their contribution to knowledge management in public health, with the aim of informing future development of portals in this field. A systematic literature search was conducted of the peer-reviewed and grey literature to identify articles that described the design, development or evaluation of Knowledge Exchange Portals KEPs in the public health field. The content of the articles was analysed, interpreted and synthesised in light of the objectives of the review. The systematic search yielded 2223 articles, of which fifteen were deemed eligible for review, including eight case studies, six evaluation studies and one commentary article. Knowledge exchange portals mainly included design features to support knowledge access and creation, but formative evaluation studies examining user needs suggested collaborative features supporting knowledge exchange would also be useful. Overall web usage statistics revealed increasing use of some of these portals over time; however difficulties remain in retaining users. There is some evidence to suggest that the use of a knowledge exchange portal in combination with tailored and targeted messaging can increase the use of evidence in policy and program decision making at the organisational level. Knowledge exchange portals can be a platform for providing integrated access to relevant content and resources in one location, for sharing and distributing information and for bringing people together for knowledge exchange. However more performance evaluation studies are needed to determine how they can best support evidence-informed decision making in public health.

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.

Web-Based Versus Usual Care and Other Formats of Decision Aids to Support Prostate Cancer Screening Decisions: Systematic Review and Meta-Analysis.

PubMed

Baptista, Sofia; Teles Sampaio, Elvira; Heleno, Bruno; Azevedo, Luís Filipe; Martins, Carlos

2018-06-26

Prostate cancer is a leading cause of cancer among men. Because screening for prostate cancer is a controversial issue, many experts in the field have defended the use of shared decision making using validated decision aids, which can be presented in different formats (eg, written, multimedia, Web). Recent studies have concluded that decision aids improve knowledge and reduce decisional conflict. This meta-analysis aimed to investigate the impact of using Web-based decision aids to support men's prostate cancer screening decisions in comparison with usual care and other formats of decision aids. We searched PubMed, CINAHL, PsycINFO, and Cochrane CENTRAL databases up to November 2016. This search identified randomized controlled trials, which assessed Web-based decision aids for men making a prostate cancer screening decision and reported quality of decision-making outcomes. Two reviewers independently screened citations for inclusion criteria, extracted data, and assessed risk of bias. Using a random-effects model, meta-analyses were conducted pooling results using mean differences (MD), standardized mean differences (SMD), and relative risks (RR). Of 2406 unique citations, 7 randomized controlled trials met the inclusion criteria. For risk of bias, selective outcome reporting and participant/personnel blinding were mostly rated as unclear due to inadequate reporting. Based on seven items, two studies had high risk of bias for one item. Compared to usual care, Web-based decision aids increased knowledge (SMD 0.46; 95% CI 0.18-0.75), reduced decisional conflict (MD -7.07%; 95% CI -9.44 to -4.71), and reduced the practitioner control role in the decision-making process (RR 0.50; 95% CI 0.31-0.81). Web-based decision aids compared to printed decision aids yielded no differences in knowledge, decisional conflict, and participation in decision or screening behaviors. Compared to video decision aids, Web-based decision aids showed lower average knowledge scores (SMD -0.50; 95% CI -0.88 to -0.12) and a slight decrease in prostate-specific antigen screening (RR 1.12; 95% CI 1.01-1.25). According to this analysis, Web-based decision aids performed similarly to alternative formats (ie, printed, video) for the assessed decision-quality outcomes. The low cost, readiness, availability, and anonymity of the Web can be an advantage for increasing access to decision aids that support prostate cancer screening decisions among men. ©Sofia Baptista, Elvira Teles Sampaio, Bruno Heleno, Luís Filipe Azevedo, Carlos Martins. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.06.2018.

Computerization of guidelines: a knowledge specification method to convert text to detailed decision tree for electronic implementation.

PubMed

Aguirre-Junco, Angel-Ricardo; Colombet, Isabelle; Zunino, Sylvain; Jaulent, Marie-Christine; Leneveut, Laurence; Chatellier, Gilles

2004-01-01

The initial step for the computerization of guidelines is the knowledge specification from the prose text of guidelines. We describe a method of knowledge specification based on a structured and systematic analysis of text allowing detailed specification of a decision tree. We use decision tables to validate the decision algorithm and decision trees to specify and represent this algorithm, along with elementary messages of recommendation. Edition tools are also necessary to facilitate the process of validation and workflow between expert physicians who will validate the specified knowledge and computer scientist who will encode the specified knowledge in a guide-line model. Applied to eleven different guidelines issued by an official agency, the method allows a quick and valid computerization and integration in a larger decision support system called EsPeR (Personalized Estimate of Risks). The quality of the text guidelines is however still to be developed further. The method used for computerization could help to define a framework usable at the initial step of guideline development in order to produce guidelines ready for electronic implementation.

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.

A Decision Support System for Predicting Students' Performance

ERIC Educational Resources Information Center

Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis

2016-01-01

Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…

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.

Fuzzy-Arden-Syntax-based, Vendor-agnostic, Scalable Clinical Decision Support and Monitoring Platform.

PubMed

Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea

2015-01-01

This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning.

"People Can Go against the Government": Risk-Based Decision Making and High School Students' Concepts of Society

ERIC Educational Resources Information Center

Radakovic, Nenad

2015-01-01

Research in mathematics education stresses the importance of content knowledge in solving authentic tasks in statistics and in risk-based decision making. Existing research supports the claim that students rely on content knowledge and context expertise to make sense of data. In this article, however, I present evidence that the relationship…

Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest

Treesearch

Denys Yemshanov; Frank H. Koch; Yakov Ben-Haim; William D. Smith

2010-01-01

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads...

Integrating Water Quality and River Rehabilitation Management - A Decision-Analytical Perspective

NASA Astrophysics Data System (ADS)

Reichert, P.; Langhans, S.; Lienert, J.; Schuwirth, N.

2009-04-01

Integrative river management involves difficult decisions about alternative measures to improve their ecological state. For this reason, it seems useful to apply knowledge from the decision sciences to support river management. We discuss how decision-analytical elements can be employed for designing an integrated river management procedure. An important aspect of this procedure is to clearly separate scientific predictions of the consequences of alternatives from objectives to be achieved by river management. The key elements of the suggested procedure are (i) the quantitative elicitation of the objectives from different stakeholder groups, (ii) the compilation of the current scientific knowledge about the consequences of the effects resulting from suggested measures in the form of a probabilistic mathematical model, and (iii) the use of these predictions and valuations to prioritize alternatives, to uncover conflicting objectives, to support the design of better alternatives, and to improve the transparency of communication about the chosen management strategy. The development of this procedure led to insights regarding necessary steps to be taken for rational decision-making in river management, to guidelines about the use of decision-analytical techniques for performing these steps, but also to new insights about the application of decision-analytical techniques in general. In particular, the consideration of the spatial distribution of the effects of measures and the potential added value of connected rehabilitated river reaches leads to favoring measures that have a positive effect beyond a single river reach. As these effects only propagate within the river network, this results in a river basin oriented management concept as a consequence of a rational decision support procedure, rather than as an a priori management paradigm. There are also limitations to the support that can be expected from the decision-analytical perspective. It will not provide the societal values that are driving prioritization in river management, it will only support their elicitation and rational use. This is particularly important for the assessment of micro-pollutants because of severe limitations in scientific knowledge of their effects on river ecosystems. This makes the influence of pollution by micro-pollutants on prioritization of measures strongly dependent on the weight of the precautionary principle relative to other societal objectives of river management.

The influence of science funding agencies in support of effective decision-maker scientist partnerships

NASA Astrophysics Data System (ADS)

Arnott, J. C.; Lemos, M. C.

2017-12-01

A wealth of evidence supports the idea that collaboration between scientists and decision-makers is an influential factor in generating actionable knowledge. Nevertheless, persistent obstacles across the research-policy-practice interface limit the amount of engagement that may be necessary to satisfy demands for information to support decisions. Funding agencies have been identified as one possible driver of change, but few multi-year studies have been conducted to trace the influence of program designs on research practices or other outcomes. To fill this gap, we examine a body of applied science projects (n=120) funded through NOAA's National Estuarine Research Reserve System from 1998-2014. Periodic innovation in the structure of this funding program, including requirements for end user engagement and the inclusion of collaboration specialists, offers a natural experiment from which to test hypotheses about the how funding program design influences research practice, utilization, and broader impacts. Using content analysis of project reports and interviews of project team members, end users, and program managers (n=40), we produce a data that can be analyzed through both statistical and qualitative methods. We find that funder mandates significantly influence the intensity of interaction between researchers and practitioners as well as affect long-term change in research cultures. When interaction intensifies, corresponding gains appear in the readiness of research to support decision-making and the readiness of user groups to incorporate findings into their work. While collaborative methods transform research practice and positively influence the applied contexts in which partnerships occur, it remains less clear whether this actually increases the direct use of scientific to inform decisions. For example, collaboration may lead to outcomes other than new knowledge or knowledge application, yielding many positive outcomes that are distinct from knowledge use itself. We find that improved and more flexible evaluation approaches at the project level and more nuanced, supported and guided by program sponsors, are needed.

Knowledge Representation Artifacts for Use in Sensemaking Support Systems

DTIC Science & Technology

2015-03-12

and manual processing must be replaced by automated processing wherever it makes sense and is possible. Clearly, given the data and cognitive...knowledge-centric view to situation analysis and decision-making as previously discussed, has lead to the development of several automated processing components...for use in sensemaking support systems [6-11]. In turn, automated processing has required the development of appropriate knowledge

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

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

PubMed

Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-26

Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness.

Clinical Decision Support in Electronic Prescribing: Recommendations and an Action Plan

PubMed Central

Teich, Jonathan M.; Osheroff, Jerome A.; Pifer, Eric A.; Sittig, Dean F.; Jenders, Robert A.

2005-01-01

Clinical decision support (CDS) in electronic prescribing (eRx) systems can improve the safety, quality, efficiency, and cost-effectiveness of care. However, at present, these potential benefits have not been fully realized. In this consensus white paper, we set forth recommendations and action plans in three critical domains: (1) advances in system capabilities, including basic and advanced sets of CDS interventions and knowledge, supporting database elements, operational features to improve usability and measure performance, and management and governance structures; (2) uniform standards, vocabularies, and centralized knowledge structures and services that could reduce rework by vendors and care providers, improve dissemination of well-constructed CDS interventions, promote generally applicable research in CDS methods, and accelerate the movement of new medical knowledge from research to practice; and (3) appropriate financial and legal incentives to promote adoption. PMID:15802474

Designing for knowledge: bridging socio-hydrological monitoring and beyond

NASA Astrophysics Data System (ADS)

Mao, F.; Clark, J.; Buytaert, W.; Ochoa-Tocachi, B. F.; Hannah, D. M.

2016-12-01

Many methods and applications have been developed to research socio-hydrological systems, such as participatory monitoring, environmental big data processing and sensor network data transmission. However, these data-centred activities are insufficient to guarantee successful knowledge co-generation, decision making or governance. This research suggests a shift of attentions in designing socio-hydrological monitoring tools, from designing for data to designing for knowledge (DfK). Compared to the former strategy, DfK has at least three features as follows. (1) Why monitor? DfK demands the data produced by the newly introduced monitoring application to have potentials to generate socio-hydrological knowledge that supports decision making or management. It means that when designing a monitoring tool, we should not only answer how to collect data, but also questions such as how to best use the collected data in the form of knowledge. (2) What is the role of monitoring? DfK admits that the socio-hydrological data and knowledge generated by monitoring is just one of many kinds to support decision making and management. It means that the importance of monitoring and scientific evidence should not be overestimated, and knowledge cogeneration and synthesis should be considered in advance in the monitoring design process. (3) Who participate? DfK implies a wider engagement of stakeholders, which is not restricted between volunteers as data collectors and providers, and scientist and researcher communities as main data users. It requires a broader consideration of users, including not only data collectors, processors and interpreters, but also local and indigenous knowledge providers, and decision makers who use the knowledge and data. In summary, this research proposes a knowledge-centred strategy in designing participatory socio-hydrological monitoring tools, in order to make monitoring more useful and effective.

Knowledge Management Implementation and the Tools Utilized in Healthcare for Evidence-Based Decision Making: A Systematic Review.

PubMed

Shahmoradi, Leila; Safadari, Reza; Jimma, Worku

2017-09-01

Healthcare is a knowledge driven process and thus knowledge management and the tools to manage knowledge in healthcare sector are gaining attention. The aim of this systematic review is to investigate knowledge management implementation and knowledge management tools used in healthcare for informed decision making. Three databases, two journals websites and Google Scholar were used as sources for the review. The key terms used to search relevant articles include: "Healthcare and Knowledge Management"; "Knowledge Management Tools in Healthcare" and "Community of Practices in healthcare". It was found that utilization of knowledge management in healthcare is encouraging. There exist numbers of opportunities for knowledge management implementation, though there are some barriers as well. Some of the opportunities that can transform healthcare are advances in health information and communication technology, clinical decision support systems, electronic health record systems, communities of practice and advanced care planning. Providing the right knowledge at the right time, i.e., at the point of decision making by implementing knowledge management in healthcare is paramount. To do so, it is very important to use appropriate tools for knowledge management and user-friendly system because it can significantly improve the quality and safety of care provided for patients both at hospital and home settings.

Role of Advance Care Planning in Proxy Decision Making Among Individuals With Dementia and Their Family Caregivers.

PubMed

Kwak, Jung; De Larwelle, Jessica A; Valuch, Katharine O'Connell; Kesler, Toni

2016-01-01

Health care proxies make important end-of-life decisions for individuals with dementia. A cross-sectional survey was conducted to examine the role of advance care planning in proxy decision making for 141 individuals with cognitive impairment, Alzheimer's disease, or other types of dementia. Proxies who did not know the preferences of individuals with dementia for life support treatments reported greater understanding of their values. Proxies of individuals with dementia who did not want life support treatments anticipated receiving less support and were more uncertain in decision making. The greater knowledge proxies had about dementia trajectory, family support, and trust of physicians, the more informed, clearer, and less uncertain they were in decision making. In addition to advance care planning, multiple factors influence proxy decision making, which should be considered in developing interventions and future research to support informed decision making for individuals with dementia and their families. Copyright 2016, SLACK Incorporated.

Information management to enable personalized medicine: stakeholder roles in building clinical decision support.

PubMed

Downing, Gregory J; Boyle, Scott N; Brinner, Kristin M; Osheroff, Jerome A

2009-10-08

Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized decision-making, a comparison of current and future applications of clinical decision support to enable individualized medical treatment plans is presented. If clinical decision support tools are to impact outcomes in a clear and positive manner, their development and deployment must therefore consider the needs of the providers, including specific practice needs, information workflow, and practice environment.

Information management to enable personalized medicine: stakeholder roles in building clinical decision support

PubMed Central

2009-01-01

Background Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Discussion Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. Summary This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized decision-making, a comparison of current and future applications of clinical decision support to enable individualized medical treatment plans is presented. If clinical decision support tools are to impact outcomes in a clear and positive manner, their development and deployment must therefore consider the needs of the providers, including specific practice needs, information workflow, and practice environment. PMID:19814826

Decision-Making and the Interface between Human Intelligence and Artificial Intelligence. AIR 1987 Annual Forum Paper.

ERIC Educational Resources Information Center

Henard, Ralph E.

Possible future developments in artificial intelligence (AI) as well as its limitations are considered that have implications for institutional research in higher education, and especially decision making and decision support systems. It is noted that computer software programs have been developed that store knowledge and mimic the decision-making…

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,...

The Influence of Parental Support, Knowledge, and Authoritative Parenting on Hmong and European American Adolescent Development

ERIC Educational Resources Information Center

Supple, Andrew J.; Small, Stephen A.

2006-01-01

This study used a community-wide survey of adolescents to compare adolescent perceptions of parental support, knowledge, and authoritative decision making in samples of Hmong and European Americans. Additional analyses considered variation in parental influence on adolescent outcomes across these groups. The results suggested that Hmong American…

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.

Decision Making: New Paradigm for Education.

ERIC Educational Resources Information Center

Wales, Charles E.; And Others

1986-01-01

Defines education's new paradigm as schooling based on decision making, the critical thinking skills serving it, and the knowledge base supporting it. Outlines a model decision-making process using a hypothetical breakfast problem; a late riser chooses goals, generates ideas, develops an action plan, and implements and evaluates it. (4 references)…

Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making.

PubMed

Capalbo, Susan M; Antle, John M; Seavert, Clark

2017-07-01

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa , which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed

Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

Multidisciplinary Modelling of Symptoms and Signs with Archetypes and SNOMED-CT for Clinical Decision Support.

PubMed

Marco-Ruiz, Luis; Maldonado, J Alberto; Karlsen, Randi; Bellika, Johan G

2015-01-01

Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology.

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.

Preliminary validation of the Satisfaction With Decision scale with depressed primary care patients

PubMed Central

Wills, Celia E.; Holmes‐Rovner, Margaret

2003-01-01

Abstract Objective To conduct a preliminary validation of the Satisfaction With Decision (SWD) scale with depressed primary care patients. Design  Cross‐sectional observational pilot study using a postal survey. Setting and participants  Depressed primary care patients (n = 97) who recently had made a new decision about antidepressant medication use completed surveys regarding their treatment decisions. Main variables  Measures included patient‐reported satisfaction with decision, decisional conflict, knowledge about depression and treatment, decision involvement, pain and health status, antidepressant medication efficacy, and satisfaction with health services. Results  The SWD scale had good internal consistency reliability (α = 0.85). Evidence for construct validity was confirmed via a hypothesized pattern of relationships between the SWD scale and other measures. Decision satisfaction was associated with several issues of relevance for designing patient‐centred decision support interventions: (1) knowledge about depression and treatment; (2) involvement in health‐related decisions; and (3) aiding evaluation of trade‐offs among pros and cons of treatment. Conclusions  The results of this pilot study show that the SWD scale appears to be a psychometrically sound and practical measure for research with this population. Additional research is needed on the theoretical nature of decision satisfaction and developing and testing patient‐centred decision support interventions for depression treatment. PMID:12752743

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

Attitudes and Decisional Conflict Regarding Breast Reconstruction Among Breast Cancer Patients.

PubMed

Manne, Sharon L; Topham, Neal; Kirstein, Laurie; Virtue, Shannon Myers; Brill, Kristin; Devine, Katie A; Gajda, Tina; Frederick, Sara; Darabos, Katie; Sorice, Kristen

The decision to undergo breast reconstruction (BR) surgery after mastectomy is made during stressful circumstances. Many women do not feel well prepared to make this decision. Using the Ottawa Decision Support Framework, this study aims to describe women's reasons to choose or not choose BR, BR knowledge, decisional preparedness, and decisional conflict about BR. Possible demographic, medical, BR knowledge, and attitudinal correlates of decisional conflict about BR were also evaluated. Participants were 55 women with early-stage breast cancer drawn from the baseline data of a pilot randomized trial evaluating the efficacy of a BR decision support aid for breast cancer patients considering BR. The most highly ranked reasons to choose BR were the desire for breasts to be equal in size, the desire to wake up from surgery with a breast in place, and perceived bother of a scar with no breast. The most highly ranked reasons not to choose BR were related to the surgical risks and complications. Regression analyses indicated that decisional conflict was associated with higher number of reasons not to choose BR and lower levels of decisional preparedness. The results suggest that breast cancer patients considering BR may benefit from decisional support. Healthcare professionals may facilitate decision making by focusing on reasons for each patient's uncertainty and unaddressed concerns. All patients, even those who have consulted with a plastic surgeon and remain uncertain about their decision, may benefit from decision support from a health professional.

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.

Use of Low-Literacy Decision Aid to Enhance Knowledge and Reduce Decisional Conflict Among a Diverse Population of Adults With Rheumatoid Arthritis: Results of a Pilot Study.

PubMed

Barton, Jennifer L; Trupin, Laura; Schillinger, Dean; Evans-Young, Gina; Imboden, John; Montori, Victor M; Yelin, Edward

2016-07-01

Despite innovations in treatment of rheumatoid arthritis (RA), adherence is poor and disparities persist. Shared decision making (SDM) promotes patient engagement and enhances adherence; however, few tools support SDM in RA. Our objective was to pilot a low-literacy medication guide and decision aid to facilitate patient-clinician conversations about RA medications. RA patients were consecutively enrolled into 1 of 3 arms: 1) control; patients received existing medication guide prior to clinic visit, 2) adapted guide prior to visit, and 3) adapted guide prior to plus decision aid during visit. Outcomes were collected immediately postvisit, at 1-week, and at 3- and 6-month interviews. Eligible adults had to have failed at least 1 disease-modifying antirheumatic drug and fulfill 1 of the following: age >65 years, immigrant, non-English speaker, less than high school education, limited health literacy, and racial/ethnic minority. Primary outcomes were knowledge of RA medications, decisional conflict, and acceptability of interventions. The majority of 166 patients were immigrants (66%), non-English speakers (54%), and had limited health literacy (71%). Adequate RA knowledge postvisit in arm 3 was higher (78%) than arm 1 (53%; adjusted odds ratio 2.7, 95% confidence interval 1.2, 6.1). Among patients with a medication change, there was lower (better) mean decisional conflict in arms 2 and 3 (P = 0.03). There were no significant differences in acceptability. A low-literacy medication guide and decision aid was acceptable, improved knowledge, and reduced decisional conflict among vulnerable RA patients. Enhancing knowledge and patient engagement with decision support tools may lead to medication choices better aligned with RA patients' values and preferences. © 2016, American College of Rheumatology.

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

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

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.

Leveraging certified nursing assistant documentation and knowledge to improve clinical decision making: the on-time quality improvement program to prevent pressure ulcers.

PubMed

Sharkey, Siobhan; Hudak, Sandra; Horn, Susan D; Spector, William

2011-04-01

The goal of this article was to enhance understanding of the On-Time Quality Improvement for Long-term Care Program, a practical approach to embed health information technology into quality improvement in nursing homes that leverages certified nursing assistant documentation and knowledge, supports frontline clinical decision making, and establishes proactive intervention for pressure ulcer prevention.

A conceptual framework for understanding the perspectives on the causes of the science-practice gap in ecology and conservation.

PubMed

Bertuol-Garcia, Diana; Morsello, Carla; N El-Hani, Charbel; Pardini, Renata

2018-05-01

Applying scientific knowledge to confront societal challenges is a difficult task, an issue known as the science-practice gap. In Ecology and Conservation, scientific evidence has been seldom used directly to support decision-making, despite calls for an increasing role of ecological science in developing solutions for a sustainable future. To date, multiple causes of the science-practice gap and diverse approaches to link science and practice in Ecology and Conservation have been proposed. To foster a transparent debate and broaden our understanding of the difficulties of using scientific knowledge, we reviewed the perceived causes of the science-practice gap, aiming to: (i) identify the perspectives of ecologists and conservation scientists on this problem, (ii) evaluate the predominance of these perspectives over time and across journals, and (iii) assess them in light of disciplines studying the role of science in decision-making. We based our review on 1563 sentences describing causes of the science-practice gap extracted from 122 articles and on discussions with eight scientists on how to classify these sentences. The resulting process-based framework describes three distinct perspectives on the relevant processes, knowledge and actors in the science-practice interface. The most common perspective assumes only scientific knowledge should support practice, perceiving a one-way knowledge flow from science to practice and recognizing flaws in knowledge generation, communication, and/or use. The second assumes that both scientists and decision-makers should contribute to support practice, perceiving a two-way knowledge flow between science and practice through joint knowledge-production/integration processes, which, for several reasons, are perceived to occur infrequently. The last perspective was very rare, and assumes scientists should put their results into practice, but they rarely do. Some causes (e.g. cultural differences between scientists and decision-makers) are shared with other disciplines, while others seem specific to Ecology and Conservation (e.g. inadequate research scales). All identified causes require one of three general types of solutions, depending on whether the causal factor can (e.g. inadequate research questions) or cannot (e.g. scientific uncertainty) be changed, or if misconceptions (e.g. undervaluing abstract knowledge) should be solved. The unchanged predominance of the one-way perspective over time may be associated with the prestige of evidence-based conservation and suggests that debates in Ecology and Conservation lag behind trends in other disciplines towards bidirectional views ascribing larger roles to decision-makers. In turn, the two-way perspective seems primarily restricted to research traditions historically isolated from mainstream conservation biology. All perspectives represented superficial views of decision-making by not accounting for limits to human rationality, complexity of decision-making contexts, fuzzy science-practice boundaries, ambiguity brought about by science, and different types of knowledge use. However, joint knowledge-production processes from the two-way perspective can potentially allow for democratic decision-making processes, explicit discussions of values and multiple types of science use. To broaden our understanding of the interface and foster productive science-practice linkages, we argue for dialogue among different research traditions within Ecology and Conservation, joint knowledge-production processes between scientists and decision-makers and interdisciplinarity across Ecology, Conservation and Political Science in both research and education. © 2017 Cambridge Philosophical Society.

Knowledge in Development: Epistemic Machineries in a Global Context

ERIC Educational Resources Information Center

Evers, Hans-Dieter; Kaiser, Markus; Muller, Christine

2009-01-01

Knowledge has become a decisive and competitive resource for local and global development, especially since the paradigm "knowledge for development" was initiated and promoted by the World Bank in 1998-1999. Through the use of novel management structures and technologically supported social networks, development organisations and…

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

PubMed Central

Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-01

Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Conclusions Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness. PMID:26813512

Collaboration and co-production of climate knowledge: lessons from a network on the front-line

NASA Astrophysics Data System (ADS)

Kettle, N.

2016-12-01

The science-practice gap is broadly considered a major barrier to the production and application of decision-relevant science. This study uses a social network analysis, based on 126 interviews, to analyze the roles and network ties among climate scientists, service providers, and decision makers in Alaska. Our research highlights the importance of key actors and significant differences in bonding and bridging ties across roles - structural characteristics that provide a basis for informing recommendations to build adaptive capacity and support the co-production of knowledge. Our findings also illustrate that some individuals in the network engage in multiple roles, suggesting that conceptualizing the science-practice interface as consisting of "producers" and "consumers" oversimplifies how individuals engage in climate science, services, and decision making. This research supports the notion that the development and use of climate information is a networked phenomenon. It also emphasizes the importance of centralized individuals who are capable of engaging in multiple roles for the transition of knowledge action.

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.

Producing More Actionable Science Isn't the Problem; It's Providing Decision-Makers with Access to Right Actionable Knowledge

NASA Astrophysics Data System (ADS)

Trexler, M.

2017-12-01

Policy-makers today have almost infinite climate-relevant scientific and other information available to them. The problem for climate change decision-making isn't missing science or inadequate knowledge of climate risks; the problem is that the "right" climate change actionable knowledge isn't getting to the right decision-maker, or is getting there too early or too late to effectively influence her decision-making. Actionable knowledge is not one-size-fit-all, and for a given decision-maker might involve scientific, economic, or risk-based information. Simply producing more and more information as we are today is not the solution, and actually makes it harder for individual decision-makers to access "their" actionable knowledge. The Climatographers began building the Climate Web five years ago to test the hypothesis that a knowledge management system could help navigate the gap between infinite information and individual actionable knowledge. Today the Climate Web's more than 1,500 index terms allow instant access to almost any climate change topic. It is a curated public-access knowledgebase of more than 1,000 books, 2,000 videos, 15,000 reports and articles, 25,000 news stories, and 3,000 websites. But it is also much more, linking together tens of thousands of individually extracted ideas and graphics, and providing Deep Dives into more than 100 key topics from changing probability distributions of extreme events to climate communications best practices to cognitive dissonance in climate change decision-making. The public-access Climate Web is uniquely able to support cross-silo learning, collaboration, and actionable knowledge dissemination. The presentation will use the Climate Web to demonstrate why knowledge management should be seen as a critical component of science and policy-making collaborations.

Forward view: advancing health library and knowledge services in England.

PubMed

Lacey Bryant, Sue; Bingham, Helen; Carlyle, Ruth; Day, Alison; Ferguson, Linda; Stewart, David

2018-03-01

This article is the fourth in a series on New Directions. The National Health Service is under pressure, challenged to meet the needs of an ageing population, whilst striving to improve standards and ensure decision making is underpinned by evidence. Health Education England is steering a new course for NHS library and knowledge services in England to ensure access to knowledge and evidence for all decision makers. Knowledge for Healthcare calls for service transformation, role redesign, greater coordination and collaboration. To meet user expectations, health libraries must achieve sustainable, affordable access to digital content. Traditional tasks will progressively become mechanised. Alongside supporting learners, NHS librarians and knowledge specialists will take a greater role as knowledge brokers, delivering business critical services. They will support the NHS workforce to signpost patients and the public to high-quality information. There is a need for greater efficiency and effectiveness through greater co-operation and service mergers. Evaluation of service quality will focus more on outcomes, less on counting. These changes require an agile workforce, fit for the future. There is a bright future in which librarians' expertise is used to mobilise evidence, manage and share knowledge, support patients, carers and families, optimise technology and social media and provide a keystone for improved patient care and safety. © 2018 Health Libraries Group.

Clinical Decision Support Knowledge Management: Strategies for Success.

PubMed

Khalifa, Mohamed; Alswailem, Osama

2015-01-01

Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

Capturing information needs of care providers to support knowledge sharing and distributed decision making.

PubMed

Rogers, M; Zach, L; An, Y; Dalrymple, P

2012-01-01

This paper reports on work carried out to elicit information needs at a trans-disciplinary, nurse-managed health care clinic that serves a medically disadvantaged urban population. The trans-disciplinary model provides a "one-stop shop" for patients who can receive a wide range of services beyond traditional primary care. However, this model of health care presents knowledge sharing challenges because little is known about how data collected from the non-traditional services can be integrated into the traditional electronic medical record (EMR) and shared with other care providers. There is also little known about how health information technology (HIT) can be used to support the workflow in such a practice. The objective of this case study was to identify the information needs of care providers in order to inform the design of HIT to support knowledge sharing and distributed decision making. A participatory design approach is presented as a successful technique to specify requirements for HIT applications that can support a trans-disciplinary model of care. Using this design approach, the researchers identified the information needs of care providers working at the clinic and suggested HIT improvements to integrate non-traditional information into the EMR. These modifications allow knowledge sharing among care providers and support better health decisions. We have identified information needs of care providers as they are relevant to the design of health information systems. As new technology is designed and integrated into various workflows it is clear that understanding information needs is crucial to acceptance of that technology.

Dissociations in mathematical knowledge: case studies in Down's syndrome and Williams syndrome.

PubMed

Robinson, Sally J; Temple, Christine M

2013-02-01

A study is reported of mathematical vocabulary and factual mathematical knowledge in PQ, a 22 year old with Down's syndrome (DS) who has a verbal mental age (MA) of 9 years 2 months and ST, a 15 year old with Williams syndrome (WS) who has a verbal MA of 9 years 6 months, matched to typically developing controls. The number of mathematical words contained within PQ's lexical stores was significantly reduced as reflected by performance on lexical decision. PQ was also impaired at both naming from descriptions and describing mathematical words. These results contrast with normal lexical decision and item descriptions for concrete words reported recently for PQ (Robinson and Temple, 2010). PQ's recall of mathematical facts was also impaired, whilst his recall of general knowledge facts was normal. This performance in DS indicates a deficit in both lexical representation and semantic knowledge for mathematical words and mathematical facts. In contrast, ST, the teenager with WS had good accuracy on lexical decision, naming and generating definitions for mathematical words. This contrasted with the atypical performance with concrete words recently reported for ST (Robinson and Temple, 2009). Knowledge of addition facts and general knowledge facts was also unimpaired for ST, though knowledge of multiplication facts was weak. Together the cases form a double dissociation and provide support for the distinct representation of mathematical and concrete items within the lexical-semantic system during development. The dissociations between mathematical and general factual knowledge also indicate that different types of factual knowledge may be selectively impaired during development. There is further support for a modular structure within which mathematical vocabulary and mathematical knowledge have distinct representations. This supports the case for the independent representation of factual and language-based knowledge within the semantic system during development. Copyright © 2011 Elsevier Ltd. All rights reserved.

The development of an online decision aid to support persons having a genetic predisposition to cancer and their partners during reproductive decision-making: a usability and pilot study.

PubMed

Reumkens, Kelly; Tummers, Marly H E; Gietel-Habets, Joyce J G; van Kuijk, Sander M J; Aalfs, Cora M; van Asperen, Christi J; Ausems, Margreet G E M; Collée, Margriet; Dommering, Charlotte J; Kets, C Marleen; van der Kolk, Lizet E; Oosterwijk, Jan C; Tjan-Heijnen, Vivianne C G; van der Weijden, Trudy; de Die-Smulders, Christine E M; van Osch, Liesbeth A D M

2018-05-30

An online decision aid to support persons having a genetic predisposition to cancer and their partners during reproductive decision-making was developed. A two-phase usability test was conducted among 12 couples (N = 22; 2 persons participated without their partner) at risk for hereditary cancer and 15 health care providers. Couples and health care providers expressed similar suggestions for improvements, and evaluated the modified decision aid as acceptable, easy to use, and comprehensible. The final decision aid was pilot tested (N = 16) with paired sample t tests comparing main outcomes (decisional conflict, knowledge, realistic expectations regarding the reproductive options and decision self-efficacy) before (T0), immediately (T1) and 2 weeks after (T2) use of the decision aid. Pilot testing indicated decreased decisional conflict scores, increased knowledge, and improved realistic expectations regarding the reproductive options, at T1 and T2. No effect was found for couples' decision self-efficacy. The positive findings during usability testing were thus reflected in the pilot study. The decision aid will be further evaluated in a nationwide pretest-posttest study to facilitate implementation in the onco-genetic counselling setting. Ultimately, it is expected that the decision aid will enable end-users to make an informed decision.

Knowledge discovery from data as a framework to decision support in medical domains

PubMed Central

Gibert, Karina

2009-01-01

Introduction Knowledge discovery from data (KDD) is a multidisciplinary discipline which appeared in 1996 for “non trivial identifying of valid, novel, potentially useful, ultimately understandable patterns in data”. Pre-treatment of data and post-processing is as important as the data exploitation (Data Mining) itself. Different analysis techniques can be properly combined to produce explicit knowledge from data. Methods Hybrid KDD methodologies combining Artificial Intelligence with Statistics and visualization have been used to identify patterns in complex medical phenomena: experts provide prior knowledge (pK); it biases the search of distinguishable groups of homogeneous objects; support-interpretation tools (CPG) assisted experts in conceptualization and labelling of discovered patterns, consistently with pK. Results Patterns of dependency in mental disabilities supported decision-making on legislation of the Spanish Dependency Law in Catalonia. Relationships between type of neurorehabilitation treatment and patterns of response for brain damage are assessed. Patterns of the perceived QOL along time are used in spinal cord lesion to improve social inclusion. Conclusion Reality is more and more complex and classical data analyses are not powerful enough to model it. New methodologies are required including multidisciplinarity and stressing on production of understandable models. Interaction with the experts is critical to generate meaningful results which can really support decision-making, particularly convenient transferring the pK to the system, as well as interpreting results in close interaction with experts. KDD is a valuable paradigm, particularly when facing very complex domains, not well understood yet, like many medical phenomena.

Communicating risk of hereditary breast and ovarian cancer with an interactive decision support tool.

PubMed

Rupert, Douglas J; Squiers, Linda B; Renaud, Jeanette M; Whitehead, Nedra S; Osborn, Roger J; Furberg, Robert D; Squire, Claudia M; Tzeng, Janice P

2013-08-01

Women with hereditary breast and ovarian cancer syndrome (HBOC) face a higher risk of earlier, more aggressive cancer. Because of HBOC's rarity, screening is recommended only for women with strong cancer family histories. However, most patients do not have accurate history available and struggle to understand genetic concepts. Cancer in the Family, an online clinical decision support tool, calculated women's HBOC risk and promoted shared patient-provider decisions about screening. A pilot evaluation (n=9 providers, n=48 patients) assessed the tool's impact on knowledge, attitudes, and screening decisions. Patients used the tool before wellness exams and completed three surveys. Providers accessed the tool during exams, completed exam checklists, and completed four surveys. Patients entered complete family histories (67%), calculated personal risk (96%), and shared risk printouts with providers (65%). HBOC knowledge increased dramatically for patients and providers, and many patients (75%) perceived tool results as valid. The tool prompted patient-provider discussions about HBOC risk and cancer family history (88%). The tool was effective in increasing knowledge, collecting family history, and sparking patient-provider discussions about HBOC screening. Interactive tools can effectively communicate personalized risk and promote shared decisions, but they are not a substitute for patient-provider discussions. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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.

New Zealand university students' knowledge and attitudes to organ and tissue donation.

PubMed

Cornwall, Jon; Schafer, Cyril; Lal, Navneet; D'Costa, Rohit; Nada-Raja, Shyamala

2015-08-07

Organ and tissue donation (OTD) rates in New Zealand are low compared to many countries. Young adults are 'tomorrow's donors', yet the attitudes and knowledge of this group to OTD have not been examined locally. Such information is relevant to ODT education and clinical engagement. A random sample of University of Otago students (<25 years, permanent New Zealand resident) was surveyed to examine OTD knowledge and attitudes. This included general knowledge, OTD policy (opt-in, opt-out), donation by self, and donation by loved ones. Questions included yes-no, multiple choice, and Likert-type responses. Analyses by sex, demographic characteristics, supportive attitudes to ODT, and University of Otago student profile were performed. 180 responses were gathered (mean age 20.1 years, 67% female, 68% New Zealand European); there were no age or response differences between sexes, participants were generally not representative of the University of Otago student profile. Outcomes indicated limited OTD knowledge, positive support for OTD, and willingness to engage in donation the decision-making process for loved ones. Differences between supportive and non-supportive OTD attitudes was seen for some questions. Findings highlight areas for strategic OTD public engagement and provide details relevant to guiding appropriate clinical interaction in facilitating decisions about OTD.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed Central

Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser. Images Figure 1 PMID:10566470

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.

“Kinect-ing” With Clinicians: A Knowledge Translation Resource to Support Decision Making About Video Game Use in Rehabilitation

PubMed Central

Levac, Danielle; Espy, Deborah; Fox, Emily; Pradhan, Sujata

2015-01-01

Microsoft's Kinect for Xbox 360 virtual reality (VR) video games are promising rehabilitation options because they involve motivating, full-body movement practice. However, these games were designed for recreational use, which creates challenges for clinical implementation. Busy clinicians require decision-making support to inform game selection and implementation that address individual therapeutic goals. This article describes the development and preliminary evaluation of a knowledge translation (KT) resource to support clinical decision making about selection and use of Kinect games in physical therapy. The knowledge-to-action framework guided the development of the Kinecting With Clinicians (KWiC) resource. Five physical therapists with VR and video game expertise analyzed the Kinect Adventure games. A consensus-building method was used to arrive at categories to organize clinically relevant attributes guiding game selection and game play. The process and results of an exploratory usability evaluation of the KWiC resource by clinicians through interviews and focus groups at 4 clinical sites is described. Subsequent steps in the evaluation and KT process are proposed, including making the KWiC resource Web-based and evaluating the utility of the online resource in clinical practice. PMID:25256741

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.

"Kinect-ing" with clinicians: a knowledge translation resource to support decision making about video game use in rehabilitation.

PubMed

Levac, Danielle; Espy, Deborah; Fox, Emily; Pradhan, Sujata; Deutsch, Judith E

2015-03-01

Microsoft's Kinect for Xbox 360 virtual reality (VR) video games are promising rehabilitation options because they involve motivating, full-body movement practice. However, these games were designed for recreational use, which creates challenges for clinical implementation. Busy clinicians require decision-making support to inform game selection and implementation that address individual therapeutic goals. This article describes the development and preliminary evaluation of a knowledge translation (KT) resource to support clinical decision making about selection and use of Kinect games in physical therapy. The knowledge-to-action framework guided the development of the Kinecting With Clinicians (KWiC) resource. Five physical therapists with VR and video game expertise analyzed the Kinect Adventure games. A consensus-building method was used to arrive at categories to organize clinically relevant attributes guiding game selection and game play. The process and results of an exploratory usability evaluation of the KWiC resource by clinicians through interviews and focus groups at 4 clinical sites is described. Subsequent steps in the evaluation and KT process are proposed, including making the KWiC resource Web-based and evaluating the utility of the online resource in clinical practice. © 2015 American Physical Therapy Association.

Data access and decision tools for coastal water resources management

EPA Science Inventory

US EPA has supported the development of numerous models and tools to support implementation of environmental regulations. However, transfer of knowledge and methods from detailed technical models to support practical problem solving by local communities and watershed or coastal ...

Analysis of the risk management decisionmaking processes and the decision support systems in the wildland fire agencies

Treesearch

Patrick Withen

2007-01-01

This paper offers an analysis of the strengths, weaknesses, opportunities, and threats in the risk management process, decision support systems (DSSs), and other types of decisionmaking, including recognition primed decisionmaking, bricolage with the goal of improving DSSs and decisionmaking. DSSs may be thought of as any technology or knowledge that is used as an aid...

Knowledge Flow Mesh and Its Dynamics: A Decision Support Environment

DTIC Science & Technology

2008-06-01

paper was the ability of the United States military to achieve dominance through information superiority. The use of intelligent sensors and... Intelligence Agency, National Security Agency, Defense Intelligence Agency, and individual Service intelligence agencies). In fact, these edge entities would... intelligence , design, choice, and implementation. 6. Support variety of decision processes and styles. 7. DSS should be adaptable and flexible. 8. DSS

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.

Bioenergy Knowledge Discovery Framework Fact Sheet

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

None

The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

Knowledge engineering in volcanology: Practical claims and general approach

NASA Astrophysics Data System (ADS)

Pshenichny, Cyril A.

2014-10-01

Knowledge engineering, being a branch of artificial intelligence, offers a variety of methods for elicitation and structuring of knowledge in a given domain. Only a few of them (ontologies and semantic nets, event/probability trees, Bayesian belief networks and event bushes) are known to volcanologists. Meanwhile, the tasks faced by volcanology and the solutions found so far favor a much wider application of knowledge engineering, especially tools for handling dynamic knowledge. This raises some fundamental logical and mathematical problems and requires an organizational effort, but may strongly improve panel discussions, enhance decision support, optimize physical modeling and support scientific collaboration.

An exploratory mixed-methods crossover study comparing DVD- vs. Web-based patient decision support in three conditions: The importance of patient perspectives.

PubMed

Halley, Meghan C; Rendle, Katharine A S; Gillespie, Katherine A; Stanley, Katherine M; Frosch, Dominick L

2015-12-01

The last 15 years have witnessed considerable progress in the development of decision support interventions (DESIs). However, fundamental questions about design and format of delivery remain. An exploratory, randomized mixed-method crossover study was conducted to compare a DVD- and Web-based DESI. Randomized participants used either the Web or the DVD first, followed by the alternative format. Participants completed a questionnaire to assess decision-specific knowledge at baseline and a questionnaire and structured qualitative interview after viewing each format. Tracking software was used to capture Web utilization. Transcripts were analyzed using integrated inductive and deductive approaches. Quantitative data were analyzed using exploratory bivariate and multivariate analyses. Exploratory knowledge analyses suggest that both formats increased knowledge, with limited evidence that the DVD increased knowledge more than the Web. Format preference varied across participants: 44% preferred the Web, 32% preferred the DVD and 24% preferred 'both'. Patient discussions of preferences for DESI information structure and the importance of a patients' stage of a given decision suggest these characteristics may be important factors underlying variation in utilization, format preferences and knowledge outcomes. Our results suggest that both DESI formats effectively increase knowledge. Patients' perceptions of these two formats further suggest that there may be no single 'best' format for all patients. These results have important implications for understanding why different DESI formats might be preferable to and more effective for different patients. Further research is needed to explore the relationship between these factors and DESI utilization outcomes across diverse patient populations. © 2014 John Wiley & Sons Ltd.

Tapping into community wisdom and integrating local knowledge into revitalization efforts

EPA Science Inventory

Local decision-making is sometimes considered a puzzle by research ecologists, resource managers, and policy researchers. The eternal hope is to find that model or concept that provides the “right” information to support local environmental decisions. Researchers have...

Drug knowledge expressed as computable semantic triples.

PubMed

Elkin, Peter L; Carter, John S; Nabar, Manasi; Tuttle, Mark; Lincoln, Michael; Brown, Steven H

2011-01-01

The majority of questions that arise in the practice of medicine relate to drug information. Additionally, adverse reactions account for as many as 98,000 deaths per year in the United States. Adverse drug reactions account for a significant portion of those errors. Many authors believe that clinical decision support associated with computerized physician order entry has the potential to decrease this adverse drug event rate. This decision support requires knowledge to drive the process. One important and rich source of drug knowledge is the DailyMed product labels. In this project we used computationally extracted SNOMED CT™ codified data associated with each section of each product label as input to a rules engine that created computable assertional knowledge in the form of semantic triples. These are expressed in the form of "Drug" HasIndication "SNOMED CT™". The information density of drug labels is deep, broad and quite substantial. By providing a computable form of this information content from drug labels we make these important axioms (facts) more accessible to computer programs designed to support improved care.

Computer based extraction of phenoptypic features of human congenital anomalies from the digital literature with natural language processing techniques.

PubMed

Karakülah, Gökhan; Dicle, Oğuz; Koşaner, Ozgün; Suner, Aslı; Birant, Çağdaş Can; Berber, Tolga; Canbek, Sezin

2014-01-01

The lack of laboratory tests for the diagnosis of most of the congenital anomalies renders the physical examination of the case crucial for the diagnosis of the anomaly; and the cases in the diagnostic phase are mostly being evaluated in the light of the literature knowledge. In this respect, for accurate diagnosis, ,it is of great importance to provide the decision maker with decision support by presenting the literature knowledge about a particular case. Here, we demonstrated a methodology for automated scanning and determining of the phenotypic features from the case reports related to congenital anomalies in the literature with text and natural language processing methods, and we created a framework of an information source for a potential diagnostic decision support system for congenital anomalies.

Constitutional and Legal Protection for Life Support Limitation in India

PubMed Central

Mani, RK

2015-01-01

Appropriate treatment limitations towards the end of life to reduce unwanted burdens require ethical clarity that is supported by appropriate legislation. The lack of knowledge of enabling legal provisions, physicians feel vulnerable to legal misinterpretation of treatment limiting decisions. In India the lack of societal awareness, inadequate exploration of the gray areas of bio-ethics and unambiguous legal position relating to terminal illness have resulted in poor quality end of life care. Much of the perceived vulnerability by the physician is attributable to insufficient knowledge and understanding of existing constitutional and legal position in India. While we await informed legal and legislative opinion, this paper highlights possible legal liabilities arising from treatment limitation decisions with available defense. It is hoped that such clarity would lead to more confident ethical decisions and improved end of life care for patients. PMID:26600691

Why do clinicians choose the therapies and techniques they do? Exploring clinical decision-making via treatment selections in dysphagia practice.

PubMed

McCurtin, Arlene; Healy, Chiara

2017-02-01

Speech-language pathologists (SLPs) are assumed to use evidence-based practice to inform treatment decisions. However, the reasoning underpinning treatment selections is not well known. Understanding why SLPs choose the treatments they do may be clarified by exploring the reasoning tied to specific treatments such as dysphagia interventions. An electronic survey methodology was utilised. Participants were accessed via the gatekeepers of two national dysphagia special interest groups representing adult and paediatric populations. Information was elicited on the dysphagia therapies and techniques used and on the reasoning for using/not using therapies. Data was analysed using descriptive and non-parametric statistics. The survey had a 74.8% response rate (n = 116). Consensus in both treatment selections and reasoning supporting treatment decisions was evident. Three favoured interventions (texture modification, thickening liquids, positioning changes) were identified. The reasoning supporting treatment choices centred primarily on client suitability and clinician knowledge. Knowledge reflected both absent knowledge (e.g. training) and accumulated knowledge (clinical experience). Dysphagia practice appears highly-defined, being characterised by group consensus regarding both preferred treatments and the reasoning underpinning treatment selections. Treatment selections are based on two core criteria: client suitability and the SLPs experience/knowledge. Explicit scientific reasoning is less influential than practice-centric influences.

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.

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

Service users' experiences of participation in decision making in mental health services.

PubMed

Dahlqvist Jönsson, P; Schön, U-K; Rosenberg, D; Sandlund, M; Svedberg, P

2015-11-01

Despite the potential positive impact of shared decision making on service users knowledge and experience of decisional conflict, there is a lack of qualitative research on how participation in decision making is promoted from the perspective of psychiatric service users. This study highlights the desire of users to participate more actively in decision making and demonstrates that persons with SMI struggle to be seen as competent and equal partners in decision-making situations. Those interviewed did not feel that their strengths, abilities and needs were being recognized, which resulted in a feeling of being omitted from involvement in decision-making situations. The service users describe some essential conditions that could work to promote participation in decision making. These included having personal support, having access to knowledge, being involved in a dialogue and clarity about responsibilities. Mental health nurses can play an essential role for developing and implementing shared decision making as a tool to promote recovery-oriented mental health services. Service user participation in decision making is considered an essential component of recovery-oriented mental health services. Despite the potential of shared decision making to impact service users knowledge and positively influence their experience of decisional conflict, there is a lack of qualitative research on how participation in decision making is promoted from the perspective of psychiatric service users. In order to develop concrete methods that facilitate shared decision making, there is a need for increased knowledge regarding the users' own perspective. The aim of this study was to explore users' experiences of participation in decisions in mental health services in Sweden, and the kinds of support that may promote participation. Constructivist Grounded Theory (CGT) was utilized to analyse group and individual interviews with 20 users with experience of serious mental illness. The core category that emerged in the analysis described a 'struggle to be perceived as a competent and equal person' while three related categories including being the underdog, being controlled and being omitted described the difficulties of participating in decisions. The data analysis resulted in a model that describes internal and external conditions that influence the promotion of participation in decision making. The findings offer new insights from a user perspective and these can be utilized to develop and investigate concrete methods in order to promote user's participation in decisions. © 2015 John Wiley & Sons Ltd.

Men's Knowledge About Maternal Serum Screening for Down Syndrome and their Attitude Towards Amniocentesis.

PubMed

Brajenović-Milić, Bojana; Dorčić, Tamara Martinac

2017-02-01

The present study aimed to assess (i) the impact of screening consultation on male partner's knowledge about second trimester maternal serum screening for Down syndrome and on their attitudes toward amniocentesis, and (ii) the concomitant effect of men's involvement in pregnancy on both knowledge and attitudes. The study included 164 men who accompanied their partners to the screening appointment. Knowledge Questionnaire and Partner's Involvement in Pregnancy Scale with two dimensions, support and distance, were administered. Involvement in pregnancy was determined using two factors; support and distance. Findings revealed a significant post-consultation improvement in men's knowledge about the test, but less-educated men and those who were more distanced from partner and pregnancy were less knowledgeable even post-consultation. Compared to before the consultation, most men had a positive attitude toward amniocentesis and were willing to suggest it to their partners in case of positive test results (77 % and 42 %, respectively). The remainder would either leave the decision to their partners (20 %) or were undecided (3 %). Higher perception of distance was associated with men's unwillingness to be involved in amniocentesis decisions, particularly before consultation. However, the consultation had considerable potential to engage men with this attitude in the decision-making process. The study highlights the need to change woman-oriented prenatal screening practices for Down syndrome to involve their male partners in the consultation.

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.

Human-Computer Interaction with Medical Decisions Support Systems

NASA Technical Reports Server (NTRS)

Adolf, Jurine A.; Holden, Kritina L.

1994-01-01

Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

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.

New Directions in Health Risk Assessment: A REACH for the Future?

EPA Science Inventory

Health risk assessments have been used to support many decisions in the US to reduce risks from pollutant exposures. These decisions have been highly successful in protecting public health despite uncertainty due to gaps in knowledge and methodological limitations. In recent yea...

A decision support model to understand route choice decisions and siting of facilities in emergency evacuation.

DOT National Transportation Integrated Search

2013-10-01

In this research, we present the results of a behavior model to capture different routing strategies executed by evacuees : during hurricane evacuation by using a randomparameter logitbased modeling approach. To the best of our knowledge, : thi...

Integrating local, expert, and practical knowledge in community remediation and revitalization

EPA Science Inventory

Researchers and natural resource managers often develop tools and methods to facilitate the inclusion of science in local environmental decision-making. The eternal hope is to find that model or concept that provides the “right” information to support these decisions....

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 Virtual Information-Action Workspace for Command and Control

NASA Astrophysics Data System (ADS)

Lintern, Gavan; Naikar, Neelam

2002-10-01

Information overload has become a critical challenge within military Command and Control. However, the problem is not so much one of too much information but of abundant information that is poorly organized and poorly represented. In addition, the capabilities to test the effects of decisions before they are implemented and to monitor the progress of events after a decision is implemented are primitive. A virtual information-action workspace could be designed to resolve these issues. The design of such a space would require a detailed understanding of the specific information needed to support decision making in Command and Control. That information can be obtained with the use of knowledge acquisition and knowledge representation tools from the field of applied cognitive psychology. In addition, it will be necessary to integrate forms for perception and action into a virtual space that will support access to the information and that will provide means for testing and implementing decisions. This paper presents a rationale for a virtual information-action workspace and outlines an approach to its design.

Clinical, information and business process modeling to promote development of safe and flexible software.

PubMed

Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn

2006-09-01

Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

Exploring Challenges and Opportunities of Coproduction: USDA Climate Hub Efforts to Integrate Coproduction with Applied Research and Decision Support Tool Development in the Northwest

NASA Astrophysics Data System (ADS)

Roesch-McNally, G.; Prendeville, H. R.

2017-12-01

A lack of coproduction, the joint production of new technologies or knowledge among technical experts and other groups, is arguably one of the reasons why much scientific information and resulting decision support systems are not very usable. Increasingly, public agencies and academic institutions are emphasizing the importance of coproduction of scientific knowledge and decision support systems in order to facilitate greater engagement between the scientific community and key stakeholder groups. Coproduction has been embraced as a way for the scientific community to develop actionable scientific information that will assist end users in solving real-world problems. Increasing the level of engagement and stakeholder buy-in to the scientific process is increasingly necessary, particularly in the context of growing politicization of science and the scientific process. Coproduction can be an effective way to build trust and can build-on and integrate local and traditional knowledge. Employing coproduction strategies may enable the development of more relevant and useful information and decision support tools that address stakeholder challenges at relevant scales. The USDA Northwest Climate Hub has increasingly sought ways to integrate coproduction in the development of both applied research projects and the development of decision support systems. Integrating coproduction, however, within existing institutions is not always simple, given that coproduction is often more focused on process than products and products are, for better or worse, often the primary focus of applied research and tool development projects. The USDA Northwest Climate Hub sought to integrate coproduction into our FY2017 call for proposal process. As a result we have a set of proposals and fledgling projects that fall along the engagement continuum (see Figure 1- attached). We will share the challenges and opportunities that emerged from this purposeful integration of coproduction into the work that we prioritized for funding. This effort highlights strategies for how federal agencies might consider how and whether to codify coproduction tenets into their collaborations and agenda setting.

The Lenfest Ocean Program's experience in building institutional support for connecting science and decision-making in marine systems

NASA Astrophysics Data System (ADS)

Bednarek, A.; Close, S.; Curran, K.; Hudson, C.

2017-12-01

Addressing contemporary sustainability challenges requires attention to the integration of scientific knowledge into decision-making and deliberation. However, this remains a challenge in practice. We contend that careful stewardship of this process of integration can result in positive, durable outcomes by reconciling the production and use of scientific knowledge, and improve its relevance and utility to decision-makers. We will share lessons learned from a grantmaking program that has addressed this challenge through programmatic innovations, including by supporting staff devoted to an intermediary role. Over the past 13 years, the Lenfest Ocean Program served in a boundary spanning role by integrating decision-makers into the scoping and outreach of program supported scientific research grants. Program staff engage with decision-makers and influencers to identify policy-relevant research questions and approaches, ensuring that the research direction addresses users' needs. As research progresses, the staff monitor the grant's progress to improve the match between the research and user needs. The process is resource-intensive, however, and raises interesting questions about the role and development of this kind of specialist within different kinds of institutions, including funding agencies. We suggest that nurturing this role as a practice and profession could ultimately help the scientific community more efficiently respond to sustainability challenges.

Knowledge-based commodity distribution planning

NASA Technical Reports Server (NTRS)

Saks, Victor; Johnson, Ivan

1994-01-01

This paper presents an overview of a Decision Support System (DSS) that incorporates Knowledge-Based (KB) and commercial off the shelf (COTS) technology components. The Knowledge-Based Logistics Planning Shell (KBLPS) is a state-of-the-art DSS with an interactive map-oriented graphics user interface and powerful underlying planning algorithms. KBLPS was designed and implemented to support skilled Army logisticians to prepare and evaluate logistics plans rapidly, in order to support corps-level battle scenarios. KBLPS represents a substantial advance in graphical interactive planning tools, with the inclusion of intelligent planning algorithms that provide a powerful adjunct to the planning skills of commodity distribution planners.

Counseling Model Application: A Student Career Development Guidance for Decision Maker and Consultation

NASA Astrophysics Data System (ADS)

Irwan; Gustientiedina; Sunarti; Desnelita, Yenny

2017-12-01

The purpose of this study is to design a counseling model application for a decision-maker and consultation system. This application as an alternative guidance and individual career development for students, that include career knowledge, planning and alternative options from an expert tool based on knowledge and rule to provide the solutions on student’s career decisions. This research produces a counseling model application to obtain the important information about student career development and facilitating individual student’s development through the service form, to connect their plan with their career according to their talent, interest, ability, knowledge, personality and other supporting factors. This application model can be used as tool to get information faster and flexible for the student’s guidance and counseling. So, it can help students in doing selection and making decision that appropriate with their choice of works.

Toward detecting deception in intelligent systems

NASA Astrophysics Data System (ADS)

Santos, Eugene, Jr.; Johnson, Gregory, Jr.

2004-08-01

Contemporary decision makers often must choose a course of action using knowledge from several sources. Knowledge may be provided from many diverse sources including electronic sources such as knowledge-based diagnostic or decision support systems or through data mining techniques. As the decision maker becomes more dependent on these electronic information sources, detecting deceptive information from these sources becomes vital to making a correct, or at least more informed, decision. This applies to unintentional disinformation as well as intentional misinformation. Our ongoing research focuses on employing models of deception and deception detection from the fields of psychology and cognitive science to these systems as well as implementing deception detection algorithms for probabilistic intelligent systems. The deception detection algorithms are used to detect, classify and correct attempts at deception. Algorithms for detecting unexpected information rely upon a prediction algorithm from the collaborative filtering domain to predict agent responses in a multi-agent system.

Exploring the oxygen supply and demand framework as a learning tool in undergraduate nursing education.

PubMed

Gillespie, Mary; Shackell, Eileen

2017-11-01

In nursing education, physiological concepts are typically presented within a body 'systems' framework yet learners are often challenged to apply this knowledge in the holistic and functional manner needed for effective clinical decision-making and safe patient care. A nursing faculty addressed this learning challenge by developing an advanced organizer as a conceptual and integrative learning tool to support learners in diverse learning environments and practice settings. A mixed methods research study was conducted that explored the effectiveness of the Oxygen Supply and Demand Framework as a learning tool in undergraduate nursing education. A pretest/post-test assessment and reflective journal were used to gather data. Findings indicated the Oxygen Supply and Demand Framework guided the development of pattern recognition and thinking processes and supported knowledge development, knowledge application and clinical decision-making. The Oxygen Supply and Demand Framework supports undergraduate students learning to provide safe and effective nursing care. Copyright © 2017 Elsevier Ltd. All rights reserved.

Developing an Initial Learning Progression for the Use of Evidence in Decision-Making Contexts

ERIC Educational Resources Information Center

Bravo-Torija, Beatriz; Jiménez-Aleixandre, María-Pilar

2018-01-01

This paper outlines an initial learning progression for the use of evidence to support scientific arguments in the context of decision-making. Use of evidence is a central feature of knowledge evaluation and, therefore, of argumentation. The proposal is based on the literature on argumentation and use of evidence in decision-making contexts. The…

Key principles for a national clinical decision support knowledge sharing framework: synthesis of insights from leading subject matter experts.

PubMed

Kawamoto, Kensaku; Hongsermeier, Tonya; Wright, Adam; Lewis, Janet; Bell, Douglas S; Middleton, Blackford

2013-01-01

To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework. As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework. Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model. Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC's Advancing CDS initiative. The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care.

[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.

Why bother with the brain? A role for decision neuroscience in understanding strategic variability.

PubMed

Venkatraman, Vinod

2013-01-01

Neuroscience, by its nature, seems to hold considerable promise for understanding the fundamental mechanisms of decision making. In recent years, several studies in the domain of "neuroeconomics" or "decision neuroscience" have provided important insights into brain function. Yet, the apparent success and value of each of these domains are frequently called into question by researchers in economics and behavioral decision making. Critics often charge that knowledge about the brain is unnecessary for understanding decision preferences. In this chapter, I contend that knowledge about underlying brain mechanisms helps in the development of biologically plausible models of behavior, which can then help elucidate the mechanisms underlying individual choice biases and strategic preferences. Using a novel risky choice paradigm, I will demonstrate that people vary in whether they adopt compensatory or noncompensatory rules in economic decision making. Importantly, neuroimaging studies using functional magnetic resonance imaging reveal that distinct neural mechanisms support variability in choices and variability in strategic preferences. Converging evidence from a study involving decisions between hypothetical stocks illustrates how knowledge about the underlying mechanisms can help inform neuroanatomical models of cognitive control. Last, I will demonstrate how knowledge about these underlying neural mechanisms can provide novel insights into the effects of decision states like sleep deprivation on decision preferences. Together, these findings suggest that neuroscience can play a critical role in creating robust and flexible models of real-world decision behavior. Copyright © 2013 Elsevier B.V. All rights reserved.

When Informationists Get Involved: the CHICA-GIS Project.

PubMed

Whipple, Elizabeth C; Odell, Jere D; Ralston, Rick K; Liu, Gilbert C

2013-01-01

Child Health Improvement through Computer Automation (CHICA) is a computer decision support system (CDSS) that interfaces with existing electronic medical record systems (EMRS) and delivers "just-in-time" patient-relevant guidelines to physicians during the clinical encounter and accurately captures structured data from all who interact with the system. "Delivering Geospatial Intelligence to Health Care Professionals (CHICA-GIS)" (1R01LM010923-01) expands the medical application of Geographic Information Systems (GIS) by integrating a geographic information system with CHICA. To provide knowledge management support for CHICA-GIS, three informationists at the Indiana University School of Medicine were awarded a supplement from the National Library Medicine. The informationists will enhance CHICA-GIS by: improving the accuracy and accessibility of information, managing and mapping the knowledge which undergirds the CHICA-GIS decision support tool, supporting community engagement and consumer health information outreach, and facilitating the dissemination of new CHICA-GIS research results and services.

Ludic Elicitation: Using Games for Knowledge Elicitation

ERIC Educational Resources Information Center

Cao, Yan

2014-01-01

Knowledge elicitation from human beings is important for many fields, such as decision support systems, risk communication, and customer preference studying. Traditional approaches include observations, questionnaires, structured and semi-structured interviews, and group discussions. Many publications have been studying different techniques for a…

Coordination of Individual and Organizational Planning for Natural Hazards (Invited)

NASA Astrophysics Data System (ADS)

Krantz, D. H.

2013-12-01

Decision making consists of constructing or selecting a plan. This is true at many levels of decision making: individuals or households, small groups, larger organizations, and governments. In each case, plans are constructed or selected taking account of the decision maker's prioritized set of active goals and the decision maker's beliefs about the probability or the extent to which each goal will be attained through a given plan. Planning for mitigation of or response to natural hazards can be improved if the plans of the many decision makers at multiple levels are coordinated. Government planning should ideally be informed by knowledge about the plans of businesses and non-profit organizations as well as knowledge about individual, household, and neighborhood plans. Similarly, plans at the individual and organizational levels should be informed by knowledge of others' plans at the same and at higher and lower levels of aggregation. Coordination can be impaired by differences in goals, differences in beliefs about the instrumentality of plans toward given goals, and also by ignorance of others' goals and plans. Good coordination requires incentives that promote sharing of plans, horizontally and vertically, and that alleviate conflicts in goals and conflicts in beliefs that will inevitably surface once plans are shared. Thus, four different kinds of decision aids are needed to improve natural hazard planning: mechanisms that support horizontal dissemination of plans, mechanisms that support vertical dissemination, mechanisms for examining goal conflicts and reducing these through plans that take others' goals into account, and mechanisms for examining belief conflicts.

Information and decision support needs in patients with type 2 diabetes.

PubMed

Weymann, Nina; Härter, Martin; Dirmaier, Jörg

2016-03-01

Diabetes and its sequelae cause a growing burden of morbidity and mortality. For many patients living with diabetes, the Internet is an important source of health information and support. In the course of the development of an Interactive Health Communication Application, combining evidence-based information with behavior change and decision support, we assessed the characteristics, information, and decision support needs of patients with type 2 diabetes.The needs assessment was performed in two steps. First, we conducted semi-structured interviews with 10 patients and seven physicians. In the second step, we developed a self-assessment questionnaire based on the results of the interviews and administered it to a new and larger sample of diabetes patients (N = 178). The questionnaire comprised four main sections: (1) Internet use and Internet experience, (2) diabetes knowledge, (3) relevant decisions and decision preferences, and (4) online health information needs. Descriptive data analyses were performed.In the questionnaire study, the patient sample was heterogeneous in terms of age, time since diagnosis, and glycemic control. (1) Most participants (61.7%) have searched the web for health information at least once. The majority (62%) of those who have used the web use it at least once per month. (2) Diabetes knowledge was scarce: Only a small percentage (1.9%) of the respondents answered all items of the knowledge questionnaire correctly. (3) The most relevant treatment decisions concerned glycemic control, oral medication, and acute complications. The most difficult treatment decision was whether to start insulin treatment. Of the respondents, 69.4 percent thought that medical decisions should be made by them and their doctor together. (4) The most important information needs concerned sequelae of diabetes, blood glucose control, and basic diabetes information.The Internet seems to be a feasible way to reach people with type 2 diabetes. The heterogeneity of the sample, especially with respect to diabetes knowledge, makes it clear that the projected Interactive Health Communication Application should tailor the content to the individual user, taking account of individual characteristics and preferences. A wide range of topics should be covered. Special attention should be paid to the advantages and disadvantages of insulin treatment and the fears and hopes associated with it. These results were taken into account when developing the Interactive Health Communication Application that is currently being evaluated in a randomized controlled trial (International Clinical Trials Registry DRKS00003322). © The Author(s) 2014.

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 Support Model for Introduction of Gamification Solution Using AHP

PubMed Central

2014-01-01

Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

Decision support model for introduction of gamification solution using AHP.

PubMed

Kim, Sangkyun

2014-01-01

Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

Informed Decision Making About Prostate Cancer Testing in Predominantly Immigrant Black Men: A Randomized Controlled Trial

PubMed Central

Lepore, Stephen J.; Wolf, Randi L.; Basch, Charles E.; Godfrey, Melissa; McGinty, Emma; Shmukler, Celia; Ullman, Ralph; Thomas, Nigel; Weinrich, Sally

2012-01-01

Background Decision support interventions have been developed to help men clarify their values and make informed decisions about prostate cancer testing, but they seldom target high-risk black and immigrant men. Purpose This study evaluated the efficacy of a decision support intervention focused on prostate cancer testing in a sample of predominantly immigrant black men. Methods Black men (N = 490) were randomized to tailored telephone education about prostate cancer testing or a control condition. Results Post-intervention, the intervention group had significantly greater knowledge, lower decision conflict, and greater likelihood of talking with their physician about prostate cancer testing than the control group. There were no significant intervention effects on prostate specific antigen testing, congruence between testing intention and behavior, or anxiety. Conclusions A tailored telephone decision support intervention can promote informed decision making about prostate cancer testing in black and predominantly immigrant men without increasing testing or anxiety. Clinical trial Registered in clinicaltrials.gov (NCT01415375) PMID:22825933

Developing an Environmental Decision Support System for Stream Management: the STREAMES Experience

NASA Astrophysics Data System (ADS)

Riera, J.; Argerich, A.; Comas, J.; Llorens, E.; Martí, E.; Godé, L.; Pargament, D.; Puig, M.; Sabater, F.

2005-05-01

Transferring research knowledge to stream managers is crucial for scientifically sound management. Environmental decision support systems are advocated as an effective means to accomplish this. STREAMES (STream REAach Management: an Expert System) is a decision tree based EDSS prototype developed within the context of an European project as a tool to assist water managers in the diagnosis of problems, detection of causes, and selection of management strategies for coping with stream degradation issues related mostly to excess nutrient availability. STREAMES was developed by a team of scientists, water managers, and experts in knowledge engineering. Although the tool focuses on management at the stream reach scale, it also incorporates a mass-balance catchment nutrient emission model and a simple GIS module. We will briefly present the prototype and share our experience in its development. Emphasis will be placed on the process of knowledge acquisition, the design process, the pitfalls and benefits of the communication between scientists and managers, and the potential for future development of STREAMES, particularly in the context of the EU Water Framework Directive.

Introduction: The Growing Importance of Traditional Forest-Related Knowledge

Treesearch

Ronald L. Trosper; John A. Parrotta

2012-01-01

The knowledge, innovations, and practices of local and indigenous communities have supported their forest-based livelihoods for countless generations. The role of traditional knowledge—and the bio-cultural diversity it sustains—is increasingly recognized as important by decision makers, conservation and development organizations, and the scientifi c community. However...

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

From open source communications to knowledge

NASA Astrophysics Data System (ADS)

Preece, Alun; Roberts, Colin; Rogers, David; Webberley, Will; Innes, Martin; Braines, Dave

2016-05-01

Rapid processing and exploitation of open source information, including social media sources, in order to shorten decision-making cycles, has emerged as an important issue in intelligence analysis in recent years. Through a series of case studies and natural experiments, focussed primarily upon policing and counter-terrorism scenarios, we have developed an approach to information foraging and framing to inform decision making, drawing upon open source intelligence, in particular Twitter, due to its real-time focus and frequent use as a carrier for links to other media. Our work uses a combination of natural language (NL) and controlled natural language (CNL) processing to support information collection from human sensors, linking and schematising of collected information, and the framing of situational pictures. We illustrate the approach through a series of vignettes, highlighting (1) how relatively lightweight and reusable knowledge models (schemas) can rapidly be developed to add context to collected social media data, (2) how information from open sources can be combined with reports from trusted observers, for corroboration or to identify con icting information; and (3) how the approach supports users operating at or near the tactical edge, to rapidly task information collection and inform decision-making. The approach is supported by bespoke software tools for social media analytics and knowledge management.

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

Knowledge Management and the Academy

ERIC Educational Resources Information Center

Cain, Timothy J.; Branin, Joseph J.; Sherman, W. Michael

2008-01-01

Universities and colleges generate extraordinary quantities of knowledge and innovation, but in many ways the academy struggles to keep pace with the digital revolution. Growing pressures are reshaping how universities must do business--students expecting enhanced access and support, administrators eager to make data-driven strategic decisions,…

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.

Does the Use of a Decision Aid Improve Decision Making in Prosthetic Heart Valve Selection? A Multicenter Randomized Trial.

PubMed

Korteland, Nelleke M; Ahmed, Yunus; Koolbergen, David R; Brouwer, Marjan; de Heer, Frederiek; Kluin, Jolanda; Bruggemans, Eline F; Klautz, Robert J M; Stiggelbout, Anne M; Bucx, Jeroen J J; Roos-Hesselink, Jolien W; Polak, Peter; Markou, Thanasie; van den Broek, Inge; Ligthart, Rene; Bogers, Ad J J C; Takkenberg, Johanna J M

2017-02-01

A Dutch online patient decision aid to support prosthetic heart valve selection was recently developed. A multicenter randomized controlled trial was conducted to assess whether use of the patient decision aid results in optimization of shared decision making in prosthetic heart valve selection. In a 5-center randomized controlled trial, patients were allocated to receive either standard preoperative care (control group) or additional access to the patient decision aid (intervention group). Legally capable adult patients accepted for elective isolated or combined aortic and mitral valve replacement were included. Primary outcome was preoperative decisional conflict (Decisional Conflict Scale); secondary outcomes included patient knowledge, involvement in valve selection, anxiety and depression, (valve-specific) quality of life, and regret. Out of 306 eligible patients, 155 were randomized (78 control and 77 intervention). Preoperative decisional conflict did not differ between the groups (34% versus 33%; P =0.834). Intervention patients felt better informed (median Decisional Conflict Scale informed subscore: 8 versus 17; P =0.046) and had a better knowledge of prosthetic valves (85% versus 68%; P =0.004). Intervention patients experienced less anxiety and depression (median Hospital Anxiety and Depression Scale score: 6 versus 9; P =0.015) and better mental well-being (mean Short Form Health Survey score: 54 versus 50; P =0.032). Three months postoperatively, valve-specific quality of life and regret did not differ between the groups. A patient decision aid to support shared decision making in prosthetic heart valve selection does not lower decisional conflict. It does result in more knowledgeable, better informed, and less anxious and depressed patients, with a better mental well-being. http://www.trialregister.nl. Unique identifier: NTR4350. © 2017 American Heart Association, Inc.

Improving Information Products for System 2 Decision Support

ERIC Educational Resources Information Center

Gibson, Neal

2010-01-01

The creation, maintenance, and management of Information Product (IP) systems that are used by organizations for complex decisions represent a unique set of challenges. These challenges are compounded when the purpose of such a systems is also for knowledge creation and dissemination. Information quality research to date has focused mainly upon…

A decision support tool for adaptive management of native prairie ecosystems

USGS Publications Warehouse

Hunt, Victoria M.; Jacobi, Sarah; Gannon, Jill J.; Zorn, Jennifer E.; Moore, Clinton; Lonsdorf, Eric V.

2016-01-01

The Native Prairie Adaptive Management initiative is a decision support framework that provides cooperators with management-action recommendations to help them conserve native species and suppress invasive species on prairie lands. We developed a Web-based decision support tool (DST) for the U.S. Fish and Wildlife Service and the U.S. Geological Survey initiative. The DST facilitates cross-organizational data sharing, performs analyses to improve conservation delivery, and requires no technical expertise to operate. Each year since 2012, the DST has used monitoring data to update ecological knowledge that it translates into situation-specific management-action recommendations (e.g., controlled burn or prescribed graze). The DST provides annual recommendations for more than 10,000 acres on 20 refuge complexes in four U.S. states. We describe how the DST promotes the long-term implementation of the program for which it was designed and may facilitate decision support and improve ecological outcomes of other conservation efforts.

Patients' experiences of communication and involvement in decision-making about atrial fibrillation treatment in consultations with nurses and physicians.

PubMed

Siouta, Eleni; Hellström Muhli, Ulla; Hedberg, Berith; Broström, Anders; Fossum, Bjöörn; Karlgren, Klas

2016-09-01

Insights in consultations across patient interactions with physicians and nurses are of vital importance for strengthening the patients' involvement in the treatment decision-making process. The experience of involvement and communication in decision-making from the patients' perspective has been sparsely explored. To examine how patients describe involvement in and communication about decision-making regarding treatment in consultations with nurses and physicians. Twenty-two patients with atrial fibrillation (AF), aged 37-90 years, were interviewed directly after their consultations with nurses and physicians in outpatient AF clinics in six Swedish hospitals. In consultations with nurses, the patients felt involved when obtaining clarifications about AF as a disease and its treatment and when preparing for and building up confidence in decision-making. In consultations with physicians, the patients felt involved when they could cooperate in decision-making, when acquiring knowledge, and when they felt that they were being understood. One shared category was found in consultations with both nurses and physicians, and the patients felt involved when they had a sense of trust and felt secure during and between consultations. Patients with AF stated that they would need to acquire knowledge and build up confidence and ability in order to be effectively involved in the decision-making about treatment. Despite not being actively involved in decision-making, patients felt involved through experiencing supportive and confirming communication. Attention must be given to the relationship with the patient to create the conditions for patient involvement in the consultation. This can be achieved through supportive communication attempting to create a feeling of clarity and building confidence. This will support involvement in decision-making concerning AF treatment and feelings of being understood and of trust in physicians and/or nurses. © 2015 Nordic College of Caring Science.

Formal ontologies in biomedical knowledge representation.

PubMed

Schulz, S; Jansen, L

2013-01-01

Medical decision support and other intelligent applications in the life sciences depend on increasing amounts of digital information. Knowledge bases as well as formal ontologies are being used to organize biomedical knowledge and data. However, these two kinds of artefacts are not always clearly distinguished. Whereas the popular RDF(S) standard provides an intuitive triple-based representation, it is semantically weak. Description logics based ontology languages like OWL-DL carry a clear-cut semantics, but they are computationally expensive, and they are often misinterpreted to encode all kinds of statements, including those which are not ontological. We distinguish four kinds of statements needed to comprehensively represent domain knowledge: universal statements, terminological statements, statements about particulars and contingent statements. We argue that the task of formal ontologies is solely to represent universal statements, while the non-ontological kinds of statements can nevertheless be connected with ontological representations. To illustrate these four types of representations, we use a running example from parasitology. We finally formulate recommendations for semantically adequate ontologies that can efficiently be used as a stable framework for more context-dependent biomedical knowledge representation and reasoning applications like clinical decision support systems.

Tailoring and field-testing the use of a knowledge translation peer support shared decision making strategy with First Nations, Inuit and Métis people making decisions about their cancer care: a study protocol.

PubMed

Jull, Janet; Mazereeuw, Maegan; Sheppard, Amanada; Kewayosh, Alethea; Steiner, Richard; Graham, Ian D

2018-01-01

Tailoring and testing a peer support decision making strategy with First Nations, Inuit and Métis people making decisions about their cancer care: A study protocol.First Nations, Inuit and Métis (FNIM) people face higher risks for cancer compared to non-FNIM populations. They also face cultural barriers to health service use. Within non-FNIM populations an approach to health decision making, called shared decision making (SDM), has been found to improve the participation of people in their healthcare. Peer support with SDM further improves these benefits. The purpose of this study is to tailor and test a peer support SDM strategy with community support workers to increase FNIM people's participation in their cancer care.This project has two phases that will be designed and conducted with a Steering Committee that includes members of the FNIM and cancer care communities. First, a peer support SDM strategy will be tailored to meet the needs of cancer system users who are receiving care in urban settings, and training in the SDM strategy developed for community support workers. Three communities will be supported for participation in the study and community support workers who are peers from each community will be trained to use the SDM strategy.Next, each community support worker will work with a community member who has a diagnosis of cancer or who has supported a family member with cancer. Each community support worker and community member pair will use the SDM strategy. The participation and experience of the community support worker and community member will be evaluated.The research will be used to develop strategies to support people who are making decisions about their health. Tailoring and field-testing the use of a knowledge translation peer support shared decision making strategy with First Nations, Inuit and Métis people making decisions about their cancer care: A study protocol Background First Nations, Inuit and Métis ("FNIM") people face increased cancer risks in relation to general populations and experience barriers to health service use. Shared decision making (SDM) has been found to improve peoples' participation and outcomes in healthcare and peer support with SDM further improves these benefits. The purpose of this study is to tailor and then field test, by and with FNIM communities, a peer support SDM strategy for use in cancer care. Methods This project has 2 theory-driven phases and 5 stages (a-e). A core research team that includes members of the Aboriginal Cancer Control Unit of Cancer Care Ontario communities and academic researchers, will work with a Steering Committee. In phase 1 , (stage a) a peer support SDM strategy will be tailored to meet the needs of cancer system users who are receiving care in urban settings and (stage b), training developed that will i) introduce participant communities to SDM, and ii) train community support workers (CSWs) within these communities. Next (stage c), three communities will be approached for voluntary participation in the study. These communities will be introduced to SDM in community meetings, and if in agreement then CSWs from each community will be recruited to participate in the study. One volunteer CSW from each community will be trained to use the peer support SDM strategy to enable phase 2 (field test of the peer support SDM strategy).During phase 2 (stage d), each CSW will be matched to a volunteer community member who has had a diagnosis of cancer or has supported a family member with cancer and is familiar with Ontario cancer systems. Each CSW-community member pair (3 to 4 pairs/community) will use the tailored peer support SDM strategy; their interaction will be audio-recorded and their participation and experience evaluated (total of 9 to 12 interviews). As well (stage e), data will be collected on health systems' factors related to the use of the peer support SDM strategy. Discussion Findings will develop peer support SDM strategies to enhance participation of FNIM people in cancer care decisions, advance knowledge translation science, and support a proposal to conduct a multi-site implementation trial.

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

Bridging the guideline implementation gap: a systematic, document-centered approach to guideline implementation.

PubMed

Shiffman, Richard N; Michel, George; Essaihi, Abdelwaheb; Thornquist, Elizabeth

2004-01-01

A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems. This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification. The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institute's guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system. Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge.

Knowledge transfer and exchange processes for environmental health issues in Canadian Aboriginal communities.

PubMed

Jack, Susan M; Brooks, Sandy; Furgal, Chris M; Dobbins, Maureen

2010-02-01

Within Canadian Aboriginal communities, the process for utilizing environmental health research evidence in the development of policies and programs is not well understood. This fundamental qualitative descriptive study explored the perceptions of 28 environmental health researchers, senior external decision-makers and decision-makers working within Aboriginal communities about factors influencing knowledge transfer and exchange, beliefs about research evidence and Traditional Knowledge and the preferred communication channels for disseminating and receiving evidence. The results indicate that collaborative relationships between researchers and decision-makers, initiated early and maintained throughout a research project, promote both the efficient conduct of a study and increase the likelihood of knowledge transfer and exchange. Participants identified that empirical research findings and Traditional Knowledge are different and distinct types of evidence that should be equally valued and used where possible to provide a holistic understanding of environmental issues and support decisions in Aboriginal communities. To facilitate the dissemination of research findings within Aboriginal communities, participants described the elements required for successfully crafting key messages, locating and using credible messengers to deliver the messages, strategies for using cultural brokers and identifying the communication channels commonly used to disseminate and receive this type of information.

Knowledge Transfer and Exchange Processes for Environmental Health Issues in Canadian Aboriginal Communities

PubMed Central

Jack, Susan M.; Brooks, Sandy; Furgal, Chris M.; Dobbins, Maureen

2010-01-01

Within Canadian Aboriginal communities, the process for utilizing environmental health research evidence in the development of policies and programs is not well understood. This fundamental qualitative descriptive study explored the perceptions of 28 environmental health researchers, senior external decision-makers and decision-makers working within Aboriginal communities about factors influencing knowledge transfer and exchange, beliefs about research evidence and Traditional Knowledge and the preferred communication channels for disseminating and receiving evidence. The results indicate that collaborative relationships between researchers and decision-makers, initiated early and maintained throughout a research project, promote both the efficient conduct of a study and increase the likelihood of knowledge transfer and exchange. Participants identified that empirical research findings and Traditional Knowledge are different and distinct types of evidence that should be equally valued and used where possible to provide a holistic understanding of environmental issues and support decisions in Aboriginal communities. To facilitate the dissemination of research findings within Aboriginal communities, participants described the elements required for successfully crafting key messages, locating and using credible messengers to deliver the messages, strategies for using cultural brokers and identifying the communication channels commonly used to disseminate and receive this type of information. PMID:20616996

A feature dictionary supporting a multi-domain medical knowledge base.

PubMed

Naeymi-Rad, F

1989-01-01

Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

Student Achievement Effects of Technology-Supported Remediation of Understanding of Fractions

ERIC Educational Resources Information Center

Ross, John A.; Bruce, Catherine D.

2009-01-01

Students have difficulty learning fractions, and problems in understanding fractions persist into adulthood, with moderate to severe consequences for everyday and occupational decision-making. Remediation of student misconceptions is hampered by deficiencies in teachers' knowledge of the discipline and pedagogical content knowledge. We theorized…

Adoption of clinical decision support systems in a developing country: Antecedents and outcomes of physician's threat to perceived professional autonomy.

PubMed

Esmaeilzadeh, Pouyan; Sambasivan, Murali; Kumar, Naresh; Nezakati, Hossein

2015-08-01

The basic objective of this research is to study the antecedents and outcomes of professional autonomy which is a central construct that affects physicians' intention to adopt clinical decision support systems (CDSS). The antecedents are physicians' attitude toward knowledge sharing and interactivity perception (about CDSS) and the outcomes are performance expectancy and intention to adopt CDSS. Besides, we include (1) the antecedents of attitude toward knowledge sharing-subjective norms, social factors and OCB (helping behavior) and (2) roles of physicians' involvement in decision making, computer self-efficacy and effort expectancy in our framework. Data from a stratified sample of 335 Malaysian physicians working in 12 public and private hospitals in Malaysia were collected to test the hypotheses using Structural Equation Modeling (SEM). The important findings of our research are: (1) factors such as perceived threat to professional autonomy, performance expectancy, and physicians' involvement in making decision about CDSS have significant impact on physicians' intention to adopt CDSS; (2) physicians' attitude toward knowledge sharing, interactivity perception and computer self-efficacy of physicians play a crucial role in influencing their perceived threat to professional autonomy; and (3) social network, shared goals and OCB (helping behavior) impact physicians' attitude toward knowledge sharing. The findings provide a comprehensive understanding of the factors that influence physicians' intention to adopt CDSS in a developing country. The results can help hospital managers manage CDSS implementation in an effective manner. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Key principles for a national clinical decision support knowledge sharing framework: synthesis of insights from leading subject matter experts

PubMed Central

Hongsermeier, Tonya; Wright, Adam; Lewis, Janet; Bell, Douglas S; Middleton, Blackford

2013-01-01

Objective To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework. Materials and methods As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework. Results Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model. Discussion Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC's Advancing CDS initiative. Conclusion The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care. PMID:22865671

Developing quality indicators and auditing protocols from formal guideline models: knowledge representation and transformations.

PubMed

Advani, Aneel; Goldstein, Mary; Shahar, Yuval; Musen, Mark A

2003-01-01

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a model representation and algorithm for deriving structured quality indicators and auditing protocols from formalized specifications of guidelines used in decision support systems. We apply the model and algorithm to the assessment of physician concordance with a guideline knowledge model for hypertension used in a decision-support system. The properties of our solution include the ability to derive automatically context-specific and case-mix-adjusted quality indicators that can model global or local levels of detail about the guideline parameterized by defining the reliability of each indicator or element of the guideline.

Treatment decision-making in ductal carcinoma in situ: A mixed methods systematic review of women's experiences and information needs.

PubMed

Rutherford, Claudia; Mercieca-Bebber, Rebecca; Butow, Phyllis; Wu, Jenny Liang; King, Madeleine T

2017-09-01

Decision-making in ductal carcinoma in situ (DCIS) is complex due to the heterogeneity of the disease. This study aimed to understand women's experience of making treatment decisions for DCIS, their information and support needs, and factors that influenced decisions. We searched six electronic databases, conference proceedings, and key authors. Two reviewers independently applied inclusion and quality criteria, and extracted findings. Thematic analysis was used to combine and summarise findings. We identified six themes and 28 subthemes from 18 studies. Women with DCIS have knowledge deficits about DCIS, experience anxiety related to information given at diagnosis and the complexity of decision-making, and have misconceptions regarding risks and outcomes of treatment. Women's decisions are influenced by their understanding of risk, the clinical features of their DCIS, and the benefits and harms of treatment options. Women are dissatisfied with the decisional support available. Informed and shared decision-making in this complex decision setting requires clear communication of information specific to DCIS and individual's, as well as decision support for patients and clinicians. This approach would educate patients and clinicians, and assist clinicians in supporting patients to an evidence-based treatment plan that aligns with individual values and pReferences. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting species distributions for conservation decisions

PubMed Central

Guisan, Antoine; Tingley, Reid; Baumgartner, John B; Naujokaitis-Lewis, Ilona; Sutcliffe, Patricia R; Tulloch, Ayesha I T; Regan, Tracey J; Brotons, Lluis; McDonald-Madden, Eve; Mantyka-Pringle, Chrystal; Martin, Tara G; Rhodes, Jonathan R; Maggini, Ramona; Setterfield, Samantha A; Elith, Jane; Schwartz, Mark W; Wintle, Brendan A; Broennimann, Olivier; Austin, Mike; Ferrier, Simon; Kearney, Michael R; Possingham, Hugh P; Buckley, Yvonne M

2013-01-01

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. PMID:24134332

Streamlining the Discovery, Evaluation, and Integration of Data, Models, and Decision Support Systems: a Big Picture View

EPA Science Inventory

21st century environmental problems are wicked and require holistic systems thinking and solutions that integrate social and economic knowledge with knowledge of the environment. Computer-based technologies are fundamental to our ability to research and understand the relevant sy...

Data Mining and Knowledge Management in Higher Education -Potential Applications.

ERIC Educational Resources Information Center

Luan, Jing

This paper introduces a new decision support tool, data mining, in the context of knowledge management. The most striking features of data mining techniques are clustering and prediction. The clustering aspect of data mining offers comprehensive characteristics analysis of students, while the predicting function estimates the likelihood for a…

GODDESS: A Goal-Directed Decision Structuring System.

DTIC Science & Technology

1980-06-01

differ- ent support techniques. From a practical viewpoint, though, the major drawback of manual interviews is their length and cost. Since real - time ...conducting his future inquiries. A direct man-machine interface could provide three distinct advantages. First, it offers the capability of real - time ...knowledge in tree form. In many real -world applications, the decision maker may not perceive a problem in the form of a time sequence of decision

Data mining in child welfare.

PubMed

Schoech, D; Quinn, A; Rycraft, J R

2000-01-01

Data mining is the sifting through of voluminous data to extract knowledge for decision making. This article illustrates the context, concepts, processes, techniques, and tools of data mining, using statistical and neural network analyses on a dataset concerning employee turnover. The resulting models and their predictive capability, advantages and disadvantages, and implications for decision support are highlighted.

Patients' perceptions and attitudes on recurrent prostate cancer and hormone therapy: Qualitative comparison between decision-aid and control groups.

PubMed

Gorawara-Bhat, Rita; O'Muircheartaigh, Siobhan; Mohile, Supriya; Dale, William

2017-09-01

To compare patients' attitudes towards recurrent prostate cancer (PCa) and starting hormone therapy (HT) treatment in two groups-Decision-Aid (DA) (intervention) and Standard-of-care (SoC) (Control). The present research was conducted at three academic clinics-two in the Midwest and one in the Northeast U.S. Patients with biochemical recurrence of PCa (n=26) and follow-up oncology visits meeting inclusion criteria were randomized to either the SoC or DA intervention group prior to their consultation. Analysts were blinded to group assignment. Semi-structured phone interviews with patients were conducted 1-week post consultation. Interviews were audio-taped and transcribed. Qualitative analytic techniques were used to extract salient themes and conduct a comparative analysis of the two groups. Four salient themes emerged-1) knowledge acquisition, 2) decision-making style, 3) decision-making about timing of HT, and 4) anxiety-coping mechanisms. A comparative analysis showed that patients receiving the DA intervention had a better comprehension of Prostate-specific antigen (PSA), an improved understanding of HT treatment implications, an external locus-of-control, participation in shared decision-making and, support-seeking for anxiety reduction. In contrast, SoC patients displayed worse comprehension of PSA testing and HT treatment implications, internal locus-of-control, unilateral involvement in knowledge-seeking and decision-making, and no support-seeking for anxiety-coping. The DA was more effective than the SoC group in helping PCa patients understand the full implications of PSA testing and treatment; motivating shared decision-making, and support-seeking for anxiety relief. DA DVD interventions can be a useful patient education tool for bringing higher quality decision-making to prostate cancer care. Copyright © 2017 Elsevier Ltd. All rights reserved.

Shared decision making in Swedish community mental health services - an evaluation of three self-reporting instruments.

PubMed

Rosenberg, David; Schön, Ulla-Karin; Nyholm, Maria; Grim, Katarina; Svedberg, Petra

2017-04-01

Despite the potential impact of shared decision making on users satisfaction with care and quality in health care decisions, there is a lack of knowledge and skills regarding how to work with shared decision making among health care providers. The aim of this study was to evaluate the psychometric properties of three instruments that measure varied dimensions of shared decision making, based on self-reports by clients, in a Swedish community mental health context. The study sample consisted of 121 clients with experience of community mental health care, and involved in a wide range of decisions regarding both social support and treatment. The questionnaires were examined for face and content validity, internal consistency, test-retest reliability and construct validity. The instruments displayed good face and content validity, satisfactory internal consistency and a moderate to good level of stability in test-retest reliability with fair to moderate construct correlations, in a sample of clients with serious mental illness and experience of community mental health services in Sweden. The questionnaires are considered to be relevant to the decision making process, user-friendly and appropriate in a Swedish community mental health care context. They functioned well in settings where non-medical decisions, regarding social and support services, are the primary focus. The use of instruments that measure various dimensions of the self-reported experience of clients, can be a key factor in developing knowledge of how best to implement shared decision making in mental health services.

Indigenous knowledge management to enhance community resilience to tsunami risk: lessons learned from Smong traditions in Simeulue island, Indonesia

NASA Astrophysics Data System (ADS)

Rahman, A.; Sakurai, A.; Munadi, K.

2017-02-01

Knowledge accumulation and production embedded in communities through social interactions meant that the Smong tradition of indigenous knowledge of tsunami risk successfully alerted people to the 2004 tsunami, on the island of Simeulue, in Aceh, Indonesia. Based on this practical example, an indigenous management model was developed for Smong information. This knowledge management method involves the transformation of indigenous knowledge into applicable ways to increase community resilience, including making appropriate decisions and taking action in three disaster phases. First, in the pre-disaster stage, the community needs to be willing to mainstream and integrate indigenous knowledge of disaster risk reduction issues into related activities. Second, during disasters, the Smong tradition should make the community able to think clearly, act based on informed decisions, and protect themselves and others by using their indigenous knowledge. Last, in the post-disaster phase, the community needs to be strong enough to face challenges and support each other and “building back better” efforts, using local resources. The findings for the Smong tradition provide valuable knowledge about community resilience. Primary community resilience to disasters is strongly related to existing knowledge that triggers appropriate decisions and actions during pre-disaster, disaster, and post-disaster phases.

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

NASA Astrophysics Data System (ADS)

Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

Impact of a Lung Cancer Screening Counseling and Shared Decision-Making Visit.

PubMed

Mazzone, Peter J; Tenenbaum, Amanda; Seeley, Meredith; Petersen, Hilary; Lyon, Christina; Han, Xiaozhen; Wang, Xiao-Feng

2017-03-01

Lung cancer screening is a complex balance of benefits and harms. A counseling and shared decision-making visit has been mandated to assist patients with the decision about participation in screening. To our knowledge, the impact of this visit on patient understanding and decisions has not been studied. We developed a centralized counseling and shared decision-making visit for our lung cancer screening program. The visit included confirmation of eligibility for screening, education supported by a narrated slide show, individualized risk assessment with a decision aid, time for answering questions, and data collection. We surveyed consecutive patients prior to the visit, immediately after the visit, and 1 month after the visit to determine the impact of the visit on their knowledge. Twenty-three of 423 patients (5.4%) who had a visit did not proceed to the screening CT scan. One hundred twenty-five consecutive patients completed the initial survey, 122 completed the postvisit survey, and 113 completed the 1-month follow-up survey. Prior to the visit, the patients had a poor level of understanding about the age and smoking eligibility criteria (8.8% and 13.6% correct, respectively) and the benefits and harms of screening (55.2% and 38.4% correct, respectively). There was a significant improvement in knowledge noted after the visit for all questions (P = .03 to P < .0001). Knowledge waned by the 1-month follow-up but remained higher than it was before the visit. A centralized counseling and shared decision-making visit impacts the patient's knowledge about the eligibility criteria, benefits, and harms of lung cancer screening with LDCT, helping patients make value-based decisions. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Knowledge Co-production Strategies for Water Resources Modeling and Decision Making

NASA Astrophysics Data System (ADS)

Gober, P.

2016-12-01

The limited impact of scientific information on policy making and climate adaptation in North America has raised awareness of the need for new modeling strategies and knowledge transfer processes. This paper outlines the rationale for a new paradigm in water resources modeling and management, using examples from the USA and Canada. Principles include anticipatory modeling, complex system dynamics, decision making under uncertainty, visualization, capacity to represent and manipulate critical trade-offs, stakeholder engagement, local knowledge, context-specific activities, social learning, vulnerability analysis, iterative and collaborative modeling, and the concept of a boundary organization. In this framework, scientists and stakeholders are partners in the production and dissemination of knowledge for decision making, and local knowledge is fused with scientific observation and methodology. Discussion draws from experience in building long-term collaborative boundary organizations in Phoenix, Arizona in the USA and the Saskatchewan River Basin (SRB) in Canada. Examples of boundary spanning activities include the use of visualization, the concept of a decision theater, infrastructure to support social learning, social networks, and reciprocity, simulation modeling to explore "what if" scenarios of the future, surveys to elicit how water problems are framed by scientists and stakeholders, and humanistic activities (theatrical performances, art exhibitions, etc.) to draw attention to local water issues. The social processes surrounding model development and dissemination are at least as important as modeling assumptions, procedures, and results in determining whether scientific knowledge will be used effectively for water resources decision making.

Decisional needs assessment of patients with complex care needs in primary care: a participatory systematic mixed studies review protocol

PubMed Central

Pluye, Pierre; Légaré, France; Haggerty, Jeannie; Gore, Genevieve C; Sherif, Reem El; Poitras, Marie-Ève; Beaulieu, Marie-Claude; Beaulieu, Marie-Dominique; Bush, Paula L; Couturier, Yves; Débarges, Béatrice; Gagnon, Justin; Giguère, Anik; Grad, Roland; Granikov, Vera; Goulet, Serge; Hudon, Catherine; Kremer, Bernardo; Kröger, Edeltraut; Kudrina, Irina; Lebouché, Bertrand; Loignon, Christine; Lussier, Marie-Thérèse; Martello, Cristiano; Nguyen, Quynh; Pratt, Rebekah; Rihoux, Benoit; Rosenberg, Ellen; Samson, Isabelle; Senn, Nicolas; Li Tang, David; Tsujimoto, Masashi; Vedel, Isabelle; Ventelou, Bruno; Wensing, Michel; Bigras, Magali

2017-01-01

Introduction Patients with complex care needs (PCCNs) often suffer from combinations of multiple chronic conditions, mental health problems, drug interactions and social vulnerability, which can lead to healthcare services overuse, underuse or misuse. Typically, PCCNs face interactional issues and unmet decisional needs regarding possible options in a cascade of interrelated decisions involving different stakeholders (themselves, their families, their caregivers, their healthcare practitioners). Gaps in knowledge, values clarification and social support in situations where options need to be deliberated hamper effective decision support interventions. This review aims to (1) assess decisional needs of PCCNs from the perspective of stakeholders, (2) build a taxonomy of these decisional needs and (3) prioritise decisional needs with knowledge users (clinicians, patients and managers). Methods and analysis This review will be based on the interprofessional shared decision making (IP-SDM) model and the Ottawa Decision Support Framework. Applying a participatory research approach, we will identify potentially relevant studies through a comprehensive literature search; select relevant ones using eligibility criteria inspired from our previous scoping review on PCCNs; appraise quality using the Mixed Methods Appraisal Tool; conduct a three-step synthesis (sequential exploratory mixed methods design) to build taxonomy of key decisional needs; and integrate these results with those of a parallel PCCNs’ qualitative decisional need assessment (semistructured interviews and focus group with stakeholders). Ethics and dissemination This systematic review, together with the qualitative study (approved by the Centre Intégré Universitaire de Santé et Service Sociaux du Saguenay-Lac-Saint-Jean ethical committee), will produce a working taxonomy of key decisional needs (ontological contribution), to inform the subsequent user-centred design of a support tool for addressing PCCNs’ decisional needs (practical contribution). We will adapt the IP-SDM model, normally dealing with a single decision, for PCCNs who experience cascade of decisions involving different stakeholders (theoretical contribution). Knowledge users will facilitate dissemination of the results in the Canadian primary care network. PROSPERO registration number CRD42015020558. PMID:29133314

Decisional needs assessment of patients with complex care needs in primary care: a participatory systematic mixed studies review protocol.

PubMed

Bujold, Mathieu; Pluye, Pierre; Légaré, France; Haggerty, Jeannie; Gore, Genevieve C; Sherif, Reem El; Poitras, Marie-Eve; Beaulieu, Marie-Claude; Beaulieu, Marie-Dominique; Bush, Paula L; Couturier, Yves; Débarges, Beatrice; Gagnon, Justin; Giguère, Anik; Grad, Roland; Granikov, Vera; Goulet, Serge; Hudon, Catherine; Kremer, Bernardo; Kröger, Edeltraut; Kudrina, Irina; Lebouché, Bertrand; Loignon, Christine; Lussier, Marie-Therese; Martello, Cristiano; Nguyen, Quynh; Pratt, Rebekah; Rihoux, Benoit; Rosenberg, Ellen; Samson, Isabelle; Senn, Nicolas; Li Tang, David; Tsujimoto, Masashi; Vedel, Isabelle; Ventelou, Bruno; Wensing, Michel

2017-11-12

Patients with complex care needs (PCCNs) often suffer from combinations of multiple chronic conditions, mental health problems, drug interactions and social vulnerability, which can lead to healthcare services overuse, underuse or misuse. Typically, PCCNs face interactional issues and unmet decisional needs regarding possible options in a cascade of interrelated decisions involving different stakeholders (themselves, their families, their caregivers, their healthcare practitioners). Gaps in knowledge, values clarification and social support in situations where options need to be deliberated hamper effective decision support interventions. This review aims to (1) assess decisional needs of PCCNs from the perspective of stakeholders, (2) build a taxonomy of these decisional needs and (3) prioritise decisional needs with knowledge users (clinicians, patients and managers). This review will be based on the interprofessional shared decision making (IP-SDM) model and the Ottawa Decision Support Framework. Applying a participatory research approach, we will identify potentially relevant studies through a comprehensive literature search; select relevant ones using eligibility criteria inspired from our previous scoping review on PCCNs; appraise quality using the Mixed Methods Appraisal Tool; conduct a three-step synthesis (sequential exploratory mixed methods design) to build taxonomy of key decisional needs; and integrate these results with those of a parallel PCCNs' qualitative decisional need assessment (semistructured interviews and focus group with stakeholders). This systematic review, together with the qualitative study (approved by the Centre Intégré Universitaire de Santé et Service Sociaux du Saguenay-Lac-Saint-Jean ethical committee), will produce a working taxonomy of key decisional needs (ontological contribution), to inform the subsequent user-centred design of a support tool for addressing PCCNs' decisional needs (practical contribution). We will adapt the IP-SDM model, normally dealing with a single decision, for PCCNs who experience cascade of decisions involving different stakeholders (theoretical contribution). Knowledge users will facilitate dissemination of the results in the Canadian primary care network. CRD42015020558. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Digital Framework to Support Providers and Patients in Diabetes Related Behavior Modification.

PubMed

Abidi, Samina; Vallis, Michael; Piccinini-Vallis, Helena; Imran, Syed Ali; Abidi, Syed Sibte Raza

2017-01-01

We present Diabetes Web-Centric Information and Support Environment (D-WISE) that features: (a) Decision support tool to assist family physicians to administer Behavior Modification (BM) strategies to patients; and (b) Patient BM application that offers BM strategies and motivational interventions to engage patients. We take a knowledge management approach, using semantic web technologies, to model the social cognition theory constructs, Canadian diabetes guidelines and BM protocols used locally, in terms of a BM ontology that drives the BM decision support to physicians and BM strategy adherence monitoring and messaging to patients. We present the qualitative analysis of D-WISE usability by both physicians and patients.

Developing a knowledge base to support the annotation of ultrasound images of ectopic pregnancy.

PubMed

Dhombres, Ferdinand; Maurice, Paul; Friszer, Stéphanie; Guilbaud, Lucie; Lelong, Nathalie; Khoshnood, Babak; Charlet, Jean; Perrot, Nicolas; Jauniaux, Eric; Jurkovic, Davor; Jouannic, Jean-Marie

2017-01-31

Ectopic pregnancy is a frequent early complication of pregnancy associated with significant rates of morbidly and mortality. The positive diagnosis of this condition is established through transvaginal ultrasound scanning. The timing of diagnosis depends on the operator expertise in identifying the signs of ectopic pregnancy, which varies dramatically among medical staff with heterogeneous training. Developing decision support systems in this context is expected to improve the identification of these signs and subsequently improve the quality of care. In this article, we present a new knowledge base for ectopic pregnancy, and we demonstrate its use on the annotation of clinical images. The knowledge base is supported by an application ontology, which provides the taxonomy, the vocabulary and definitions for 24 types and 81 signs of ectopic pregnancy, 484 anatomical structures and 32 technical elements for image acquisition. The knowledge base provides a sign-centric model of the domain, with the relations of signs to ectopic pregnancy types, anatomical structures and the technical elements. The evaluation of the ontology and knowledge base demonstrated a positive feedback from a panel of 17 medical users. Leveraging these semantic resources, we developed an application for the annotation of ultrasound images. Using this application, 6 operators achieved a precision of 0.83 for the identification of signs in 208 ultrasound images corresponding to 35 clinical cases of ectopic pregnancy. We developed a new ectopic pregnancy knowledge base for the annotation of ultrasound images. The use of this knowledge base for the annotation of ultrasound images of ectopic pregnancy showed promising results from the perspective of clinical decision support system development. Other gynecological disorders and fetal anomalies may benefit from our approach.

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

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

Algorithm for decision support as the tool for control system of industries with variable assortment of products

NASA Astrophysics Data System (ADS)

Ladaniuk, Anatolii; Ivashchuk, Viacheslav; Kisała, Piotr; Askarova, Nursanat; Sagymbekova, Azhar

2015-12-01

Conditions of diversification of enterprise products are involving for changes of higher levels of management hierarchy, so it's leading by tasks correcting and changing schedule for operating of production plans. Ordinary solve by combination of enterprise resource are planning and management execution system often has exclusively statistical content. So, the development of decision support system, that helps to use knowledge about subject for capabilities estimating and order of operation of production object is relevant in this time.

Implementation of a cystic fibrosis lung transplant referral patient decision aid in routine clinical practice: an observational study.

PubMed

Stacey, Dawn; Vandemheen, Katherine L; Hennessey, Rosamund; Gooyers, Tracy; Gaudet, Ena; Mallick, Ranjeeta; Salgado, Josette; Freitag, Andreas; Berthiaume, Yves; Brown, Neil; Aaron, Shawn D

2015-02-07

The decision to have lung transplantation as treatment for end-stage lung disease from cystic fibrosis (CF) has benefits and serious risks. Although patient decision aids are effective interventions for helping patients reach a quality decision, little is known about implementing them in clinical practice. Our study evaluated a sustainable approach for implementing a patient decision aid for adults with CF considering referral for lung transplantation. A prospective pragmatic observational study was guided by the Knowledge-to-Action Framework. Healthcare professionals in all 23 Canadian CF clinics were eligible. We surveyed participants regarding perceived barriers and facilitators to patient decision aid use. Interventions tailored to address modifiable identified barriers included training, access to decision aids, and conference calls. The primary outcome was >80% use of the decision aid in year 2. Of 23 adult CF clinics, 18 participated (78.2%) and 13 had healthcare professionals attend training. Baseline barriers were healthcare professionals' inadequate knowledge for supporting patients making decisions (55%), clarifying patients' values for outcomes of options (58%), and helping patients handle conflicting views of others (71%). Other barriers were lack of time (52%) and needing to change how transplantation is discussed (42%). Baseline facilitators were healthcare professionals feeling comfortable discussing bad transplantation outcomes (74%), agreeing the decision aid would be easy to experiment with (71%) and use in the CF clinic (87%), and agreeing that using the decision aid would not require reorganization of the CF clinic (90%). After implementing the decision aid with interventions tailored to the barriers, decision aid use increased from 29% at baseline to 85% during year 1 and 92% in year 2 (p < 0.001). Compared to baseline, more healthcare professionals at the end of the study were confident in supporting decision-making (p = 0.03) but continued to feel inadequate ability with supporting patients to handle conflicting views (p = 0.01). Most Canadian CF clinics agreed to participate in the study. Interventions were used to target identified modifiable barriers to using the patient decision aid in routine CF clinical practice. CF clinics reported using it with almost all patients in the second year.

Development of an expert system for assessing trumpeter swan breeding habitat in the Northern Rocky Mountains.

USGS Publications Warehouse

Sojda, Richard S.; Cornely, John E.; Howe, Adele E.

2002-01-01

A decision support system for the management of the Rocky Mountain Population of Trumpeter Swans (Cygnus buccinators) is being developed. As part of this, three expert systems are also in development: one for assessing the quality of Trumpeter Swan breeding habitat; one for making water level recommendations in montane, palustrine wetlands; and one for assessing the contribution a particular site can make towards meeting objectives from as flyway perspective. The focus of this paper is the development of the breeding habitat expert system, which currently consists of 157 rules. Out purpose is to provide decision support for issues that appear to be beyond the capability of a single persons to conceptualize and solve. We propose that by involving multiple experts in the development and use of the systems, management will be significantly improved. The knowledge base for the expert system has been developed using standard knowledge engineering techniques with a small team of ecological experts. Knowledge was then coded using production rules organized in decision trees using a commercial expert system development shell. The final system has been deployed on the world wide web.

D-WISE: Diabetes Web-Centric Information and Support Environment: conceptual specification and proposed evaluation.

PubMed

Abidi, Samina; Vallis, Michael; Raza Abidi, Syed Sibte; Piccinini-Vallis, Helena; Imran, Syed Ali

2014-06-01

To develop and evaluate Diabetes Web-Centric Information and Support Environment (D-WISE) that offers 1) a computerized decision-support system to assist physicians to A) use the Canadian Diabetes Association clinical practice guidelines (CDA CPGs) to recommend evidence-informed interventions; B) offer a computerized readiness assessment strategy to help physicians administer behaviour-change strategies to help patients adhere to disease self-management programs; and 2) a patient-specific diabetes self-management application, accessible through smart mobile devices, that offers behaviour-change interventions to engage patients in self-management. The above-mentioned objectives were pursued through a knowledge management approach that involved 1) Translation of paper-based CDA CPGs and behaviour-change models as computerized decision-support tools that will assist physicians to offer evidence-informed and personalized diabetes management and behaviour-change strategies; 2) Engagement of patients in their diabetes care by generating a diabetes self-management program that takes into account their preferences, challenges and needs; 3) Empowering patients to self-manage their condition by providing them with personalized educational and motivational messages through a mobile self-management application. The theoretical foundation of our research is grounded in behaviour-change models and healthcare knowledge management. We used 1) knowledge modelling to computerize the paper-based CDA CPGs and behaviour-change models, in particular, the behaviour-change strategy elements of A) readiness-to-change assessments; B) motivation-enhancement interventions categorized along the lines of patients' being ready, ambivalent or not ready; and C) self-efficacy enhancement. The CDA CPGs and the behaviour-change models are modelled and computerized in terms of A) a diabetes management ontology that serves as the knowledge resource for all the services offered by D-WISE; B) decision support services that use logic-based reasoning algorithms to utilize the knowledge encoded within the diabetes management ontology to assist physicians by recommending patient-specific diabetes-management interventions and behaviour-change strategies; C) a mobile diabetes self-management application to engage and educate diabetes patients to self-manage their condition in a home-based setting while working in concert with their family physicians. We have been successful in creating and conducting a usability assessment of the physician decision support tool. These results will be published once the patient self- management application has been evaluated. D-WISE will be evaluated through pilot studies measuring 1) the usability of the e-Health interventions; and 2) the impact of the interventions on patients' behaviour changes and diabetes control. Copyright © 2014 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

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.

Science communication and vernal pool conservation: a study of local decision maker attitudes in a knowledge-action system.

PubMed

McGreavy, Bridie; Webler, Thomas; Calhoun, Aram J K

2012-03-01

In this study, we describe local decision maker attitudes towards vernal pools to inform science communication and enhance vernal pool conservation efforts. We conducted interviews with town planning board and conservation commission members (n = 9) from two towns in the State of Maine in the northeastern United States. We then mailed a questionnaire to a stratified random sample of planning board members in August and September 2007 with a response rate of 48.4% (n = 320). The majority of survey respondents favored the protection and conservation of vernal pools in their towns. Decision makers were familiar with the term "vernal pool" and demonstrated positive attitudes to vernal pools in general. General appreciation and willingness to conserve vernal pools predicted support for the 2006 revisions to the Natural Resource Protection Act regulating Significant Vernal Pools. However, 48% of respondents were unaware of this law and neither prior knowledge of the law nor workshop attendance predicted support for the vernal pool law. Further, concerns about private property rights and development restrictions predicted disagreement with the vernal pool law. We conclude that science communication must rely on specific frames of reference, be sensitive to cultural values, and occur in an iterative system to link knowledge and action in support of vernal pool conservation. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Development of a patient decision aid for choice of surgical treatment for breast cancer

PubMed Central

Sawka, Carol A.; Goel, Vivek; Mahut, Catherine A.; Taylor, Glen A.; Thiel, Elaine C.; O'Connor, Annette M.; Ackerman, Ida; Burt, Janet H.; Gort, Elaine H.

2002-01-01

Purpose A patient decision aid for the surgical treatment of early stage breast cancer was developed and evaluated. The rationale for its development was the knowledge that breast conserving therapy (lumpectomy followed by breast radiation) and mastectomy produce equivalent outcomes, and the current general agreement that the decision for the type of surgery should rest with the patient. Methods A decision aid was developed and evaluated in sequential pilot studies of 18 and 10 women with newly diagnosed breast cancer who were facing a decision for breast conserving therapy or mastectomy. Both qualitative (general reaction, self‐reported anxiety, clarity, satisfaction) and quantitative (knowledge and decisional conflict) measures were assessed. Results The decision aid consists of an audiotape and workbook and takes 36 min to complete. Based on qualitative comments and satisfaction ratings, 17 of 18 women reported a positive reaction to the decision aid, and all 18 reported that it helped clarify information given by the surgeon. Women did not report an increase in anxiety and 17 of 18 women were either satisfied or very satisfied with the decision aid. Conclusion This pilot study supports the hypothesis that this decision aid may be a helpful adjunct in the decision for surgical management of early stage breast cancer. We are currently conducting a randomized trial of the decision aid versus a simple educational pamphlet to evaluate its efficacy as measured by knowledge, decisional conflict, anxiety and post‐decisional regret. PMID:11281859

Evidence-informed decision-making by professionals working in addiction agencies serving women: a descriptive qualitative study.

PubMed

Jack, Susan M; Dobbins, Maureen; Sword, Wendy; Novotna, Gabriela; Brooks, Sandy; Lipman, Ellen L; Niccols, Alison

2011-11-07

Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions.

Evidence-informed decision-making by professionals working in addiction agencies serving women: a descriptive qualitative study

PubMed Central

2011-01-01

Background Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. Methods A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Results Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. Conclusions There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions. PMID:22059528

Middle Mississippi River decision support system: user's manual

USGS Publications Warehouse

Rohweder, Jason J.; Zigler, Steven J.; Fox, Timothy J.; Hulse, Steven N.

2005-01-01

This user's manual describes the Middle Mississippi River Decision Support System (MMRDSS) and gives detailed examples on its use. The MMRDSS provides a framework to assist decision makers regarding natural resource issues in the Middle Mississippi River floodplain. The MMRDSS is designed to provide users with a spatially explicit tool for tasks, such as inventorying existing knowledge, developing models to investigate the potential effects of management decisions, generating hypotheses to advance scientific understanding, and developing scientifically defensible studies and monitoring. The MMRDSS also includes advanced tools to assist users in evaluating differences in complexity, connectivity, and structure of aquatic habitats among river reaches. The Environmental Systems Research Institute ArcView 3.x platform was used to create and package the data and tools of the MMRDSS.

Supporting Neonatal Intensive Care Unit Parents Through Social Media.

PubMed

Dzubaty, Dolores R

2016-01-01

Parents of infants in the neonatal intensive care unit may often find themselves seeking healthcare information from online and social media sources. Social media applications are available to healthcare consumers and their families, as well as healthcare providers, in a variety of formats. Information that parents gather on their own, and information that is explained by providers, is then used when parents make healthcare decisions regarding their infants. Parents also seek support from peers and family while making healthcare decisions. The combination of knowledge obtained and social support given may empower the parent to feel more confident in their decision making. Healthcare professionals can guide parents to credible resources. The exchange of information between providers and parents can occur using a variety of communication methods. Misperceptions can be corrected, support given, open sharing of information occurs, and parent empowerment may result.

Bridging the Guideline Implementation Gap: A Systematic, Document-Centered Approach to Guideline Implementation

PubMed Central

Shiffman, Richard N.; Michel, George; Essaihi, Abdelwaheb; Thornquist, Elizabeth

2004-01-01

Objective: A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems. Design: This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification. Results: The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institute's guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system. Conclusion: Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge. PMID:15187061

Data-mining to build a knowledge representation store for clinical decision support. Studies on curation and validation based on machine performance in multiple choice medical licensing examinations.

PubMed

Robson, Barry; Boray, Srinidhi

2016-06-01

Extracting medical knowledge by structured data mining of many medical records and from unstructured data mining of natural language source text on the Internet will become increasingly important for clinical decision support. Output from these sources can be transformed into large numbers of elements of knowledge in a Knowledge Representation Store (KRS), here using the notation and to some extent the algebraic principles of the Q-UEL Web-based universal exchange and inference language described previously, rooted in Dirac notation from quantum mechanics and linguistic theory. In a KRS, semantic structures or statements about the world of interest to medicine are analogous to natural language sentences seen as formed from noun phrases separated by verbs, prepositions and other descriptions of relationships. A convenient method of testing and better curating these elements of knowledge is by having the computer use them to take the test of a multiple choice medical licensing examination. It is a venture which perhaps tells us almost as much about the reasoning of students and examiners as it does about the requirements for Artificial Intelligence as employed in clinical decision making. It emphasizes the role of context and of contextual probabilities as opposed to the more familiar intrinsic probabilities, and of a preliminary form of logic that we call presyllogistic reasoning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Creation of a Tool for Assessing Knowledge in Evidence-Based Decision-Making in Practicing Health Care Providers.

PubMed

Spurr, Kathy; Dechman, Gail; Lackie, Kelly; Gilbert, Robert

2016-01-01

Evidence-based decision-making (EBDM) is the process health care providers (HCPs) use to identify and appraise potential evidence. It supports the integration of best research evidence with clinical expertise and patient values into the decision-making process for patient care. Competence in this process is essential to delivery of optimal care. There is no objective tool that assesses EBDM across HCP groups. This research aimed to develop a content valid tool to assess knowledge of the principles of evidence-based medicine and the EBDM process, for use with all HCPs. A Delphi process was used in the creation of the tool. Pilot testing established its content validity with the added benefit of evaluating HCPs' knowledge of EBDM. Descriptive statistics and multivariate mixed models were used to evaluate individual survey responses in total, as well as within each EBDM component. The tool consisted of 26 multiple-choice questions. A total of 12,884 HCPs in Nova Scotia were invited to participate in the web-based validation study, yielding 818 (6.3%) participants, 471 of whom completed all questions. The mean overall score was 68%. Knowledge in one component, integration of evidence with clinical expertise and patient preferences, was identified as needing development across all HCPs surveyed. A content valid tool for assessing HCP EBDM knowledge was created and can be used to support the development of continuing education programs to enhance EBDM competency.

In-context query reformulation for failing SPARQL queries

NASA Astrophysics Data System (ADS)

Viswanathan, Amar; Michaelis, James R.; Cassidy, Taylor; de Mel, Geeth; Hendler, James

2017-05-01

Knowledge bases for decision support systems are growing increasingly complex, through continued advances in data ingest and management approaches. However, humans do not possess the cognitive capabilities to retain a bird's-eyeview of such knowledge bases, and may end up issuing unsatisfiable queries to such systems. This work focuses on the implementation of a query reformulation approach for graph-based knowledge bases, specifically designed to support the Resource Description Framework (RDF). The reformulation approach presented is instance-and schema-aware. Thus, in contrast to relaxation techniques found in the state-of-the-art, the presented approach produces in-context query reformulation.

Life Satisfaction and Perceived Meaningfulness of Learning Experience among First-Year Traditional Graduate Social Work Students

ERIC Educational Resources Information Center

Fakunmoju, Sunday; Donahue, Gilpatrick R.; McCoy, Shandria; Mengel, Alison S.

2016-01-01

Knowledge about life satisfaction and learning experience among first-year graduate students is sparse, despite its relevance to instructional decisions, academic support, and success of students. Adequate knowledge is crucial, as it may help graduate students manage personal and professional life changes associated with graduate education. Using…

Outcomes-focused knowledge translation: a framework for knowledge translation and patient outcomes improvement.

PubMed

Doran, Diane M; Sidani, Souraya

2007-01-01

Regularly accessing information that is current and reliable continues to be a challenge for front-line staff nurses. Reconceptualizing how nurses access information and designing appropriate decision support systems to facilitate timely access to information may be important for increasing research utilization. An outcomes-focused knowledge translation framework was developed to guide the continuous improvement of patient care through the uptake of research evidence and feedback data about patient outcomes. The framework operationalizes the three elements of the PARIHS framework at the point of care. Outcomes-focused knowledge translation involves four components: (a) patient outcomes measurement and real-time feedback about outcomes achievement; (b) best-practice guidelines, embedded in decision support tools that deliver key messages in response to patient assessment data; (c) clarification of patients' preferences for care; and (d) facilitation by advanced practice nurses and practice leaders. In this paper the framework is described and evidence is provided to support theorized relationships among the concepts in the framework. The framework guided the design of a knowledge translation intervention aimed at continuous improvement of patient care and evidence-based practice, which are fostered through real-time feedback data about patient outcomes, electronic access to evidence-based resources at the point of care, and facilitation by advanced practice nurses. The propositions in the framework need to be empirically tested through future research.

Sustainable urban systems: Co-design and framing for transformation.

PubMed

Webb, Robert; Bai, Xuemei; Smith, Mark Stafford; Costanza, Robert; Griggs, David; Moglia, Magnus; Neuman, Michael; Newman, Peter; Newton, Peter; Norman, Barbara; Ryan, Chris; Schandl, Heinz; Steffen, Will; Tapper, Nigel; Thomson, Giles

2018-02-01

Rapid urbanisation generates risks and opportunities for sustainable development. Urban policy and decision makers are challenged by the complexity of cities as social-ecological-technical systems. Consequently there is an increasing need for collaborative knowledge development that supports a whole-of-system view, and transformational change at multiple scales. Such holistic urban approaches are rare in practice. A co-design process involving researchers, practitioners and other stakeholders, has progressed such an approach in the Australian context, aiming to also contribute to international knowledge development and sharing. This process has generated three outputs: (1) a shared framework to support more systematic knowledge development and use, (2) identification of barriers that create a gap between stated urban goals and actual practice, and (3) identification of strategic focal areas to address this gap. Developing integrated strategies at broader urban scales is seen as the most pressing need. The knowledge framework adopts a systems perspective that incorporates the many urban trade-offs and synergies revealed by a systems view. Broader implications are drawn for policy and decision makers, for researchers and for a shared forward agenda.

Effective behavioral modeling and prediction even when few exemplars are available

NASA Astrophysics Data System (ADS)

Goan, Terrance; Kartha, Neelakantan; Kaneshiro, Ryan

2006-05-01

While great progress has been made in the lowest levels of data fusion, practical advances in behavior modeling and prediction remain elusive. The most critical limitation of existing approaches is their inability to support the required knowledge modeling and continuing refinement under realistic constraints (e.g., few historic exemplars, the lack of knowledge engineering support, and the need for rapid system deployment). This paper reports on our ongoing efforts to develop Propheteer, a system which will address these shortcomings through two primary techniques. First, with Propheteer we abandon the typical consensus-driven modeling approaches that involve infrequent group decision making sessions in favor of an approach that solicits asynchronous knowledge contributions (in the form of alternative future scenarios and indicators) without burdening the user with endless certainty or probability estimates. Second, we enable knowledge contributions by personnel beyond the typical core decision making group, thereby casting light on blind spots, mitigating human biases, and helping maintain the currency of the developed behavior models. We conclude with a discussion of the many lessons learned in the development of our prototype Propheteer system.

Participatory approach to the development of a knowledge base for problem-solving in diabetes self-management.

PubMed

Cole-Lewis, Heather J; Smaldone, Arlene M; Davidson, Patricia R; Kukafka, Rita; Tobin, Jonathan N; Cassells, Andrea; Mynatt, Elizabeth D; Hripcsak, George; Mamykina, Lena

2016-01-01

To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Participatory approach to the development of a knowledge base for problem-solving in diabetes self-management

PubMed Central

Cole-Lewis, Heather J.; Smaldone, Arlene M.; Davidson, Patricia R.; Kukafka, Rita; Tobin, Jonathan N.; Cassells, Andrea; Mynatt, Elizabeth D.; Hripcsak, George; Mamykina, Lena

2015-01-01

Objective To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. Materials and methods The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. Results The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. Discussion The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. Conclusion The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions. PMID:26547253

Developing Quality Indicators and Auditing Protocols from Formal Guideline Models: Knowledge Representation and Transformations

PubMed Central

Advani, Aneel; Goldstein, Mary; Shahar, Yuval; Musen, Mark A.

2003-01-01

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a model representation and algorithm for deriving structured quality indicators and auditing protocols from formalized specifications of guidelines used in decision support systems. We apply the model and algorithm to the assessment of physician concordance with a guideline knowledge model for hypertension used in a decision-support system. The properties of our solution include the ability to derive automatically (1) context-specific and (2) case-mix-adjusted quality indicators that (3) can model global or local levels of detail about the guideline (4) parameterized by defining the reliability of each indicator or element of the guideline. PMID:14728124

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.

PubMed

Dhukaram, Anandhi Vivekanandan; Baber, Chris

2015-06-01

Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Components of Social Competence and Strategies of Support: Considering What to Teach and How

ERIC Educational Resources Information Center

Han, Heejeong Sophia; Kemple, Kristen Mary

2006-01-01

Decisions about how to support the development of young children's social competence must be made on the basis of knowledge of important competencies to be developed, as well as effective strategies to support those competencies. This paper combines a broad-definition model of components of social competence (Kostelnik, Stein, Whiren, Soderman, &…

Health data and data governance.

PubMed

Hovenga, Evelyn J S; Grain, Heather

2013-01-01

Health is a knowledge industry, based on data collected to support care, service planning, financing and knowledge advancement. Increasingly there is a need to collect, retrieve and use health record information in an electronic format to provide greater flexibility, as this enables retrieval and display of data in multiple locations and formats irrespective of where the data were collected. Electronically maintained records require greater structure and consistency to achieve this. The use of data held in records generated in real time in clinical systems also has the potential to reduce the time it takes to gain knowledge, as there is less need to collect research specific information, this is only possible if data governance principles are applied. Connected devices and information systems are now generating huge amounts of data, as never before seen. An ability to analyse and mine very large amounts of data, "Big Data", provides policy and decision makers with new insights into varied aspects of work and information flow and operational business patterns and trends, and drives greater efficiencies, and safer and more effective health care. This enables decision makers to apply rules and guidance that have been developed based upon knowledge from many individual patient records through recognition of triggers based upon that knowledge. In clinical decision support systems information about the individual is compared to rules based upon knowledge gained from accumulated information of many to provide guidance at appropriate times in the clinical process. To achieve this the data in the individual system, and the knowledge rules must be represented in a compatible and consistent manner. This chapter describes data attributes; explains the difference between data and information; outlines the requirements for quality data; shows the relevance of health data standards; and describes how data governance impacts representation of content in systems and the use of that information.

The application of decision analysis to life support research and technology development

NASA Technical Reports Server (NTRS)

Ballin, Mark G.

1994-01-01

Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

HPV vaccine introduction at the local level in a developing country: attitudes and criteria among key actors.

PubMed

Piñeros, Marion; Wiesner, Carolina; Cortés, Claudia; Trujillo, Lina María

2010-05-01

In most developing countries, HPV vaccines have been licensed but there are no national policy recommendations, nor is it clear how decisions on the introduction of this new vaccine are made. Decentralization processes in many Latin American countries favor decision-making at the local level. Through a qualitative study we explored knowledge regarding the HPV vaccine and the criteria that influence decision-making among local health actors in four regions of Colombia. We conducted a total of 14 in-depths interviews with different actors; for the analysis we performed content analysis. Results indicate that decision-making on the HPV vaccine at the local level has mainly been driven by pressure from local political actors, in a setting where there is low technical knowledge of the vaccine. This increases the risk of initiatives that may foster inequity. Local decisions and initiatives need to be strengthened technically and supported by national-level decisions, guidelines and follow-up.

Intuition: A Concept Analysis.

PubMed

Chilcote, Deborah R

2017-01-01

The purpose of this article is to conceptually examine intuition; identify the importance of intuition in nursing education, clinical practice, and patient care; encourage acceptance of the use of intuition; and add to the body of nursing knowledge. Nurses often report using intuition when making clinical decisions. Intuition is a rapid, unconscious process based in global knowledge that views the patient holistically while synthesizing information to improve patient outcomes. However, with the advent of evidence-based practice (EBP), the use of intuition has become undervalued in nursing. Walker and Avant's framework was used to analyze intuition. A literature search from 1987 to 2014 was conducted using the following keywords: intuition, intuition and nursing, clinical decision making, clinical decision making and intuition, patient outcomes, EBP, and analytical thinking. The use of intuition is reported by nurses, but is not legitimized within the nursing profession. Defining attributes of intuition are an unconscious, holistic knowledge gathered without using an analytical process and knowledge derived through synthesis, not analysis. Consequences include verification of intuition through an analytical process and translating that knowledge into a course of action. This article supports the use of intuition in nursing by offering clarity to the concept, adds to the nursing knowledge base, encourages a holistic view of the patient during clinical decision making, and encourages nurse educators to promote the use of intuition. © 2016 Wiley Periodicals, Inc.

Newly graduated nurses' use of knowledge sources in clinical decision-making: an ethnographic study.

PubMed

Voldbjerg, Siri Lygum; Grønkjaer, Mette; Wiechula, Rick; Sørensen, Erik Elgaard

2017-05-01

To explore which knowledge sources newly graduated nurses' use in clinical decision-making and why and how they are used. In spite of an increased educational focus on skills and competencies within evidence-based practice, newly graduated nurses' ability to use components within evidence-based practice with a conscious and reflective use of research evidence has been described as being poor. To understand why, it is relevant to explore which other knowledge sources are used. This may shed light on why research evidence is sparsely used and ultimately inform approaches to strengthen the knowledgebase used in clinical decision-making. Ethnographic study using participant-observation and individual semistructured interviews of nine Danish newly graduated nurses in medical and surgical hospital settings. Newly graduates use of knowledge sources was described within three main structures: 'other', 'oneself' and 'gut feeling'. Educational preparation, transition into clinical practice and the culture of the setting influenced the knowledge sources used. The sources ranged from overt easily articulated knowledge sources to covert sources that were difficult to articulate. The limited articulation of certain sources inhibited the critical reflection on the reasoning behind decisions. Reflection is a prerequisite for an evidence-based practice where decisions should be transparent in order to consider if other evidentiary sources could be used. Although there is a complexity and variety to knowledge sources used, there is an imbalance with the experienced nurse playing a key role, functioning both as predominant source and a role model as to which sources are valued and used in clinical decision-making. If newly graduates are to be supported in an articulate and reflective use of a variety of sources, they have to be allocated to experienced nurses who model a reflective, articulate and balanced use of knowledge sources. © 2016 John Wiley & Sons Ltd.

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.

Applying voting theory in natural resource management: a case of multiple-criteria group decision support.

PubMed

Laukkanen, Sanna; Kangas, Annika; Kangas, Jyrki

2002-02-01

Voting theory has a lot in common with utility theory, and especially with group decision-making. An expected-utility-maximising strategy exists in voting situations, as well as in decision-making situations. Therefore, it is natural to utilise the achievements of voting theory also in group decision-making. Most voting systems are based on a single criterion or holistic preference information on decision alternatives. However, a voting scheme called multicriteria approval is specially developed for decision-making situations with multiple criteria. This study considers the voting theory from the group decision support point of view and compares it with some other methods applied to similar purposes in natural resource management. A case study is presented, where the approval voting approach is introduced to natural resources planning and tested in a forestry group decision-making process. Applying multicriteria approval method was found to be a potential approach for handling some challenges typical for forestry group decision support. These challenges include (i) utilising ordinal information in the evaluation of decision alternatives, (ii) being readily understandable for and treating equally all the stakeholders in possession of different levels of knowledge on the subject considered, (iii) fast and cheap acquisition of preference information from several stakeholders, and (iv) dealing with multiple criteria.

Nordic couples' decision-making processes during assisted reproduction treatments.

PubMed

Sol Olafsdottir, Helga; Wikland, Matts; Möller, Anders

2013-06-01

To study couples' perceptions of their decision-making process during the first three years of infertility treatments. This study is a part of a larger project studying the decision-making processes of 22 infertile heterosexual couples, recruited from fertility clinics in all five Nordic countries, over a three year period. A descriptive qualitative method was used. Process of decision-making during assisted reproduction treatments. Seventeen couples had succeeded in becoming parents after approximately three years. Our study suggests that the decision-making process during fertility treatments has three phases: (i) recognizing the decisions to be made, with subcategories; the driving force, mutual project, (ii) gathering knowledge and experience about the options, with subcategories; trust, patient competence, personalized support, and (iii) adapting decisions to possible options, with subcategories; strategic planning, adaption. The core category was "maintaining control in a situation of uncertainty." Two parallel processes affect couples' decision-making process, one within themselves and their relationship, and the other in their contact with the fertility clinic. Couples struggle to make decisions, trusting clinic personnel for guidance, knowledge, and understanding. Nevertheless, couples expressed disappointment with the clinics' reactions to their requests for shared decision-making. Copyright © 2013 Elsevier B.V. All rights reserved.

Knowledge Engineering as a Component of the Curriculum for Medical Cybernetists.

PubMed

Karas, Sergey; Konev, Arthur

2017-01-01

According to a new state educational standard, students who have chosen medical cybernetics as their major must develop a knowledge engineering competency. Previously, in the course "Clinical cybernetics" while practicing project-based learning students were designing automated workstations for medical personnel using client-server technology. The purpose of the article is to give insight into the project of a new educational module "Knowledge engineering". Students will acquire expert knowledge by holding interviews and conducting surveys, and then they will formalize it. After that, students will form declarative expert knowledge in a network model and analyze the knowledge graph. Expert decision making methods will be applied in software on the basis of a production model of knowledge. Project implementation will result not only in the development of analytical competencies among students, but also creation of a practically useful expert system based on student models to support medical decisions. Nowadays, this module is being tested in the educational process.

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.

Structured representation for core elements of common clinical decision support interventions to facilitate knowledge sharing.

PubMed

Zhou, Li; Hongsermeier, Tonya; Boxwala, Aziz; Lewis, Janet; Kawamoto, Kensaku; Maviglia, Saverio; Gentile, Douglas; Teich, Jonathan M; Rocha, Roberto; Bell, Douglas; Middleton, Blackford

2013-01-01

At present, there are no widely accepted, standard approaches for representing computer-based clinical decision support (CDS) intervention types and their structural components. This study aimed to identify key requirements for the representation of five widely utilized CDS intervention types: alerts and reminders, order sets, infobuttons, documentation templates/forms, and relevant data presentation. An XML schema was proposed for representing these interventions and their core structural elements (e.g., general metadata, applicable clinical scenarios, CDS inputs, CDS outputs, and CDS logic) in a shareable manner. The schema was validated by building CDS artifacts for 22 different interventions, targeted toward guidelines and clinical conditions called for in the 2011 Meaningful Use criteria. Custom style sheets were developed to render the XML files in human-readable form. The CDS knowledge artifacts were shared via a public web portal. Our experience also identifies gaps in existing standards and informs future development of standards for CDS knowledge representation and sharing.

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

Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

NASA Astrophysics Data System (ADS)

Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

Clinical decision support systems for addressing information needs of physicians.

PubMed

Denekamp, Yaron

2007-11-01

Clinicians routinely practice in a state of incomplete information--about the patient, and about medical knowledge pertaining to patients' care. Consequently, there is now growing interest in the use of CDSS to bring decision support to the point of care. CDSS can impact physician behavior in routine practice. Nonetheless, CDSSs are meant to support humans who are ultimately responsible for the clinical decisions, rather than replace them. Although the adoption of CDSS has proceeded at a slow pace, there is a widespread recognition that CDSSs are expected to play a crucial role in reducing medical errors and improving the quality and efficacy of health care. This will be facilitated by the gradual maturation of electronic health record systems and the emergence of standard terminologies and messaging standards for the exchange of clinical data.

What can Natural Language Processing do for Clinical Decision Support?

PubMed Central

Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.

2009-01-01

Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

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.

Supporting shared decision making using an Option Grid for osteoarthritis of the knee in an interface musculoskeletal clinic: A stepped wedge trial.

PubMed

Elwyn, Glyn; Pickles, Tim; Edwards, Adrian; Kinsey, Katharine; Brain, Kate; Newcombe, Robert G; Firth, Jill; Marrin, Katy; Nye, Alan; Wood, Fiona

2016-04-01

To evaluate whether introducing tools, specifically designed for use in clinical encounters, namely Option Grids, into a clinical practice setting leads to higher levels of shared decision making. A stepped wedge trial design where 6 physiotherapists at an interface clinic in Oldham, UK, were sequentially instructed in how to use an Option Grid for osteoarthritis of the knee. Patients with suspected or confirmed osteoarthritis of the knee were recruited, six per clinician prior to instruction, and six per clinician afterwards. We measured shared decision making, patient knowledge, and readiness to decide. A total of 72 patients were recruited; 36 were allocated to the intervention group. There was an 8.4 point (95% CI 4.4 to 12.2) increase in the Observer OPTION score (range 0-100) in the intervention group. The mean gain in knowledge was 0.9 points (score range 0-5, 95% CI, 0.3 to 1.5). There was no increase in encounter duration. Shared decision making increased when clinicians used the knee osteoarthritis Option Grid. Tools designed to support collaboration and deliberation about treatment options lead to increased levels of shared decision making. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Assessing the influence of knowledge translation platforms on health system policy processes to achieve the health millennium development goals in Cameroon and Uganda: a comparative case study.

PubMed

Ongolo-Zogo, Pierre; Lavis, John N; Tomson, Goran; Sewankambo, Nelson K

2018-05-01

There is a scarcity of empirical data on the influence of initiatives supporting evidence-informed health system policy-making (EIHSP), such as the knowledge translation platforms (KTPs) operating in Africa. To assess whether and how two KTPs housed in government-affiliated institutions in Cameroon and Uganda have influenced: (1) health system policy-making processes and decisions aiming at supporting achievement of the health millennium development goals (MDGs); and (2) the general climate for EIHSP. We conducted an embedded comparative case study of four policy processes in which Evidence Informed Policy Network (EVIPNet) Cameroon and Regional East African Community Health Policy Initiative (REACH-PI) Uganda were involved between 2009 and 2011. We combined a documentary review and semi structured interviews of 54 stakeholders. A framework-guided thematic analysis, inspired by scholarship in health policy analysis and knowledge utilization was used. EVIPNet Cameroon and REACH-PI Uganda have had direct influence on health system policy decisions. The coproduction of evidence briefs combined with tacit knowledge gathered during inclusive evidence-informed stakeholder dialogues helped to reframe health system problems, unveil sources of conflicts, open grounds for consensus and align viable and affordable options for achieving the health MDGs thus leading to decisions. New policy issue networks have emerged. The KTPs indirectly influenced health policy processes by changing how interests interact with one another and by introducing safe-harbour deliberations and intersected with contextual ideational factors by improving access to policy-relevant evidence. KTPs were perceived as change agents with positive impact on the understanding, acceptance and adoption of EIHSP because of their complementary work in relation to capacity building, rapid evidence syntheses and clearinghouse of policy-relevant evidence. This embedded case study illustrates how two KTPs influenced policy decisions through pathways involving policy issue networks, interest groups interaction and evidence-supported ideas and how they influenced the general climate for EIHSP.

Assessing the influence of knowledge translation platforms on health system policy processes to achieve the health millennium development goals in Cameroon and Uganda: a comparative case study

PubMed Central

Lavis, John N; Tomson, Goran; Sewankambo, Nelson K

2018-01-01

Abstract There is a scarcity of empirical data on the influence of initiatives supporting evidence-informed health system policy-making (EIHSP), such as the knowledge translation platforms (KTPs) operating in Africa. To assess whether and how two KTPs housed in government-affiliated institutions in Cameroon and Uganda have influenced: (1) health system policy-making processes and decisions aiming at supporting achievement of the health millennium development goals (MDGs); and (2) the general climate for EIHSP. We conducted an embedded comparative case study of four policy processes in which Evidence Informed Policy Network (EVIPNet) Cameroon and Regional East African Community Health Policy Initiative (REACH-PI) Uganda were involved between 2009 and 2011. We combined a documentary review and semi structured interviews of 54 stakeholders. A framework-guided thematic analysis, inspired by scholarship in health policy analysis and knowledge utilization was used. EVIPNet Cameroon and REACH-PI Uganda have had direct influence on health system policy decisions. The coproduction of evidence briefs combined with tacit knowledge gathered during inclusive evidence-informed stakeholder dialogues helped to reframe health system problems, unveil sources of conflicts, open grounds for consensus and align viable and affordable options for achieving the health MDGs thus leading to decisions. New policy issue networks have emerged. The KTPs indirectly influenced health policy processes by changing how interests interact with one another and by introducing safe-harbour deliberations and intersected with contextual ideational factors by improving access to policy-relevant evidence. KTPs were perceived as change agents with positive impact on the understanding, acceptance and adoption of EIHSP because of their complementary work in relation to capacity building, rapid evidence syntheses and clearinghouse of policy-relevant evidence. This embedded case study illustrates how two KTPs influenced policy decisions through pathways involving policy issue networks, interest groups interaction and evidence-supported ideas and how they influenced the general climate for EIHSP. PMID:29506146

Application of the principles of evidence-based practice in decision making among senior management in Nova Scotia's addiction services agencies.

PubMed

Murphy, Matthew; MacCarthy, M Jayne; McAllister, Lynda; Gilbert, Robert

2014-12-05

Competency profiles for occupational clusters within Canada's substance abuse workforce (SAW) define the need for skill and knowledge in evidence-based practice (EBP) across all its members. Members of the Senior Management occupational cluster hold ultimate responsibility for decisions made within addiction services agencies and therefore must possess the highest level of proficiency in EBP. The objective of this study was to assess the knowledge of the principles of EBP, and use of the components of the evidence-based decision making (EBDM) process in members of this occupational cluster from selected addiction services agencies in Nova Scotia. A convenience sampling method was used to recruit participants from addiction services agencies. Semi-structured qualitative interviews were conducted with eighteen Senior Management. The interviews were audio-recorded, transcribed verbatim and checked by the participants. Interview transcripts were coded and analyzed for themes using content analysis and assisted by qualitative data analysis software (NVivo 9.0). Data analysis revealed four main themes: 1) Senior Management believe that addictions services agencies are evidence-based; 2) Consensus-based decision making is the norm; 3) Senior Management understand the principles of EBP and; 4) Senior Management do not themselves use all components of the EBDM process when making decisions, oftentimes delegating components of this process to decision support staff. Senior Management possess an understanding of the principles of EBP, however, when making decisions they often delegate components of the EBDM process to decision support staff. Decision support staff are not defined as an occupational cluster in Canada's SAW and have not been ascribed a competency profile. As such, there is no guarantee that this group possesses competency in EBDM. There is a need to advocate for the development of a defined occupational cluster and associated competency profile for this critical group.

EVA Suit Studies: Human Forward Contamination Project

NASA Technical Reports Server (NTRS)

Rucker, Michelle

2017-01-01

Background: NASA Strategic Knowledge Gap B5: Forward Contamination for Mars. Issue: we have knowledge gaps!: Whether / how microbes are released from crewed pressure systems. Why do we care?: Informs Mars operational concepts - How to protect the science; Informs architecture decisions - How “open” Environmental Control and Life Support (ECLS) systems are; Informs landing site selection decisions - How close we can land / operate to where life may be present. Project goal: get some data to fill in these gaps: Data will help determine whether we’re ready to go to Mars, or if we need to change our systems or operational designs.

Improving the role of vulnerability assessments In decision support for effective climate adaptation

Treesearch

Linda A. Joyce; Constance I. Millar

2014-01-01

Vulnerability assessments (VA) have been proposed as an initial step in a process to develop and implement adaptation management for climate change in forest ecosystems. Scientific understanding of the effects of climate change is an ever-accumulating knowledge base. Synthesizing information from this knowledge base in the context of our understanding of ecosystem...

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...

The treatment implementation advisor: a component of the GypsES project

Treesearch

Michael C. Saunders; Michael A. Foster

1991-01-01

The treatment implementation advisor is one of the knowledge based advisory modules of GypsES, a knowledge system environment for decision support in gypsy moth management. Its function is to provide detailed advice on intervention tactics for gypsy moth: e.g. aerial and ground application of insecticides and microbials, inundative or augmentative releases of...

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...

Impact of a web-based prostate cancer treatment decision aid on patient-reported decision process parameters: results from the Prostate Cancer Patient Centered Care trial.

PubMed

Cuypers, Maarten; Lamers, Romy E D; Kil, Paul J M; van de Poll-Franse, Lonneke V; de Vries, Marieke

2018-05-12

To compare patients' evaluation of the treatment decision-making process in localized prostate cancer between counseling that included an online decision aid (DA) and standard counseling. Eighteen Dutch hospitals were randomized to DA counseling (n = 235) or the control group with standard counseling (n = 101) in a pragmatic, cluster randomized controlled trial. The DA was provided to patients at, or soon after diagnosis. Decisional conflict, involvement, knowledge, and satisfaction with information were assessed with a questionnaire after treatment decision-making. Anxiety and depression served as covariates. The levels of decision involvement and conflict were comparable between patients in both groups. Patients with a DA felt more knowledgeable but scored equally well on a knowledge test as patients without a DA. Small significant negative effects were found on satisfaction with information and preparation for decision-making. A preference for print over online and depression and anxiety symptoms was negatively associated with satisfaction and conflict scores in the DA group. The DA aimed to support shared decision-making, while outcomes for a majority of DA users were comparable to patients who received standard counseling. Patients, who are less comfortable with the online DA format or experience anxiety or depression symptoms, could require more guidance toward shared decision-making. To evaluate long-term DA effects, follow-up evaluation on treatment satisfaction and decisional regret will be done.

The role of depression pharmacogenetic decision support tools in shared decision making.

PubMed

Arandjelovic, Katarina; Eyre, Harris A; Lenze, Eric; Singh, Ajeet B; Berk, Michael; Bousman, Chad

2017-10-29

Patients discontinue antidepressant medications due to lack of knowledge, unrealistic expectations, and/or unacceptable side effects. Shared decision making (SDM) invites patients to play an active role in their treatment and may indirectly improve outcomes through enhanced engagement in care, adherence to treatment, and positive expectancy of medication outcomes. We believe decisional aids, such as pharmacogenetic decision support tools (PDSTs), facilitate SDM in the clinical setting. PDSTs may likewise predict drug tolerance and efficacy, and therefore adherence and effectiveness on an individual-patient level. There are several important ethical considerations to be navigated when integrating PDSTs into clinical practice. The field requires greater empirical research to demonstrate clinical utility, and the mechanisms thereof, as well as exploration of the ethical use of these technologies.

The impact of computer self-efficacy, computer anxiety, and perceived usability and acceptability on the efficacy of a decision support tool for colorectal cancer screening

PubMed Central

Lindblom, Katrina; Gregory, Tess; Flight, Ingrid H K; Zajac, Ian

2011-01-01

Objective This study investigated the efficacy of an internet-based personalized decision support (PDS) tool designed to aid in the decision to screen for colorectal cancer (CRC) using a fecal occult blood test. We tested whether the efficacy of the tool in influencing attitudes to screening was mediated by perceived usability and acceptability, and considered the role of computer self-efficacy and computer anxiety in these relationships. Methods Eighty-one participants aged 50–76 years worked through the on-line PDS tool and completed questionnaires on computer self-efficacy, computer anxiety, attitudes to and beliefs about CRC screening before and after exposure to the PDS, and perceived usability and acceptability of the tool. Results Repeated measures ANOVA found that PDS exposure led to a significant increase in knowledge about CRC and screening, and more positive attitudes to CRC screening as measured by factors from the Preventive Health Model. Perceived usability and acceptability of the PDS mediated changes in attitudes toward CRC screening (but not CRC knowledge), and computer self-efficacy and computer anxiety were significant predictors of individuals' perceptions of the tool. Conclusion Interventions designed to decrease computer anxiety, such as computer courses and internet training, may improve the acceptability of new health information technologies including internet-based decision support tools, increasing their impact on behavior change. PMID:21857024

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.

The story of rising voices: Facilitating collaboration between indigenous and western ways of knowing

USGS Publications Warehouse

Maldonado, Julie; Lazrus, Heather; Bennett, Shiloh-Kay; Chief, Karletta; Dhillon, Carla May; Gough, Bob; Kruger, Linda; Morisette, Jeffrey T.; Petrovic, Stefan; Whyte, Kyle P.; Companion, Michele; Chaiken, Miriam S.

2016-01-01

Indigenous community self-determination, cultures, and ways of life are at high risk from climate change impacts and ecological dispossession. Partnerships between experts with backgrounds in Indigenous and western knowledge may be productive and effective ways to reduce vulnerability and foster resilience. This chapter examines collaborations among scientific and Native American, Alaska Native, and Pacific Island communities to support climate solutions. We draw examples from the "Rising Voices: Collaborative Science with Indigenous Knowledge for Climate Solutions" program (Rising Voices) to examine how boundary organizations function cross-culturally to increase communities' adaptive capacity through knowledge exchange, as well as building the decision-making capacity needed to exercise sovereignty and make adaptive decisions in a changing climate.

An evidence-based shared decision making programme on the prevention of myocardial infarction in type 2 diabetes: protocol of a randomised-controlled trial.

PubMed

Buhse, Susanne; Heller, Tabitha; Kasper, Jürgen; Mühlhauser, Ingrid; Müller, Ulrich Alfons; Lehmann, Thomas; Lenz, Matthias

2013-10-19

Lack of patient involvement in decision making has been suggested as one reason for limited treatment success. Concepts such as shared decision making may contribute to high quality healthcare by supporting patients to make informed decisions together with their physicians.A multi-component shared decision making programme on the prevention of heart attack in type 2 diabetes has been developed. It aims at improving the quality of decision-making by providing evidence-based patient information, enhancing patients' knowledge, and supporting them to actively participate in decision-making. In this study the efficacy of the programme is evaluated in the setting of a diabetes clinic. A single blinded randomised-controlled trial is conducted to compare the shared decision making programme with a control-intervention. The intervention consists of an evidence-based patient decision aid on the prevention of myocardial infarction and a corresponding counselling module provided by diabetes educators. Similar in duration and structure, the control-intervention targets nutrition, sports, and stress coping. A total of 154 patients between 40 and 69 years of age with type 2 diabetes and no previous diagnosis of ischaemic heart disease or stroke are enrolled and allocated either to the intervention or the control-intervention. Primary outcome measure is the patients' knowledge on benefits and harms of heart attack prevention captured by a standardised knowledge test. Key secondary outcome measure is the achievement of treatment goals prioritised by the individual patient. Treatment goals refer to statin taking, HbA1c-, blood pressure levels and smoking status. Outcomes are assessed directly after the counselling and at 6 months follow-up. Analyses will be carried out on intention-to-treat basis. Concurrent qualitative methods are used to explore intervention fidelity and to gain insight into implementation processes. Interventions to facilitate evidence-based shared decision making represent an innovative approach in diabetes care. The results of this study will provide information on the efficacy of such a concept in the setting of a diabetes clinic in Germany. ISRCTN84636255.

The Morningside Initiative: Collaborative Development of a Knowledge Repository to Accelerate Adoption of Clinical Decision Support

PubMed Central

Greenes, Robert; Bloomrosen, Meryl; Brown-Connolly, Nancy E.; Curtis, Clayton; Detmer, Don E; Enberg, Robert; Fridsma, Douglas; Fry, Emory; Goldstein, Mary K; Haug, Peter; Hulse, Nathan; Hongsermeier, Tonya; Maviglia, Saverio; Robbins, Craig W; Shah, Hemant

2010-01-01

The Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced Technology Research Center (TATRC) of the US Army Medical Research Materiel Command. Participants were subject matter experts in clinical decision support (CDS) and included representatives from the Department of Defense, Veterans Health Administration, Kaiser Permanente, Partners Healthcare System, Henry Ford Health System, Arizona State University, and the American Medical Informatics Association (AMIA). The Morningside Initiative was convened in response to the AMIA Roadmap for National Action on Clinical Decision Support and on the basis of other considerations and experiences of the participants. Its formation was the unanimous recommendation of participants at the 2007 meeting which called for creating a shared repository of executable knowledge for diverse health care organizations and practices, as well as health care system vendors. The rationale is based on the recognition that sharing of clinical knowledge needed for CDS across organizations is currently virtually non-existent, and that, given the considerable investment needed for creating, maintaining and updating authoritative knowledge, which only larger organizations have been able to undertake, this is an impediment to widespread adoption and use of CDS. The Morningside Initiative intends to develop and refine (1) an organizational framework, (2) a technical approach, and (3) CDS content acquisition and management processes for sharing CDS knowledge content, tools, and experience that will scale with growing numbers of participants and can be expanded in scope of content and capabilities. Intermountain Healthcare joined the initial set of participants shortly after its formation. The efforts of the Morningside Initiative are intended to serve as the basis for a series of next steps in a national agenda for CDS. It is based on the belief that sharing of knowledge can be highly effective as is the case in other competitive domains such as genomics. Participants in the Morningside Initiative believe that a coordinated effort between the private and public sectors is needed to accomplish this goal and that a small number of highly visible and respected health care organizations in the public and private sector can lead by example. Ultimately, a future collaborative knowledge sharing organization must have a sustainable long-term business model for financial support. PMID:21603282

The morningside initiative: collaborative development of a knowledge repository to accelerate adoption of clinical decision support.

PubMed

Greenes, Robert; Bloomrosen, Meryl; Brown-Connolly, Nancy E; Curtis, Clayton; Detmer, Don E; Enberg, Robert; Fridsma, Douglas; Fry, Emory; Goldstein, Mary K; Haug, Peter; Hulse, Nathan; Hongsermeier, Tonya; Maviglia, Saverio; Robbins, Craig W; Shah, Hemant

2010-01-01

The Morningside Initiative is a public-private activity that has evolved from an August, 2007, meeting at the Morningside Inn, in Frederick, MD, sponsored by the Telemedicine and Advanced Technology Research Center (TATRC) of the US Army Medical Research Materiel Command. Participants were subject matter experts in clinical decision support (CDS) and included representatives from the Department of Defense, Veterans Health Administration, Kaiser Permanente, Partners Healthcare System, Henry Ford Health System, Arizona State University, and the American Medical Informatics Association (AMIA). The Morningside Initiative was convened in response to the AMIA Roadmap for National Action on Clinical Decision Support and on the basis of other considerations and experiences of the participants. Its formation was the unanimous recommendation of participants at the 2007 meeting which called for creating a shared repository of executable knowledge for diverse health care organizations and practices, as well as health care system vendors. The rationale is based on the recognition that sharing of clinical knowledge needed for CDS across organizations is currently virtually non-existent, and that, given the considerable investment needed for creating, maintaining and updating authoritative knowledge, which only larger organizations have been able to undertake, this is an impediment to widespread adoption and use of CDS. The Morningside Initiative intends to develop and refine (1) an organizational framework, (2) a technical approach, and (3) CDS content acquisition and management processes for sharing CDS knowledge content, tools, and experience that will scale with growing numbers of participants and can be expanded in scope of content and capabilities. Intermountain Healthcare joined the initial set of participants shortly after its formation. The efforts of the Morningside Initiative are intended to serve as the basis for a series of next steps in a national agenda for CDS. It is based on the belief that sharing of knowledge can be highly effective as is the case in other competitive domains such as genomics. Participants in the Morningside Initiative believe that a coordinated effort between the private and public sectors is needed to accomplish this goal and that a small number of highly visible and respected health care organizations in the public and private sector can lead by example. Ultimately, a future collaborative knowledge sharing organization must have a sustainable long-term business model for financial support.

Using a Relational Database to Index Infectious Disease Information

PubMed Central

Brown, Jay A.

2010-01-01

Mapping medical knowledge into a relational database became possible with the availability of personal computers and user-friendly database software in the early 1990s. To create a database of medical knowledge, the domain expert works like a mapmaker to first outline the domain and then add the details, starting with the most prominent features. The resulting “intelligent database” can support the decisions of healthcare professionals. The intelligent database described in this article contains profiles of 275 infectious diseases. Users can query the database for all diseases matching one or more specific criteria (symptom, endemic region of the world, or epidemiological factor). Epidemiological factors include sources (patients, water, soil, or animals), routes of entry, and insect vectors. Medical and public health professionals could use such a database as a decision-support software tool. PMID:20623018

Towards an Intelligent Textbook of Neurology

PubMed Central

Reggia, James A.; Pula, Thaddeus P.; Price, Thomas R.; Perricone, Barry T.

1980-01-01

We define an intelligent textbook of medicine to be a computer system that: (1) provides for storage and selective retrieval of synthesized clinical knowledge for reference purposes; and (2) supports the application by computer of its knowledge to patient information to assist physicians with decision making. This paper describes an experimental system called KMS (a Knowledge Management System) for creating and using intelligent medical textbooks. KMS is domain-independent, supports multiple inference methods and representation languages, and is designed for direct use by physicians during the knowledge acquisition process. It is presented here in the context of the development of an Intelligent Textbook of Neurology. We suggest that KMS has the potential to overcome some of the problems that have inhibited the use of knowledge-based systems by physicians in the past.

Knowledge Translation of the PERC Rule for Suspected Pulmonary Embolism: A Blueprint for Reducing the Number of CT Pulmonary Angiograms.

PubMed

Drescher, Michael J; Fried, Jeremy; Brass, Ryan; Medoro, Amanda; Murphy, Timothy; Delgado, João

2017-10-01

Computerized decision support decreases the number of computed tomography pulmonary angiograms (CTPA) for pulmonary embolism (PE) ordered in emergency departments, but it is not always well accepted by emergency physicians. We studied a department-endorsed, evidence-based clinical protocol that included the PE rule-out criteria (PERC) rule, multi-modal education using principles of knowledge translation (KT), and clinical decision support embedded in our order entry system, to decrease the number of unnecessary CTPA ordered. We performed a historically controlled observational before-after study for one year pre- and post-implementation of a departmentally-endorsed protocol. We included patients > 18 in whom providers suspected PE and who did not have a contraindication to CTPA. Providers entered clinical information into a diagnostic pathway via computerized order entry. Prior to protocol implementation, we provided education to ordering providers. The primary outcome measure was the number of CTPA ordered per 1,000 visits one year before vs. after implementation. CTPA declined from 1,033 scans for 98,028 annual visits (10.53 per 1,000 patient visits (95% CI [9.9-11.2]) to 892 scans for 101,172 annual visits (8.81 per 1,000 patient visits (95% CI [8.3-9.4]) p<0.001. The absolute reduction in PACT ordered was 1.72 per 1,000 visits (a 16% reduction). Patient characteristics were similar for both periods. Knowledge translation clinical decision support using the PERC rule significantly reduced the number of CTPA ordered.

[Current situation and development trend of Chinese medicine information research].

PubMed

Dong, Yan; Cui, Meng

2013-04-01

Literature resource service was the main service that Chinese medicine (CM) information offered. But in recent years users have started to request the health information knowledge service. The CM information researches and application service mainly included: (1) the need of strength studies on theory, application of technology, information retrieval, and information standard development; (2) Information studies need to support clinical decision making, new drug research; (3) Quick response based on the network monitoring and support to emergency countermeasures. CM information researches have the following treads: (1) developing the theory system structure of CM information; (2) studying the methodology system of CM information; (3) knowledge discovery and knowledge innovation.

Using a Context-aware Medical Application to Address Information Needs for Extubation Decisions

PubMed Central

Zhu, Xinxin; Lord, William

2005-01-01

Information overload has been one of the causes of preventable medical errors [1] and escalating costs [2]. A context-aware application with embedded clinical knowledge is proposed to provide practitioners with the appropriate amount of information and content. We developed a prototype of a context-aware medical application to address clinicians’ information needs that arise in a data-intensive unit, the Cardio-Thoracic Intensive Care Unit (CTICU). A major clinical decision supported by the prototype, the extubation decision, is illustrated. PMID:16779455

Localising and tailoring research evidence helps public health decision making.

PubMed

van der Graaf, Peter; Cheetham, Mandy; McCabe, Karen; Rushmer, Rosemary

2018-05-29

Published research evidence is typically not readily applicable to practice but needs to be actively mobilised. This paper explores the mechanisms used by information professionals with a specific knowledge mobilisation role to make evidence useful for local decision making and planning of public health interventions. Data are drawn from a NIHR project that studied how, when, where and by whom published research evidence is used in commissioning and planning across two sites (one in England and one in Scotland). Data included 11 in-depth interviews with information professionals, observations at meetings and documentary analysis. Published research evidence is made fit for local commissioning and planning purposes by information professionals through two mechanisms. They localise evidence (relate evidence to local context and needs) and tailor it (present actionable messages). Knowledge mobilisation roles of information professionals are not recognised and researched. Information professionals contribute to the 'inform' and 'relational' functions of knowledge mobilisation; however, they are less involved in improving the institutional environment for sustainable knowledge sharing. Information professionals are instrumental in shaping what evidence enters local decision making processes. Identifying and supporting knowledge mobilisation roles within health libraries should be the focus of future research and training. © 2018 Health Libraries Group.

The Development of a Decision Support System for Mobile Learning: A Case Study in Taiwan

ERIC Educational Resources Information Center

Chiu, Po-Sheng; Huang, Yueh-Min

2016-01-01

While mobile learning (m-learning) has considerable potential, most of previous strategies for developing this new approach to education were analysed using the knowledge, experience and judgement of individuals, with the support of statistical software. Although these methods provide systematic steps for the implementation of m-learning…

An Overview of Judgment and Decision Making Research Through the Lens of Fuzzy Trace Theory.

PubMed

Setton, Roni; Wilhelms, Evan; Weldon, Becky; Chick, Christina; Reyna, Valerie

2014-12-01

We present the basic tenets of fuzzy trace theory, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed. In doing so, we highlight how it is distinguished from traditional models of decision making in that gist reasoning plays a central role. The theory also distinguishes advanced intuition from primitive impulsivity. It predicts that different sorts of errors occur with respect to each component of judgment and decision making: background knowledge, representation, retrieval, and processing. Classic errors in the judgment and decision making literature, such as risky-choice framing and the conjunction fallacy, are accounted for by fuzzy trace theory and new results generated by the theory contradict traditional approaches. We also describe how developmental changes in brain and behavior offer crucial insight into adult cognitive processing. Research investigating brain and behavior in developing and special populations supports fuzzy trace theory's predictions about reliance on gist processing.

An Overview of Judgment and Decision Making Research Through the Lens of Fuzzy Trace Theory

PubMed Central

Setton, Roni; Wilhelms, Evan; Weldon, Becky; Chick, Christina; Reyna, Valerie

2017-01-01

We present the basic tenets of fuzzy trace theory, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed. In doing so, we highlight how it is distinguished from traditional models of decision making in that gist reasoning plays a central role. The theory also distinguishes advanced intuition from primitive impulsivity. It predicts that different sorts of errors occur with respect to each component of judgment and decision making: background knowledge, representation, retrieval, and processing. Classic errors in the judgment and decision making literature, such as risky-choice framing and the conjunction fallacy, are accounted for by fuzzy trace theory and new results generated by the theory contradict traditional approaches. We also describe how developmental changes in brain and behavior offer crucial insight into adult cognitive processing. Research investigating brain and behavior in developing and special populations supports fuzzy trace theory’s predictions about reliance on gist processing. PMID:28725239

Thoughtflow: Standards and Tools for Provenance Capture and Workflow Definition to Support Model‐Informed Drug Discovery and Development

PubMed Central

Wilkins, JJ; Chan, PLS; Chard, J; Smith, G; Smith, MK; Beer, M; Dunn, A; Flandorfer, C; Franklin, C; Gomeni, R; Harnisch, L; Kaye, R; Moodie, S; Sardu, ML; Wang, E; Watson, E; Wolstencroft, K

2017-01-01

Pharmacometric analyses are complex and multifactorial. It is essential to check, track, and document the vast amounts of data and metadata that are generated during these analyses (and the relationships between them) in order to comply with regulations, support quality control, auditing, and reporting. It is, however, challenging, tedious, error‐prone, and time‐consuming, and diverts pharmacometricians from the more useful business of doing science. Automating this process would save time, reduce transcriptional errors, support the retention and transfer of knowledge, encourage good practice, and help ensure that pharmacometric analyses appropriately impact decisions. The ability to document, communicate, and reconstruct a complete pharmacometric analysis using an open standard would have considerable benefits. In this article, the Innovative Medicines Initiative (IMI) Drug Disease Model Resources (DDMoRe) consortium proposes a set of standards to facilitate the capture, storage, and reporting of knowledge (including assumptions and decisions) in the context of model‐informed drug discovery and development (MID3), as well as to support reproducibility: “Thoughtflow.” A prototype software implementation is provided. PMID:28504472

Patient factors that influence clinicians' decision making in self-management support: A clinical vignette study.

PubMed

Bos-Touwen, Irene D; Trappenburg, Jaap C A; van der Wulp, Ineke; Schuurmans, Marieke J; de Wit, Niek J

2017-01-01

Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals' decision making regarding self-management support. A factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions), in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression. The survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors. This is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient's motivation; unmotivated patients were less likely to receive self-management support. Future tailored interventions should incorporate strategies to enhance motivation in unmotivated patients. Furthermore, care providers should be better equipped to promote motivational change in their patients.

Newly graduated nurses' use of knowledge sources: a meta-ethnography.

PubMed

Voldbjerg, Siri Lygum; Grønkjaer, Mette; Sørensen, Erik Elgaard; Hall, Elisabeth O C

2016-08-01

To advance evidence on newly graduated nurses' use of knowledge sources. Clinical decisions need to be evidence-based and understanding the knowledge sources that newly graduated nurses use will inform both education and practice. Qualitative studies on newly graduated nurses' use of knowledge sources are increasing though generated from scattered healthcare contexts. Therefore, a metasynthesis of qualitative research on what knowledge sources new graduates use in decision-making was conducted. Meta-ethnography. Nineteen reports, representing 17 studies, published from 2000-2014 were identified from iterative searches in relevant databases from May 2013-May 2014. Included reports were appraised for quality and Noblit and Hare's meta-ethnography guided the interpretation and synthesis of data. Newly graduated nurses' use of knowledge sources during their first 2-year postgraduation were interpreted in the main theme 'self and others as knowledge sources,' with two subthemes 'doing and following' and 'knowing and doing,' each with several elucidating categories. The metasynthesis revealed a line of argument among the report findings underscoring progression in knowledge use and perception of competence and confidence among newly graduated nurses. The transition phase, feeling of confidence and ability to use critical thinking and reflection, has a great impact on knowledge sources incorporated in clinical decisions. The synthesis accentuates that for use of newly graduated nurses' qualifications and skills in evidence-based practice, clinical practice needs to provide a supportive environment which nurtures critical thinking and questions and articulates use of multiple knowledge sources. © 2016 John Wiley & Sons Ltd.

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”.

Enabling Responsible Energy Decisions: What People Know, Want to Know, and Need to Know about Climate Change

NASA Astrophysics Data System (ADS)

PytlikZillig, L. M.; Tomkins, A. J.; Harrington, J. A.

2012-12-01

As part of a broader regional effort focused on climate change education and rural communities, this paper focuses on a specific effort to understand effective approaches to two presumably complementary goals: The goal of increasing knowledge about climate change and climate science in a community, and the goal of having communities use climate change and climate science information when making decisions. In this paper, we explore the argument that people do not need or want to know about climate change, in order to make responsible and sustainable energy decisions. Furthermore, we hypothesize that involvement in making responsible and sustainable energy decisions will increase openness and readiness to process climate science information, and thus increase learning about climate change in subsequent exposures to such information. Support for these hypotheses would suggest that rather than encouraging education to enable action (including engagement in attempts to make responsible decisions), efforts should focus on encouraging actions first and education second. To investigate our hypotheses, we will analyze and report results from efforts to engage residents from a medium-sized Midwestern city to give input on future programs involving sustainable energy use. The engagement process (which will not be complete until after the AGU deadline) involves an online survey and an optional face-to-face discussion with city officials and experts in energy-related areas. The online survey includes brief information about current local energy programs, questions assessing knowledge of climate change, and an open-ended question asking what additional information residents need in order to make good decisions and recommendations concerning the energy programs. To examine support for our hypotheses, we will report (1) relationships between subjective and objective knowledge of climate science and willingness to attend the face-to-face discussion about the city's energy decisions and actual attendance at the event, (2) a content analysis of what residents say they want and need to know in order to make decisions and recommendations about the city's energy programs, and (3) pilot results from a comparison of learning from a reading about climate change presented prior to the event, after the event, or presented to those who were willing to attend the face-to-face event but did not attend. We will discuss the results in terms of their implications for the relationship between knowledge and behavior, versus change in knowledge and change in behavior.

A knowledge based search tool for performance measures in health care systems.

PubMed

Beyan, Oya D; Baykal, Nazife

2012-02-01

Performance measurement is vital for improving the health care systems. However, we are still far from having accepted performance measurement models. Researchers and developers are seeking comparable performance indicators. We developed an intelligent search tool to identify appropriate measures for specific requirements by matching diverse care settings. We reviewed the literature and analyzed 229 performance measurement studies published after 2000. These studies are evaluated with an original theoretical framework and stored in the database. A semantic network is designed for representing domain knowledge and supporting reasoning. We have applied knowledge based decision support techniques to cope with uncertainty problems. As a result we designed a tool which simplifies the performance indicator search process and provides most relevant indicators by employing knowledge based systems.

Informed decision-making with and for people with dementia - efficacy of the PRODECIDE education program for legal representatives: protocol of a randomized controlled trial (PRODECIDE-RCT).

PubMed

Lühnen, Julia; Haastert, Burkhard; Mühlhauser, Ingrid; Richter, Tanja

2017-09-15

In Germany, the guardianship system provides adults who are no longer able to handle their own affairs a court-appointed legal representative, for support without restriction of legal capacity. Although these representatives only rarely are qualified in healthcare, they nevertheless play decisive roles in the decision-making processes for people with dementia. Previously, we developed an education program (PRODECIDE) to address this shortcoming and tested it for feasibility. Typical, autonomy-restricting decisions in the care of people with dementia-namely, using percutaneous endoscopic gastrostomy (PEG) or physical restrains (PR), or the prescription of antipsychotic drugs (AP)-were the subject areas trained. The training course aims to enhance the competency of legal representatives in informed decision-making. In this study, we will evaluate the efficacy of the PRODECIDE education program. A randomized controlled trial with a six-month follow-up will be conducted to compare the PRODECIDE education program with standard care, enrolling legal representatives (N = 216). The education program lasts 10 h and comprises four modules: A, decision-making processes and methods; and B, C and D, evidence-based knowledge about PEG, PR and AP, respectively. The primary outcome measure is knowledge, which is operationalized as the understanding of decision-making processes in healthcare affairs and in setting realistic expectations about benefits and harms of PEG, PR and AP in people with dementia. Secondary outcomes are sufficient and sustainable knowledge and percentage of persons concerned affected by PEG, FEM or AP. A qualitative process evaluation will be performed. Additionally, to support implementation, a concept for translating the educational contents into e-learning modules will be developed. The study results will show whether the efficacy of the education program could justify its implementation into the regular training curricula for legal representatives. Additionally, it will determine whether an e-learning course provides a valuable backup or even alternative learning strategy. TRN: ISRCTN17960111 , Date: 01/06/2017.

Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support.

PubMed

Bouaud, Jacques; Guézennec, Gilles; Séroussi, Brigitte

2018-01-01

The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitates data integration and management using the same formal mechanisms for both data concepts and information model components. This is particularly true for knowledge-based decision support tools that aim to take advantage of all facets of semantic web technologies in merging ontological reasoning, concept classification, and rule-based inferences. We present an ontology template that combines generic data model components with (parts of) existing termino-ontological resources. The approach is developed for the guideline-based decision support module on breast cancer management within the DESIREE European project. The approach is based on the entity attribute value model and could be extended to other domains.

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.

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.

Understanding nurses' decision-making when managing weaning from mechanical ventilation: a study of novice and experienced critical care nurses in Scotland and Greece.

PubMed

Kydonaki, Kalliopi; Huby, Guro; Tocher, Jennifer; Aitken, Leanne M

2016-02-01

To examine how nurses collect and use cues from respiratory assessment to inform their decisions as they wean patients from ventilatory support. Prompt and accurate identification of the patient's ability to sustain reduction of ventilatory support has the potential to increase the likelihood of successful weaning. Nurses' information processing during the weaning from mechanical ventilation has not been well-described. A descriptive ethnographic study exploring critical care nurses' decision-making processes when weaning mechanically ventilated patients from ventilatory support in the real setting. Novice and expert Scottish and Greek nurses from two tertiary intensive care units were observed in real practice of weaning mechanical ventilation and were invited to participate in reflective interviews near the end of their shift. Data were analysed thematically using concept maps based on information processing theory. Ethics approval and informed consent were obtained. Scottish and Greek critical care nurses acquired patient-centred objective physiological and subjective information from respiratory assessment and previous knowledge of the patient, which they clustered around seven concepts descriptive of the patient's ability to wean. Less experienced nurses required more encounters of cues to attain the concepts with certainty. Subjective criteria were intuitively derived from previous knowledge of patients' responses to changes of ventilatory support. All nurses used focusing decision-making strategies to select and group cues in order to categorise information with certainty and reduce the mental strain of the decision task. Nurses used patient-centred information to make a judgment about the patients' ability to wean. Decision-making strategies that involve categorisation of patient-centred information can be taught in bespoke educational programmes for mechanical ventilation and weaning. Advanced clinical reasoning skills and accurate detection of cues in respiratory assessment by critical care nurses will ensure optimum patient management in weaning mechanical ventilation. © 2016 John Wiley & Sons Ltd.

A reexamination of the evidence for the somatic marker hypothesis: what participants really know in the Iowa gambling task.

PubMed

Maia, Tiago V; McClelland, James L

2004-11-09

Bechara, Damasio, and coworkers [Bechara, A., Damasio, H., Tranel, D. & Damasio, A. R. (1997) Science 275, 1293-1295] have reported that normal participants decide advantageously before knowing the advantageous strategy in a simple card game designed to mimic real-life decision-making. Bechara et al. have used this result to support their view that nonconscious somatic markers can guide advantageous behavior. By using more sensitive methods, we show that participants have much more knowledge about the game than previously thought. In fact, participants report knowledge of the advantageous strategy more reliably than they behave advantageously. Furthermore, when they behave advantageously, their verbal reports nearly always reveal evidence of quantitative knowledge about the outcomes of the decks that would be sufficient to guide such advantageous behavior. In addition, there is evidence that participants also have access to more qualitative reportable knowledge. These results are compatible with the view that, in this task, both overt behavior and verbal reports reflect sampling from consciously accessible knowledge; there is no need to appeal to nonconscious somatic markers. We also discuss the findings of other studies that similarly suggest alternative interpretations of other evidence previously used to support a role for somatic markers in decision-making.

A mixed-methods exploration of the contraceptive experiences of female teens with epilepsy.

PubMed

Manski, Ruth; Dennis, Amanda

2014-09-01

We explored the contraceptive experiences of female teens with epilepsy, including their knowledge and perceptions of interactions between antiepileptic drugs and hormonal contraception and contraceptive decision-making processes. From November 2012 to May 2013, we conducted one online survey (n=114) and 12 online focus group discussions (n=26) with female teens with epilepsy about their contraceptive experiences and unmet needs. Survey data were analyzed using descriptive statistics and focus group transcripts were analyzed thematically using modified grounded theory methods. Both survey and focus group participants reported believing that interactions between epilepsy medications and hormonal contraceptives could lead to reductions in contraceptive efficacy and seizure control. However, their knowledge about these types of medication interactions was often incomplete. Many study participants viewed contraceptive decision making as a difficult process, and some participants reported avoiding hormonal contraceptives because of potential interactions with antiepileptic drugs. Study participants reported relying on health care providers and parents for contraceptive decision-making support. Focus group participants also reported they wanted health care providers to provide more in-depth and comprehensive counseling about contraception, and that they desired peer support with contraceptive decisions. The ability to make informed contraceptive decisions is important for teens with epilepsy as interactions between anti-epileptic drugs and hormonal contraceptives can impact seizure occurrence and lead to an increased risk of unplanned pregnancy. Guidance for providers offering contraceptive care to this population is needed, as well as a contraceptive support tool that empowers teens with epilepsy to advocate for desired health care. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

76 FR 50182 - Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic; Reef Fish Fishery of the Gulf of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-12

..., Shareholders Alliance, and would involve as many as 30 vessel owners associated with that organization... improve the scientific knowledge of red snapper and other reef fish taken from state and Federal waters of the Gulf and to use that knowledge to support fishery management decisions. The EFP, if approved...

Knowledge-Based Information Management for Watershed Analysis in the Pacific Northwest U.S.

Treesearch

Keith Reynolds; Richard Olson; Michael Saunders; Donald Latham; Michael Foster; Bruce Miller; Lawrence Bednar; Daniel Schmoldt; Patrick Cunningham; John Steffenson

1996-01-01

We are developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a variety of themes and other area-specific information, (2) an analysis...

"Whatever Is Comfortable:" Secondary Physical Educators' Curricular Decision Making: Issues of Knowledge and Gendered Performativity

ERIC Educational Resources Information Center

Ferry, Matthew; McCaughtry, Nate

2015-01-01

Throughout history there have been debates as to what content knowledge (CK) is of most value for physical education (PE). Much recent conversation has circulated around the hope that time spent in PE supports students' regular participation in physical activity (PA). Researchers' use of the term PA, however, often stresses the similarities while…

Communication barriers to applying federal research in support of land management in the United States

Treesearch

Vita Wright

2007-01-01

Barriers to effective communication between researchers and managers can ultimately result in barriers to the application of scientific knowledge and technology for land management. Both individual and organizational barriers are important in terms of how they affect the first three stages of the innovation-decision process: 1) knowledge, where an individual is exposed...

Promoting Awareness of Key Resources for Evidence-Informed Decision-making in Public Health: An Evaluation of a Webinar Series about Knowledge Translation Methods and Tools

PubMed Central

Yost, Jennifer; Mackintosh, Jeannie; Read, Kristin; Dobbins, Maureen

2016-01-01

The National Collaborating Centre for Methods and Tools (NCCMT) has developed several resources to support evidence-informed decision-making – the process of distilling and disseminating best available evidence from research, context, and experience – and knowledge translation, applying best evidence in practice. One such resource, the Registry of Methods and Tools, is a free online database of 195 methods and tools to support knowledge translation. Building on the identification of webinars as a strategy to improve the dissemination of information, NCCMT launched the Spotlight on Knowledge Translation Methods and Tools webinar series in 2012 to promote awareness and use of the Registry. To inform continued implementation of this webinar series, NCCMT conducted an evaluation of the series’ potential to improve awareness and use of the methods/tools within the Registry, as well as identify areas for improvement and “what worked.” For this evaluation, the following data were analyzed: electronic follow-up surveys administered immediately following each webinar; an additional electronic survey administered 6 months after two webinars; and Google Analytics for each webinar. As of November 2015, there have been 22 webinars conducted, reaching 2048 people in multiple sectors across Canada and around the world. Evaluation results indicate that the webinars increase awareness about the Registry and stimulate use of the methods/tools. Although webinar attendees were significantly less likely to have used the methods/tools 6 months after webinars, this may be attributed to the lack of an identified opportunity in their work to use the method/tool. Despite technological challenges and requests for further examples of how the methods/tools have been used, there is overwhelming positive feedback that the format, presenters, content, and interaction across webinars “worked.” This evaluation supports that webinars are a valuable strategy for increasing awareness and stimulating use of resources for evidence-informed decision-making and knowledge translation in public health practice. PMID:27148518

Klimanavigator - Climate Navigator - Gateway to climate knowledge in Germany

NASA Astrophysics Data System (ADS)

Schuck-Zöller, Susanne

2013-04-01

Objective More than 50 German research institutions and networks are represented on www.klimanavigator.de, a common platform, where information about their work, and the latest findings from climate research and adaptation can be found. Thus Klimanavigator as a gateway to climate knowledge provides a information portal for those who have to respond to climate change. The internet portal gives an overview of the present state of research and is estimated as a decision support tool for appropriate mitigation and adaptation measures. Target Groups The portal collects the German climate research institutions to publish their scientific knowledge in a non-scientific language. Economists, policymakers, administration and the media are bound to find the names of scientific experts and institutions by an elaborated research tool. Methodology The chapter "Dossiers" is edited by the Klimanavigator-Coordinator CSC. It gathers information to a special issue looked upon from various points of view. Publications of outstanding German scientists are presented side by side, current knowledge is being synthesized, scientifically reviewed and disseminated. The latest news from climate and adaptation research is presented in an own chapter, dedicated to the press releases of the portal members. Via RSS-feed the press releases are collected from the different partner institutions. Thirdly, portraits of the member institutions, that are individually edited by themselves, draw a map of science in Germany and help to find appropriate cooperation partners. For the future further development is being planned. Common Management Klimanavigator is being managed by the partners in common. The main decisions concerning the concept and shape of the portal are made by the partners' assembly. An elected editorial committee decides about the content between the assemblies. The Climate Service Center (part of the Helmholtz-Zentrum Geesthacht) concentrates on facilitating the cooperation, and delivering the technical support. Results/Outcome/Products Map and navigator of climate and adaptation science in Germany Representation of science in Germany and Germany as a country of science Synthesis of knowledge Network of science institutions and projects Decision support tool

Knowledge-based and model-based hybrid methodology for comprehensive waste minimization in electroplating plants

NASA Astrophysics Data System (ADS)

Luo, Keqin

1999-11-01

The electroplating industry of over 10,000 planting plants nationwide is one of the major waste generators in the industry. Large quantities of wastewater, spent solvents, spent process solutions, and sludge are the major wastes generated daily in plants, which costs the industry tremendously for waste treatment and disposal and hinders the further development of the industry. It becomes, therefore, an urgent need for the industry to identify technically most effective and economically most attractive methodologies and technologies to minimize the waste, while the production competitiveness can be still maintained. This dissertation aims at developing a novel WM methodology using artificial intelligence, fuzzy logic, and fundamental knowledge in chemical engineering, and an intelligent decision support tool. The WM methodology consists of two parts: the heuristic knowledge-based qualitative WM decision analysis and support methodology and fundamental knowledge-based quantitative process analysis methodology for waste reduction. In the former, a large number of WM strategies are represented as fuzzy rules. This becomes the main part of the knowledge base in the decision support tool, WMEP-Advisor. In the latter, various first-principles-based process dynamic models are developed. These models can characterize all three major types of operations in an electroplating plant, i.e., cleaning, rinsing, and plating. This development allows us to perform a thorough process analysis on bath efficiency, chemical consumption, wastewater generation, sludge generation, etc. Additional models are developed for quantifying drag-out and evaporation that are critical for waste reduction. The models are validated through numerous industrial experiments in a typical plating line of an industrial partner. The unique contribution of this research is that it is the first time for the electroplating industry to (i) use systematically available WM strategies, (ii) know quantitatively and accurately what is going on in each tank, and (iii) identify all WM opportunities through process improvement. This work has formed a solid foundation for the further development of powerful WM technologies for comprehensive WM in the following decade.

Decision tools in health care: focus on the problem, not the solution.

PubMed

Liu, Joseph; Wyatt, Jeremy C; Altman, Douglas G

2006-01-20

Systematic reviews or randomised-controlled trials usually help to establish the effectiveness of drugs and other health technologies, but are rarely sufficient by themselves to ensure actual clinical use of the technology. The process from innovation to routine clinical use is complex. Numerous computerised decision support systems (DSS) have been developed, but many fail to be taken up into actual use. Some developers construct technologically advanced systems with little relevance to the real world. Others did not determine whether a clinical need exists. With NHS investing 5 billion pounds sterling in computer systems, also occurring in other countries, there is an urgent need to shift from a technology-driven approach to one that identifies and employs the most cost-effective method to manage knowledge, regardless of the technology. The generic term, 'decision tool' (DT), is therefore suggested to demonstrate that these aids, which seem different technically, are conceptually the same from a clinical viewpoint. Many computerised DSSs failed for various reasons, for example, they were not based on best available knowledge; there was insufficient emphasis on their need for high quality clinical data; their development was technology-led; or evaluation methods were misapplied. We argue that DSSs and other computer-based, paper-based and even mechanical decision aids are members of a wider family of decision tools. A DT is an active knowledge resource that uses patient data to generate case specific advice, which supports decision making about individual patients by health professionals, the patients themselves or others concerned about them. The identification of DTs as a consistent and important category of health technology should encourage the sharing of lessons between DT developers and users and reduce the frequency of decision tool projects focusing only on technology. The focus of evaluation should become more clinical, with the impact of computer-based DTs being evaluated against other computer, paper- or mechanical tools, to identify the most cost effective tool for each clinical problem. We suggested the generic term 'decision tool' to demonstrate that decision-making aids, such as computerised DSSs, paper algorithms, and reminders are conceptually the same, so the methods to evaluate them should be the same.

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.

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.

Distributed collaborative environments for predictive battlespace awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.

2003-09-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Situational assessment is crucial in understanding the battlespace. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Decision support technologies can semi-automate activities, such as analysis and planning, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that the commander must fused. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing AFRL research efforts in applying distributed collaborative environments to predictive battlespace awareness.

Smart homes and ambient assisted living applications: from data to knowledge-empowering or overwhelming older adults? Contribution of the IMIA Smart Homes and Ambiant Assisted Living Working Group.

PubMed

Demiris, G; Thompson, H

2011-01-01

As health care systems face limited resources and workforce shortages to address the complex needs of older adult populations, innovative approaches utilizing information technology can support aging. Smart Home and Ambient Assisted Living (SHAAL) systems utilize advanced and ubiquitous technologies including sensors and other devices that are integrated in the residential infrastructure or wearable, to capture data describing activities of daily living and health related events. This paper highlights how data from SHAAL systems can lead to information and knowledge that ultimately improves clinical outcomes and quality of life for older adults as well as quality of health care services. We conducted a review of personal health record applications specifically for older adults and approaches to using information to improve elder care. We present a framework that showcases how data captured from SHAAL systems can be processed to provide meaningful information that becomes part of a personal health record. Synthesis and visualization of information resulting from SHAAL systems can lead to knowledge and support education, delivery of tailored interventions and if needed, transitions in care. Such actions can involve multiple stakeholders as part of shared decision making. SHAAL systems have the potential to support aging and improve quality of life and decision making for older adults and their families. The framework presented in this paper demonstrates how emphasis needs to be placed into extracting meaningful information from new innovative systems that will support decision making. The challenge for informatics designers and researchers is to facilitate an evolution of SHAAL systems expanding beyond demonstration projects to actual interventions that will improve health care for older adults.

Translating research into practice through user-centered design: An application for osteoarthritis healthcare planning.

PubMed

Carr, Eloise Cj; Babione, Julie N; Marshall, Deborah

2017-08-01

To identify the needs and requirements of the end users, to inform the development of a user-interface to translate an existing evidence-based decision support tool into a practical and usable interface for health service planning for osteoarthritis (OA) care. We used a user-centered design (UCD) approach that emphasized the role of the end-users and is well-suited to knowledge translation (KT). The first phase used a needs assessment focus group (n=8) and interviews (n=5) with target users (health care planners) within a provincial health care organization. The second phase used a participatory design approach, with two small group sessions (n=6) to explore workflow, thought processes, and needs of intended users. The needs assessment identified five design recommendations: ensuring the user-interface supports the target user group, allowing for user-directed data explorations, input parameter flexibility, clear presentation, and provision of relevant definitions. The second phase identified workflow insights from a proposed scenario. Graphs, the need for a visual overview of the data, and interactivity were key considerations to aid in meaningful use of the model and knowledge translation. A UCD approach is well suited to identify health care planners' requirements when using a decision support tool to improve health service planning and management of OA. We believe this is one of the first applications to be used in planning for health service delivery. We identified specific design recommendations that will increase user acceptability and uptake of the user-interface and underlying decision support tool in practice. Our approach demonstrated how UCD can be used to enable knowledge translation. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Technosocial Predictive Analytics in Support of Naturalistic Decision Making

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

Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.

2009-06-23

A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledgemore » management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.« less

Supporting Evidence-Informed Teaching in Biomedical and Health Professions Education Through Knowledge Translation: An Interdisciplinary Literature Review.

PubMed

Tractenberg, Rochelle E; Gordon, Morris

2017-01-01

Phenomenon: The purpose of "systematic" reviews/reviewers of medical and health professions educational research is to identify best practices. This qualitative article explores the question of whether systematic reviews can support "evidence informed" teaching and contrasts traditional systematic reviewing with a knowledge translation (KT) approach to this objective. Degrees of freedom analysis (DOFA) is used to examine the alignment of systematic review methods with educational research and the pedagogical strategies and approaches that might be considered with a decision-making framework developed to support valid assessment. This method is also used to explore how KT can be used to inform teaching and learning. The nature of educational research is not compatible with most (11/14) methods for systematic review. The inconsistency of systematic reviewing with the nature of educational research impedes both the identification and implementation of "best-evidence" pedagogy and teaching. This is primarily because research questions that do support the purposes of review do not support educational decision making. By contrast to systematic reviews of the literature, both a DOFA and KT are fully compatible with informing teaching using evidence. A DOFA supports the translation of theory to a specific teaching or learning case, so could be considered a type of KT. The DOFA results in a test of alignment of decision options with relevant educational theory, and KT leads to interventions in teaching or learning that can be evaluated. Examples of how to structure evaluable interventions are derived from a KT approach that are simply not available from a systematic review. Insights: Systematic reviewing of current empirical educational research is not suitable for deriving or supporting best practices in education. However, both "evidence-informed" and scholarly approaches to teaching can be supported as KT projects, which are inherently evaluable and can generate actionable evidence about whether the decision or intervention worked for students, instructors, and the institution. A DOFA can also support evidence- and theory-informed teaching to develop an understanding of what works, why, and for whom. Thus KT, but not systematic reviewing, can support decision making around pedagogy (and pedagogical innovation) that can also inform new teaching and learning initiatives; it can also point to new avenues of empirical research in education that are informed by, and can inform, theory.

Middle-aged women's decisions about body weight management: needs assessment and testing of a knowledge translation tool.

PubMed

Stacey, Dawn; Jull, Janet; Beach, Sarah; Dumas, Alex; Strychar, Irene; Adamo, Kristi; Brochu, Martin; Prud'homme, Denis

2015-04-01

This study aims to assess middle-aged women's needs when making body weight management decisions and to evaluate a knowledge translation tool for addressing their needs. A mixed-methods study used an interview-guided theory-based survey of professional women aged 40 to 65 years. The tool summarized evidence to address their needs and enabled women to monitor actions taken. Acceptability and usability were reported descriptively. Sixty female participants had a mean body mass index of 28.0 kg/m(2) (range, 17.0-44.9 kg/m(2)), and half were premenopausal. Common options for losing (82%) or maintaining (18%) weight included increasing physical activity (60%), eating healthier (57%), and getting support (40%). Decision-making involved getting information on options (52%), soliciting others' decisions/advice (20%), and being self-motivated (20%). Preferred information sources included written information (97%), counseling (90%), and social networking websites (43%). Five professionals (dietitian, personal trainer, occupational therapist, and two physicians) had similar responses. Of 53 women sent the tool, 27 provided acceptability feedback. They rated it as good to excellent for information on menopause (96%), body weight changes (85%), and managing body weight (85%). Most would tell others about it (81%). After 4 weeks of use, 25 women reported that the wording made sense (96%) and that the tool had clear instructions (92%) and was easy to use across time (88%). The amount of information was rated as just right (64%), but the tool had limited space for responding (72%). When making decisions about body weight management, women's needs were "getting information" and "getting support." The knowledge translation tool was acceptable and usable, but further evaluation is required.

Middle-aged women’s decisions about body weight management: needs assessment and testing of a knowledge translation tool

PubMed Central

Stacey, Dawn; Jull, Janet; Beach, Sarah; Dumas, Alex; Strychar, Irene; Adamo, Kristi; Brochu, Martin; Prud’homme, Denis

2015-01-01

Abstract Objective This study aims to assess middle-aged women’s needs when making body weight management decisions and to evaluate a knowledge translation tool for addressing their needs. Methods A mixed-methods study used an interview-guided theory-based survey of professional women aged 40 to 65 years. The tool summarized evidence to address their needs and enabled women to monitor actions taken. Acceptability and usability were reported descriptively. Results Sixty female participants had a mean body mass index of 28.0 kg/m2 (range, 17.0-44.9 kg/m2), and half were premenopausal. Common options for losing (82%) or maintaining (18%) weight included increasing physical activity (60%), eating healthier (57%), and getting support (40%). Decision-making involved getting information on options (52%), soliciting others’ decisions/advice (20%), and being self-motivated (20%). Preferred information sources included written information (97%), counseling (90%), and social networking websites (43%). Five professionals (dietitian, personal trainer, occupational therapist, and two physicians) had similar responses. Of 53 women sent the tool, 27 provided acceptability feedback. They rated it as good to excellent for information on menopause (96%), body weight changes (85%), and managing body weight (85%). Most would tell others about it (81%). After 4 weeks of use, 25 women reported that the wording made sense (96%) and that the tool had clear instructions (92%) and was easy to use across time (88%). The amount of information was rated as just right (64%), but the tool had limited space for responding (72%). Conclusions When making decisions about body weight management, women’s needs were “getting information” and “getting support.” The knowledge translation tool was acceptable and usable, but further evaluation is required. PMID:25816120

Informed Decision-Making in the Context of Prenatal Chromosomal Microarray.

PubMed

Baker, Jessica; Shuman, Cheryl; Chitayat, David; Wasim, Syed; Okun, Nan; Keunen, Johannes; Hofstedter, Renee; Silver, Rachel

2018-03-07

The introduction of chromosomal microarray (CMA) into the prenatal setting has involved considerable deliberation due to the wide range of possible outcomes (e.g., copy number variants of uncertain clinical significance). Such issues are typically discussed in pre-test counseling for pregnant women to support informed decision-making regarding prenatal testing options. This research study aimed to assess the level of informed decision-making with respect to prenatal CMA and the factor(s) influencing decision-making to accept CMA for the selected prenatal testing procedure (i.e., chorionic villus sampling or amniocentesis). We employed a questionnaire that was adapted from a three-dimensional measure previously used to assess informed decision-making with respect to prenatal screening for Down syndrome and neural tube defects. This measure classifies an informed decision as one that is knowledgeable, value-consistent, and deliberated. Our questionnaire also included an optional open-ended question, soliciting factors that may have influenced the participants' decision to accept prenatal CMA; these responses were analyzed qualitatively. Data analysis on 106 participants indicated that 49% made an informed decision (i.e., meeting all three criteria of knowledgeable, deliberated, and value-consistent). Analysis of 59 responses to the open-ended question showed that "the more information the better" emerged as the dominant factor influencing both informed and uninformed participants' decisions to accept prenatal CMA. Despite learning about the key issues in pre-test genetic counseling, our study classified a significant portion of women as making uninformed decisions due to insufficient knowledge, lack of deliberation, value-inconsistency, or a combination of these three measures. Future efforts should focus on developing educational approaches and counseling strategies to effectively increase the rate of informed decision-making among women offered prenatal CMA.

NASA Biomedical Informatics Capabilities and Needs

NASA Technical Reports Server (NTRS)

Johnson-Throop, Kathy A.

2009-01-01

To improve on-orbit clinical capabilities by developing and providing operational support for intelligent, robust, reliable, and secure, enterprise-wide and comprehensive health care and biomedical informatics systems with increasing levels of autonomy, for use on Earth, low Earth orbit & exploration class missions. Biomedical Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision-making process, at the time and place that a decision needs to be made.

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.

Identified research directions for using manufacturing knowledge earlier in the product lifecycle

PubMed Central

Hedberg, Thomas D.; Hartman, Nathan W.; Rosche, Phil; Fischer, Kevin

2016-01-01

Design for Manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within Computer-Aided Design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customization on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities, or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is how can manufacturing knowledge, depending on its definition, be used earlier in the product lifecycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behavior, and context characteristics of product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product lifecycle. PMID:27990027

Identified research directions for using manufacturing knowledge earlier in the product lifecycle.

PubMed

Hedberg, Thomas D; Hartman, Nathan W; Rosche, Phil; Fischer, Kevin

2017-01-01

Design for Manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within Computer-Aided Design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customization on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities, or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is how can manufacturing knowledge, depending on its definition, be used earlier in the product lifecycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behavior, and context characteristics of product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product lifecycle.

Shared Decision Making Interventions: Theoretical and Empirical Evidence with Implications for Health Literacy.

PubMed

Stacey, Dawn; Hill, Sophie; McCaffery, Kirsten; Boland, Laura; Lewis, Krystina B; Horvat, Lidia

2017-01-01

Basic health literacy is required for making health decisions. The aim of this chapter is to discuss the use of shared decision making interventions for supporting patient involvement in making health decisions. The chapter provides a definition of shared decision making and discusses the link between shared decision making and the three levels of health literacy: functional, communicative/interactive, and critical. The Interprofessional Shared Decision Making Model is used to identify the various players involved: the patient, the family/surrogate/significant others, decision coach, and health care professionals. When patients are involved in shared decision making, they have better health outcomes, better healthcare experiences, and likely lower costs. Yet, their degree of involvement is influenced by their level of health literacy. Interventions to facilitate shared decision making are patient decision aids, decision coaching, and question prompt lists. Patient decision aids have been shown to improve knowledge, accurate risk perceptions, and chosen options congruent with patients' values. Decision coaching improves knowledge and patient satisfaction. Question prompts also improve satisfaction. When shared decision making interventions have been evaluated with patients presumed to have lower health literacy, they appeared to be more beneficial to disadvantaged groups compared to those with higher literacy or better socioeconomic status. However, special attention needs to be applied when designing these interventions for populations with lower literacy. Two case exemplars are provided to illustrate the design and choice of interventions to better support patients with varying levels of health literacy. Despite evidence indicating these interventions are effective for involving patients in shared decision making, few are used in routine clinical practice. To increase their uptake, implementation strategies need to overcome barriers interfering with their use. Implementation strategies include training health care professionals, adopting SDM interventions that target patients, such as patient decision aids, and monitor patients' decisional comfort using the SURE test. Integrating health literacy principles is important when developing interventions that facilitate shared decision making and essential to avoid inadvertently producing higher inequalities between patients with varying levels of health literacy.

Reviewing model application to support animal health decision making.

PubMed

Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

2011-04-01

Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

7 CFR 3430.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... financial assistance that provides support or stimulation to accomplish a public purpose. Awards may be..., curriculum development, instructional materials and equipment, and innovative teaching methodologies... knowledge and informal educational programs to people, enabling them to make practical decisions. Food and...

A decision support tool for selecting traffic control devices.

DOT National Transportation Integrated Search

2015-07-01

The Federal Highway Administration (FHWA) and transportation profession continue updating and : publishing the Manual on Uniform Traffic Control Devices (MUTCD). However, it is beyond the scope of : the MUTCD to provide the breadth of knowledge neces...

Knowledge engineering for adverse drug event prevention: on the design and development of a uniform, contextualized and sustainable knowledge-based framework.

PubMed

Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Niès, Julie; Durand-Texte, Ludovic; McNair, Peter; Beuscart, Régis; Maglaveras, Nicos

2012-06-01

The primary aim of this work was the development of a uniform, contextualized and sustainable knowledge-based framework to support adverse drug event (ADE) prevention via Clinical Decision Support Systems (CDSSs). In this regard, the employed methodology involved first the systematic analysis and formalization of the knowledge sources elaborated in the scope of this work, through which an application-specific knowledge model has been defined. The entire framework architecture has been then specified and implemented by adopting Computer Interpretable Guidelines (CIGs) as the knowledge engineering formalism for its construction. The framework integrates diverse and dynamic knowledge sources in the form of rule-based ADE signals, all under a uniform Knowledge Base (KB) structure, according to the defined knowledge model. Equally important, it employs the means to contextualize the encapsulated knowledge, in order to provide appropriate support considering the specific local environment (hospital, medical department, language, etc.), as well as the mechanisms for knowledge querying, inference, sharing, and management. In this paper, we present thoroughly the establishment of the proposed knowledge framework by presenting the employed methodology and the results obtained as regards implementation, performance and validation aspects that highlight its applicability and virtue in medication safety. Copyright © 2012 Elsevier Inc. All rights reserved.

Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.

PubMed

Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng

2018-04-20

Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.

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).

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.

Evaluating Adaptation of a Cancer Clinical Trial Decision Aid for Rural Cancer Patients: A Mixed-Methods Approach.

PubMed

Pathak, Swati; George, Nerissa; Monti, Denise; Robinson, Kathy; Politi, Mary C

2018-06-03

Rural-residing cancer patients often do not participate in clinical trials. Many patients misunderstand cancer clinical trials and their rights as participant. The purpose of this study is to modify a previously developed cancer clinical trials decision aid (DA), incorporating the unique needs of rural populations, and test its impact on knowledge and decision outcomes. The study was conducted in two phases. Phase I recruited 15 rural-residing cancer survivors in a qualitative usability study. Participants navigated the original DA and provided feedback regarding usability and implementation in rural settings. Phase II recruited 31 newly diagnosed rural-residing cancer patients. Patients completed a survey before and after using the revised DA, R-CHOICES. Primary outcomes included decisional conflict, decision self-efficacy, knowledge, communication self-efficacy, and attitudes towards and willingness to consider joining a trial. In phase I, the DA was viewed positively by rural-residing cancer survivors. Participants provided important feedback about factors rural-residing patients consider when thinking about trial participation. In phase II, after using R-CHOICES, participants had higher certainty about their choice (mean post-test = 3.10 vs. pre-test = 2.67; P = 0.025) and higher trial knowledge (mean percentage correct at post-test = 73.58 vs. pre-test = 57.77; P < 0.001). There was no significant change in decision self-efficacy, communication self-efficacy, and attitudes towards or willingness to join trials. The R-CHOICES improved rural-residing patients' knowledge of cancer clinical trials and reduced conflict about making a trial decision. More research is needed on ways to further support decisions about trial participation among this population.

Cue acquisition: A feature of Malawian midwives decision making process to support normality during the first stage of labour.

PubMed

Chodzaza, Elizabeth; Haycock-Stuart, Elaine; Holloway, Aisha; Mander, Rosemary

2018-03-01

to explore Malawian midwives decision making when caring for women during the first stage of labour in the hospital setting. this focused ethnographic study examined the decision making process of 9 nurse-midwives with varying years of clinical experience in the real world setting of an urban and semi urban hospital from October 2013 to May 2014.This was done using 27 participant observations and 27 post-observation in-depth interviews over a period of six months. Qualitative data analysis software, NVivo 10, was used to assist with data management for the analysis. All data was analysed using the principle of theme and category formation. analysis revealed a six-stage process of decision making that include a baseline for labour, deciding to admit a woman to labour ward, ascertaining the normal physiological progress of labour, supporting the normal physiological progress of labour, embracing uncertainty: the midwives' construction of unusual labour as normal, dealing with uncertainty and deciding to intervene in unusual labour. This six-stage process of decision making is conceptualised as the 'role of cue acquisition', illustrating the ways in which midwives utilise their assessment of labouring women to reason and make decisions on how to care for them in labour. Cue acquisition involved the midwives piecing together segments of information they obtained from the women to formulate an understanding of the woman's birthing progress and inform the midwives decision making process. This understanding of cue acquisition by midwives is significant for supporting safe care in the labour setting. When there was uncertainty in a woman's progress of labour, midwives used deductive reasoning, for example, by cross-checking and analysing the information obtained during the span of labour. Supporting normal labour physiological processes was identified as an underlying principle that shaped the midwives clinical judgement and decision making when they cared for women in labour. the significance of this study is in the new understanding and insight into the process of midwifery decision making. Whilst the approach to decision making by the midwives requires further testing and refinement in order to explore implications for practice, the findings here provide new conceptual and practical clarity of midwifery decision making. The work contributes to the identified lack of knowledge of how midwives working clinically, in the 'real world setting. These findings therefore, contribute to this body of knowledge with regards to our understanding of decision making of midwives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Management of complex knowledge in planning for sustainable development: The use of multi-criteria decision aids

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

Kain, Jaan-Henrik; Soederberg, Henriette

2008-01-15

The vision of sustainable development entails new and complex planning situations, confronting local policy makers with changing political conditions, different content in decision making and planning and new working methods. Moreover, the call for sustainable development has been a major driving force towards an increasingly multi-stakeholder planning system. This situation requires competence in working in, and managing, groups of actors, including not only experts and project owners but also other categories of stakeholders. Among other qualities, such competence requires a working strategy aimed at integrating various, and sometimes incommensurable, forms of knowledge to construct a relevant and valid knowledge basemore » prior to decision making. Consequently, there lies great potential in methods that facilitate the evaluation of strategies for infrastructural development across multiple knowledge areas, so-called multi-criteria decision aids (MCDAs). In the present article, observations from six case studies are discussed, where the common denominators are infrastructural planning, multi-stakeholder participation and the use of MCDAs as interactive decision support. Three MCDAs are discussed - NAIADE, SCA and STRAD - with an emphasis on how they function in their procedural context. Accordingly, this is not an analysis of MCDA algorithms, of software programming aspects or of MCDAs as context-independent 'decision machines'-the focus is on MCDAs as actor systems, not as expert systems. The analysis is carried out across four main themes: (a) symmetrical management of different forms of knowledge; (b) management of heterogeneity, pluralism and conflict; (c) functionality and ease of use; and (d) transparency and trust. It shows that STRAD, by far, seems to be the most useful MCDA in interactive settings. NAIADE and SCA are roughly equivalent but have their strengths and weaknesses in different areas. Moreover, it was found that some MCDA issues require further attention, i.e., regarding transparency and understandability; qualitative/quantitative knowledge input; switching between different modes of weighting; software flexibility; as well as graphic and user interfaces.« less

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

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.

A multiobjective decision support/numerical modeling approach for design and evaluation of shallow landfill burial systems

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

Ascough, II, James Clifford

1992-05-01

The capability to objectively evaluate design performance of shallow landfill burial (SLB) systems is of great interest to diverse scientific disciplines, including hydrologists, engineers, environmental scientists, and SLB regulators. The goal of this work was to develop and validate a procedure for the nonsubjective evaluation of SLB designs under actual or simulated environmental conditions. A multiobjective decision module (MDM) based on scoring functions (Wymore, 1988) was implemented to evaluate SLB design performance. Input values to the MDM are provided by hydrologic models. The MDM assigns a total score to each SLB design alternative, thereby allowing for rapid and repeatable designmore » performance evaluation. The MDM was validated for a wide range of SLB designs under different climatic conditions. Rigorous assessment of SLB performance also requires incorporation of hydrologic probabilistic analysis and hydrologic risk into the overall design. This was accomplished through the development of a frequency analysis module. The frequency analysis module allows SLB design event magnitudes to be calculated based on the hydrologic return period. The multiobjective decision and freqeuncy anslysis modules were integrated in a decision support system (DSS) framework, SLEUTH (Shallow Landfill Evaluation Using Transport and Hydrology). SLEUTH is a Microsoft Windows {trademark} application, and is written in the Knowledge Pro Windows (Knowledge Garden, Inc., 1991) development language.« less

LAMDA at TREC CDS track 2015: Clinical Decision Support Track

DTIC Science & Technology

2015-11-20

outperforms all the other vector space models supported by Elasticsearch. MetaMap is the online tool that maps biomedical text to the Metathesaurus, and...cases. The medical knowledge consists of 700,000 biomedical documents supported by the PubMed Central [3] which is online digital database freely...Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science, ICT , and Future Planning (MSIP

The impact of the Rasouli decision: a Survey of Canadian intensivists.

PubMed

Cape, David; Fox-Robichaud, Alison; Turgeon, Alexis F; Seely, Andrew; Hall, Richard; Burns, Karen; Singal, Rohit K; Dodek, Peter; Bagshaw, Sean; Sibbald, Robert; Downar, James

2016-03-01

In a landmark 2013 decision, the Supreme Court of Canada (SCC) ruled that the withdrawal of life support in certain circumstances is a treatment requiring patient or substitute decision maker (SDM) consent. How intensive care unit (ICU) physicians perceive this ruling is unknown. To determine physician knowledge of and attitudes towards the SCC decision, as well as the self-reported changes in practice attributed to the decision. We surveyed intensivists at university hospitals across Canada. We used a knowledge test and Likert-scale questions to measure respondent knowledge of and attitudes towards the ruling. We used vignettes to assess decision making in cases of intractable physician-SDM conflict over the management of patients with very poor prognoses. We compared management choices pre-SCC decision versus post-SCC decision versus the subjective, respondent-defined most appropriate choice. Responses were compared across predefined subgroups. We performed qualitative analysis on free-text responses. We received 82 responses (response rate=42%). Respondents reported providing high levels of self-defined inappropriate treatment. Although most respondents reported no change in practice, there was a significant overall shift towards higher intensity and less subjectively appropriate management after the SCC decision. Attitudes to the SCC decision and approaches to disputes over end-of-life (EoL) care in the ICU were highly variable. There were no significant differences among predefined subgroups. Many Canadian ICU physicians report providing a higher intensity of treatment, and less subjectively appropriate treatment, in situations of dispute over EoL care after the Supreme Court of Canada's ruling in Cuthbertson versus Rasouli. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Knowledge acquisition for medical diagnosis using collective intelligence.

PubMed

Hernández-Chan, G; Rodríguez-González, A; Alor-Hernández, G; Gómez-Berbís, J M; Mayer-Pujadas, M A; Posada-Gómez, R

2012-11-01

The wisdom of the crowds (WOC) is the process of taking into account the collective opinion of a group of individuals rather than a single expert to answer a question. Based on this assumption, the use of processes based on WOC techniques to collect new biomedical knowledge represents a challenging and cutting-edge trend on biomedical knowledge acquisition. The work presented in this paper shows a new schema to collect diagnosis information in Diagnosis Decision Support Systems (DDSS) based on collective intelligence and consensus methods.

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

Time to decision: the drivers of innovation adoption decisions

NASA Astrophysics Data System (ADS)

Ciganek, Andrew Paul; (Dave) Haseman, William; Ramamurthy, K.

2014-03-01

Organisations desire timeliness. Timeliness facilitates a better responsiveness to changes in an organisation's external environment to either attain or maintain competitiveness. Despite its importance, decision timeliness has not been explicitly examined. Decision timeliness is measured in this study as the time taken to commit to a decision. The research objective is to identify the drivers of decision timeliness in the context of adopting service-oriented architecture (SOA), an innovation for enterprise computing. A research model rooted in the technology-organisation-environment (TOE) framework is proposed and tested with data collected in a large-scale study. The research variables have been examined before in the context of adoption, but their applicability to the timeliness of innovation decision-making has not received much attention and their salience is unclear. The results support multiple hypothesised relationships, including the finding that a risk-oriented organisational culture as well as normative and coercive pressures accelerates decision timeliness. Top management support as well as the traditional innovation attributes (compatibility, relative advantage and complexity/ease-of-use) were not found to be significant when examining their influence on decision timeliness, which appears inconsistent with generally accepted knowledge and deserves further examination.

Coordinating complex decision support activities across distributed applications

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1994-01-01

Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

Use of Knowledge Base Systems (EMDS) in Strategic and Tactical Forest Planning

NASA Astrophysics Data System (ADS)

Jensen, M. E.; Reynolds, K.; Stockmann, K.

2008-12-01

The USDA Forest Service 2008 Planning Rule requires Forest plans to provide a strategic vision for maintaining the sustainability of ecological, economic, and social systems across USFS lands through the identification of desired conditions and objectives. In this paper we show how knowledge-based systems can be efficiently used to evaluate disparate natural resource information to assess desired conditions and related objectives in Forest planning. We use the Ecosystem Management Decision Support (EMDS) system (http://www.institute.redlands.edu/emds/), which facilitates development of both logic-based models for evaluating ecosystem sustainability (desired conditions) and decision models to identify priority areas for integrated landscape restoration (objectives). The study area for our analysis spans 1,057 subwatersheds within western Montana and northern Idaho. Results of our study suggest that knowledge-based systems such as EMDS are well suited to both strategic and tactical planning and that the following points merit consideration in future National Forest (and other land management) planning efforts: 1) Logic models provide a consistent, transparent, and reproducible method for evaluating broad propositions about ecosystem sustainability such as: are watershed integrity, ecosystem and species diversity, social opportunities, and economic integrity in good shape across a planning area? The ability to evaluate such propositions in a formal logic framework also allows users the opportunity to evaluate statistical changes in outcomes over time, which could be very useful for regional and national reporting purposes and for addressing litigation; 2) The use of logic and decision models in strategic and tactical Forest planning provides a repository for expert knowledge (corporate memory) that is critical to the evaluation and management of ecosystem sustainability over time. This is especially true for the USFS and other federal resource agencies, which are likely to experience rapid turnover in tenured resource specialist positions within the next five years due to retirements; 3) Use of logic model output in decision models is an efficient method for synthesizing the typically large amounts of information needed to support integrated landscape restoration. Moreover, use of logic and decision models to design customized scenarios for integrated landscape restoration, as we have demonstrated with EMDS, offers substantial improvements to traditional GIS-based procedures such as suitability analysis. To our knowledge, this study represents the first attempt to link evaluations of desired conditions for ecosystem sustainability in strategic planning to tactical planning regarding the location of subwatersheds that best meet the objectives of integrated landscape restoration. The basic knowledge-based approach implemented in EMDS, with its logic (NetWeaver) and decision (Criterion Decision Plus) engines, is well suited both to multi-scale strategic planning and to multi-resource tactical planning.

Heuristics: foundations for a novel approach to medical decision making.

PubMed

Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V

2015-03-01

Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.

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...

Use of handheld computers in clinical practice: a systematic review.

PubMed

Mickan, Sharon; Atherton, Helen; Roberts, Nia Wyn; Heneghan, Carl; Tilson, Julie K

2014-07-06

Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals' use of handheld computers improve their access to information and support clinical decision making at the point of care? A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study's aim for assessing the impact of handheld computer use. We included seven randomised trials investigating medical or nursing staffs' use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Healthcare professionals' use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes.

Use of handheld computers in clinical practice: a systematic review

PubMed Central

2014-01-01

Background Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals’ use of handheld computers improve their access to information and support clinical decision making at the point of care? Methods A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study’s aim for assessing the impact of handheld computer use. Results We included seven randomised trials investigating medical or nursing staffs’ use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Conclusion Healthcare professionals’ use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes. PMID:24998515

A Randomized Trial Examining Three Strategies for Supporting Health Insurance Decisions among the Uninsured.

PubMed

Politi, Mary C; Kaphingst, Kimberly A; Liu, Jingxia Esther; Perkins, Hannah; Furtado, Karishma; Kreuter, Matthew W; Shacham, Enbal; McBride, Timothy

2016-10-01

The Affordable Care Act allows uninsured individuals to select health insurance from numerous private plans, a challenging decision-making process. This study examined the effectiveness of strategies to support health insurance decisions among the uninsured. Participants (N = 343) from urban, suburban, and rural areas were randomized to 1 of 3 conditions: 1) a plain language table; 2) a visual condition where participants chose what information to view and in what order; and 3) a narrative condition. We administered measures assessing knowledge (true/false responses about key features of health insurance), confidence in choices (uncertainty subscale of the Decisional Conflict Scale), satisfaction (items from the Health Information National Trends Survey), preferences for insurance features (measured on a Likert scale from not at all important to very important), and plan choice. Although we did not find significant differences in knowledge, confidence in choice, or satisfaction across condition, participants across conditions made value-consistent choices, selecting plans that aligned with their preferences for key insurance features. In addition, those with adequate health literacy skills as measured by the Rapid Estimate of Adult Literacy in Medicine-Short Form (REALM-SF) had higher knowledge overall ([Formula: see text] = 6.1 v. 4.8, P < 0.001) and preferred the plain language table to the visual (P = 0.04) and visual to narrative (P = 0.0002) conditions, while those with inadequate health literacy skills showed no preference for study condition. A similar pattern was seen for those with higher subjective numeracy skills and higher versus lower education with regard to health insurance knowledge. Individuals with higher income felt less confident in their choices ([Formula: see text] = 28.7 v. 10.0, where higher numbers indicate less confidence/more uncertainty; P = 0.004). Those developing materials about the health insurance marketplace to support health insurance decisions might consider starting with plain language tables, presenting health insurance terminology in context, and organizing information according to ways the uninsured might use and value insurance features. Individuals with limited health literacy and numeracy skills and those with lower education face unique challenges selecting health insurance and weighing tradeoffs between cost and coverage. © The Author(s) 2015.

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.

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.

An integrated decision support system for wastewater nutrient recovery and recycling to agriculture

NASA Astrophysics Data System (ADS)

Roy, E. D.; Bomeisl, L.; Cornbrooks, P.; Mo, W.

2017-12-01

Nutrient recovery and recycling has become a key research topic within the wastewater engineering and nutrient management communities. Several technologies now exist that can effectively capture nutrients from wastewater, and innovation in this area continues to be an important research pursuit. However, practical nutrient recycling solutions require more than capable nutrient capture technologies. We also need to understand the role that wastewater nutrient recovery and recycling can play within broader nutrient management schemes at the landscape level, including important interactions at the nexus of food, energy, and water. We are developing an integrated decision support system that combines wastewater treatment data, agricultural data, spatial nutrient balance modeling, life cycle assessment, stakeholder knowledge, and multi-criteria decision making. Our goals are to: (1) help guide design decisions related to the implementation of sustainable nutrient recovery technology, (2) support innovations in watershed nutrient management that operate at the interface of the built environment and agriculture, and (3) aid efforts to protect aquatic ecosystems while supporting human welfare in a circular nutrient economy. These goals will be realized partly through the assessment of plausible alternative scenarios for the future. In this presentation, we will describe the tool and focus on nutrient balance results for the New England region. These results illustrate that both centralized and decentralized wastewater nutrient recovery schemes have potential to transform nutrient flows in many New England watersheds, diverting wastewater N and P away from aquatic ecosystems and toward local or regional agricultural soils where they can offset a substantial percentage of imported fertilizer. We will also highlight feasibility criteria and next steps to integrate stakeholder knowledge, economics, and life cycle assessment into the tool.

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.

Supplemental knowledge acquisition through external product interface for CLIPS

NASA Technical Reports Server (NTRS)

Saito, Tim; Ebaud, Stephen; Loftin, Bowen R.

1990-01-01

Traditionally, the acquisition of knowledge for expert systems consisted of the interview process with the domain or subject matter expert (SME), observation of domain environment, and information gathering and research which constituted a direct form of knowledge acquisition (KA). The knowledge engineer would be responsible for accumulating pertinent information and/or knowledge from the SME(s) for input into the appropriate expert system development tool. The direct KA process may (or may not) have included forms of data or documentation to incorporate from the SME's surroundings. The differentiation between direct KA and supplemental KA (indirect) would be the difference in the use of data. In acquiring supplemental knowledge, the knowledge engineer would access other types of evidence (manuals, documents, data files, spreadsheets, etc.) that would support the reasoning or premises of the SME. When an expert makes a decision in a particular task, one tool that may have been used to justify a recommendation, would have been a spreadsheet total or column figure. Locating specific decision points from that data within the SME's framework would constitute supplemental KA. Data used for a specific purpose in one system or environment would be used as supplemental knowledge for another, specifically a CLIPS project.

The Impact of Multifaceted Osteoporosis Group Education on Patients' Decision-Making regarding Treatment Options and Lifestyle Changes.

PubMed

Jensen, Annesofie L; Wind, Gitte; Langdahl, Bente Lomholt; Lomborg, Kirsten

2018-01-01

Patients with chronic diseases like osteoporosis constantly have to make decisions related to their disease. Multifaceted osteoporosis group education (GE) may support patients' decision-making. This study investigated multifaceted osteoporosis GE focusing on the impact of GE on patients' decision-making related to treatment options and lifestyle. An interpretive description design using ethnographic methods was utilized with 14 women and three men diagnosed with osteoporosis who attended multifaceted GE. Data consisted of participant observation during GE and individual interviews. Attending GE had an impact on the patients' decision-making in all educational themes. Patients decided on new ways to manage osteoporosis and made decisions regarding bone health and how to implement a lifestyle ensuring bone health. During GE, teachers and patients shared evidence-based knowledge and personal experiences and preferences, respectively, leading to a two-way exchange of information and deliberation about recommendations. Though teachers and patients explored the implications of the decisions and shared their preferences, teachers stressed that the patients ultimately had to make the decision. Teachers therefore refrained from participating in the final step of the decision-making process. Attending GE has an impact on the patients' decision-making as it can initiate patient reflection and support decision-making.

The emergency patient's participation in medical decision-making.

PubMed

Wang, Li-Hsiang; Goopy, Suzanne; Lin, Chun-Chih; Barnard, Alan; Han, Chin-Yen; Liu, Hsueh-Erh

2016-09-01

The purpose of this research was to explore the medical decision-making processes of patients in emergency departments. Studies indicate that patients should be given enough time to acquire relevant information and receive adequate support when they need to make medical decisions. It is difficult to satisfy these requirements in emergency situations. Limited research has addressed the topic of decision-making among emergency patients. This qualitative study used a broadly defined grounded theory approach to explore decision-making in an emergency department in Taiwan. Thirty emergency patients were recruited between June and December 2011 for semi-structured interviews that were audio-taped and transcribed verbatim. The study identified three stages in medical decision-making by emergency patients: predecision (interpreting the problem); decision (a balancing act) and postdecision (reclaiming the self). Transference was identified as the core category and pattern of behaviour through which patients resolved their main concerns. This transference around decision-making represents a type of bricolage. The findings fill a gap in knowledge about the decision-making process among emergency patients. The results inform emergency professionals seeking to support patients faced with complex medical decision-making and suggest an emphasis on informed patient decision-making, advocacy, patient-centred care and in-service education of health staff. © 2016 John Wiley & Sons Ltd.

Socio-Hydrology Modelling for an Uncertain Future, with Examples from the USA and Canada (Invited)

NASA Astrophysics Data System (ADS)

White, D. D.; Gober, P.; Sampson, D. A.; Quay, R.; Kirkwood, C.

2013-12-01

Socio-hydrology brings an interest in human values, markets, social organizations and public policy to the traditional emphasis of water science on climate, hydrology, toxicology,and ecology. It also conveys a decision focus in the form of decision support tools, engagement, and new knowledge about the science-policy interface. This paper demonstrates how policy decisions and human behavior can be better integrated into climate and hydrological models to improve their usefulness for support in decision making. Examples from the Southwest USA and Western Canada highlight uncertainties, vulnerabilities, and critical tradeoffs facing water decision makers in the face of rapidly changing environmental and societal conditions. Irreducible uncertainties in downscaled climate and hydrological models limit the usefulness of climate-driven, predict-and-plan methods of water resource planning and management. Thus, it is argued that such methods should be replaced by approaches that use exploratory modelling, scenario planning, and risk assessment in which the emphasis is on managing uncertainty rather than on reducing it.

"Many miles to go …": a systematic review of the implementation of patient decision support interventions into routine clinical practice.

PubMed

Elwyn, Glyn; Scholl, Isabelle; Tietbohl, Caroline; Mann, Mala; Edwards, Adrian G K; Clay, Catharine; Légaré, France; van der Weijden, Trudy; Lewis, Carmen L; Wexler, Richard M; Frosch, Dominick L

2013-01-01

Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings. An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment. After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption. It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a 'referral model' consistently report difficulties. We sense that the underlying issues that militate against the use of patient decision support and, more generally, limit the adoption of shared decision making, are under-investigated and under-specified. Future reports from implementation studies could be improved by following guidelines, for example the SQUIRE proposals, and by adopting methods that would be able to go beyond the 'barriers' and 'facilitators' approach to understand more about the nature of professional and organizational resistance to these tools. The lack of incentives that reward the use of these interventions needs to be considered as a significant impediment.

“Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice

PubMed Central

2013-01-01

Background Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings. Methods An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment. Results After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption. Conclusions It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a ‘referral model’ consistently report difficulties. We sense that the underlying issues that militate against the use of patient decision support and, more generally, limit the adoption of shared decision making, are under-investigated and under-specified. Future reports from implementation studies could be improved by following guidelines, for example the SQUIRE proposals, and by adopting methods that would be able to go beyond the ‘barriers’ and ‘facilitators’ approach to understand more about the nature of professional and organizational resistance to these tools. The lack of incentives that reward the use of these interventions needs to be considered as a significant impediment. PMID:24625083

A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

NASA Astrophysics Data System (ADS)

Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

2012-12-01

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.

Evaluation of Pharmacy and Therapeutic (P&T) Committee member knowledge, attitudes and ability regarding the use of comparative effectiveness research (CER) in health care decision-making.

PubMed

Tang, D H; Warholak, T L; Hines, L E; Hurwitz, J; Brown, M; Taylor, A M; Brixner, D; Malone, D C

2014-01-01

Comparative effectiveness research (CER) is a constellation of research methods designed to improve health care decision making. Educational programs that improve health care decision makers' CER knowledge and awareness may ultimately lead to more cost-effective use of health care resources. This study was conducted to evaluate changes in CER knowledge, attitudes, and ability among Pharmacy and Therapeutics (P&T) Committee members and support staff after attending a tailored educational program. Physicians and pharmacists from two professional societies and the Indian Health Service who participated in the P&T process were invited via email to participate in this study. Participants completed a questionnaire, designed specifically for this study, prior to and following the 4-hour live, educational program on CER to determine the impact on their related knowledge, attitudes, and ability to use CER in decision-making. Rasch analysis was used to assess validity and reliability of subsections of the questionnaire and regression analysis was used to assess programmatic impact on CER knowledge, attitude, and ability. One hundred and forty of the 199 participants completed both the pre- and post-CER session questionnaires (response rate = 70.4%). Most participants (>75%) correctly answered eight of the ten knowledge items after attending the educational session. More than 60% of the respondents had a positive attitude toward CER both before and after the program. Compared to baseline (pretest), participants reported significant improvements in their perceived ability to use CER after attending the session in these areas: using CER reviews, knowledge of CER methods, identifying problems with randomized controlled trials, identifying threats to validity, understanding of evidence synthesis approaches, and evaluating the quality of CER (all P values < 0.001). The questionnaire demonstrated acceptable reliability and validity evidence (limited evidence of construct under-representation and construct irrelevant variance). The CER educational program was effective in increasing participants' CER knowledge and self-perceived ability to evaluate relevant evidence. Improving knowledge and awareness of CER and its applicability is a critical first step in improving its use in health care decision making. Copyright © 2014 Elsevier Inc. All rights reserved.

Authors' response: the primacy of conscious decision making.

PubMed

Shanks, David R; Newell, Ben R

2014-02-01

The target article sought to question the common belief that our decisions are often biased by unconscious influences. While many commentators offer additional support for this perspective, others question our theoretical assumptions, empirical evaluations, and methodological criteria. We rebut in particular the starting assumption that all decision making is unconscious, and that the onus should be on researchers to prove conscious influences. Further evidence is evaluated in relation to the core topics we reviewed (multiple-cue judgment, deliberation without attention, and decisions under uncertainty), as well as priming effects. We reiterate a key conclusion from the target article, namely, that it now seems to be generally accepted that awareness should be operationally defined as reportable knowledge, and that such knowledge can only be evaluated by careful and thorough probing. We call for future research to pay heed to the different ways in which awareness can intervene in decision making (as identified in our lens model analysis) and to employ suitable methodology in the assessment of awareness, including the requirements that awareness assessment must be reliable, relevant, immediate, and sensitive.

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.

Two Dilemmas in Communicating Mathematics in Adult Basic Courses: "How To Support Pre-Knowledge of Adult Learners" and "How To Support Democratic Classroom Decisions."

ERIC Educational Resources Information Center

Lindenskov, Lena; Hansen, Eigil Peter

This study explores how adults' perspectives, intentions, blockages, resistance, and fascinations are reconstructed during a mathematics course in adult basic education. These aspects are discussed as important building blocks for developing theory in adult educational research. Adult mathematics education was compared in different institutional…

Thoughtflow: Standards and Tools for Provenance Capture and Workflow Definition to Support Model-Informed Drug Discovery and Development.

PubMed

Wilkins, J J; Chan, Pls; Chard, J; Smith, G; Smith, M K; Beer, M; Dunn, A; Flandorfer, C; Franklin, C; Gomeni, R; Harnisch, L; Kaye, R; Moodie, S; Sardu, M L; Wang, E; Watson, E; Wolstencroft, K; Cheung, Sya

2017-05-01

Pharmacometric analyses are complex and multifactorial. It is essential to check, track, and document the vast amounts of data and metadata that are generated during these analyses (and the relationships between them) in order to comply with regulations, support quality control, auditing, and reporting. It is, however, challenging, tedious, error-prone, and time-consuming, and diverts pharmacometricians from the more useful business of doing science. Automating this process would save time, reduce transcriptional errors, support the retention and transfer of knowledge, encourage good practice, and help ensure that pharmacometric analyses appropriately impact decisions. The ability to document, communicate, and reconstruct a complete pharmacometric analysis using an open standard would have considerable benefits. In this article, the Innovative Medicines Initiative (IMI) Drug Disease Model Resources (DDMoRe) consortium proposes a set of standards to facilitate the capture, storage, and reporting of knowledge (including assumptions and decisions) in the context of model-informed drug discovery and development (MID3), as well as to support reproducibility: "Thoughtflow." A prototype software implementation is provided. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

How does the knowledge environment shape procurement practices for orthopaedic medical devices in Mexico?

PubMed

Lingg, Myriam; Wyss, Kaspar; Durán-Arenas, Luis

2016-07-08

In organisational theory there is an assumption that knowledge is used effectively in healthcare systems that perform well. Actors in healthcare systems focus on managing knowledge of clinical processes like, for example, clinical decision-making to improve patient care. We know little about connecting that knowledge to administrative processes like high-risk medical device procurement. We analysed knowledge-related factors that influence procurement and clinical procedures for orthopaedic medical devices in Mexico. We based our qualitative study on 48 semi-structured interviews with various stakeholders in Mexico: orthopaedic specialists, government officials, and social security system managers or administrators. We took a knowledge-management related perspective (i) to analyse factors of managing knowledge of clinical procedures, (ii) to assess the role of this knowledge and in relation to procurement of orthopaedic medical devices, and (iii) to determine how to improve the situation. The results of this study are primarily relevant for Mexico but may also give impulsion to other health systems with highly standardized procurement practices. We found that knowledge of clinical procedures in orthopaedics is generated inconsistently and not always efficiently managed. Its support for procuring orthopaedic medical devices is insufficient. Identified deficiencies: leaders who lack guidance and direction and thus use knowledge poorly; failure to share knowledge; insufficiently defined formal structures and processes for collecting information and making it available to actors of health system; lack of strategies to benefit from synergies created by information and knowledge exchange. Many factors are related directly or indirectly to technological aspects, which are insufficiently developed. The content of this manuscript is novel as it analyses knowledge-related factors that influence procurement of orthopaedic medical devices in Mexico. Based on our results we recommend that the procurement mechanism should integrate knowledge from clinical procedures adequately in their decision-making. Without strong guidance, organisational changes, and support by technological solutions to improve the generation and management of knowledge, procurement processes for orthopaedic high-risk medical devices will remain sub-optimal.

Knowledge discovery of drug data on the example of adverse reaction prediction

PubMed Central

2014-01-01

Background Antibiotics are the widely prescribed drugs for children and most likely to be related with adverse reactions. Record on adverse reactions and allergies from antibiotics considerably affect the prescription choices. We consider this a biomedical decision-making problem and explore hidden knowledge in survey results on data extracted from a big data pool of health records of children, from the Health Center of Osijek, Eastern Croatia. Results We applied and evaluated a k-means algorithm to the dataset to generate some clusters which have similar features. Our results highlight that some type of antibiotics form different clusters, which insight is most helpful for the clinician to support better decision-making. Conclusions Medical professionals can investigate the clusters which our study revealed, thus gaining useful knowledge and insight into this data for their clinical studies. PMID:25079450

What supports do health system organizations have in place to facilitate evidence-informed decision-making? a qualitative study

PubMed Central

2013-01-01

Background Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. Objectives The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. Methods In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a ‘knowledge broker’) in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Results A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff’s capacity building. Conclusions This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of research evidence by decision-makers, which may then lead to more informed decisions, and hopefully to a strengthened health system and improved health. PMID:23915278

What supports do health system organizations have in place to facilitate evidence-informed decision-making? A qualitative study.

PubMed

Ellen, Moriah E; Léon, Gregory; Bouchard, Gisèle; Lavis, John N; Ouimet, Mathieu; Grimshaw, Jeremy M

2013-08-06

Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a 'knowledge broker') in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff's capacity building. This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of research evidence by decision-makers, which may then lead to more informed decisions, and hopefully to a strengthened health system and improved health.

HL7 Structured Product Labeling - electronic prescribing information for provider order entry decision support.

PubMed

Schadow, Gunther

2005-01-01

Prescribing errors are an important cause of adverse events, and lack of knowledge of the drug is a root cause for prescribing errors. The FDA is issuing new regulations that will make the drug labels much more useful not only to physicians, but also to computerized order entry systems that support physicians to practice safe prescribing. For this purpose, FDA works with HL7 to create the Structured Product Label (SPL) standard that includes a document format as well as a drug knowledge representation, this poster introduces the basic concepts of SPL.

Troubleshooting Portfolios

ERIC Educational Resources Information Center

Crismond, David; Peterie, Matthew

2017-01-01

The Troubleshooting Portfolios approach was developed at the Olathe Northwest High School in Olathe, Kansas. This approach supports integrated STEM and "informed design" thinking and learning, in which students: (1) use design strategies effectively; (2) work creatively and collaboratively in teams; (3) make knowledge-driven decisions;…

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.

A knowledge creation info-structure to acquire and crystallize the tacit knowledge of health-care experts.

PubMed

Abidi, Syed Sibte Raza; Cheah, Yu-N; Curran, Janet

2005-06-01

Tacit knowledge of health-care experts is an important source of experiential know-how, yet due to various operational and technical reasons, such health-care knowledge is not entirely harnessed and put into professional practice. Emerging knowledge-management (KM) solutions suggest strategies to acquire the seemingly intractable and nonarticulated tacit knowledge of health-care experts. This paper presents a KM methodology, together with its computational implementation, to 1) acquire the tacit knowledge possessed by health-care experts; 2) represent the acquired tacit health-care knowledge in a computational formalism--i.e., clinical scenarios--that allows the reuse of stored knowledge to acquire tacit knowledge; and 3) crystallize the acquired tacit knowledge so that it is validated for health-care decision-support and medical education systems.

Talking Points: Women's Information Needs for Informed Decision-Making About Noninvasive Prenatal Testing for Down Syndrome.

PubMed

Dane, Aimée C; Peterson, Madelyn; Miller, Yvette D

2018-03-17

Adequate knowledge is a vital component of informed decision-making; however, we do not know what information women value when making decisions about noninvasive prenatal testing (NIPT). The current study aimed to identify women's information needs for decision-making about NIPT as a first-tier, non-contingent test with out-of-pocket expense and, in turn, inform best practice by specifying the information that should be prioritized when providing pre-test counseling to women in a time-limited scenario or space-limited decision support tool. We asked women (N = 242) in Australia to indicate the importance of knowing 24 information items when making a decision about NIPT and to choose two information items they would most value. Our findings suggest that women value having complete information when making decisions about NIPT. Information about the accuracy of NIPT and the pros and cons of NIPT compared to other screening and invasive tests were perceived to be most important. The findings of this study can be used to maximize the usefulness of time-limited discussions or space-limited decision support tools, but should not be routinely relied upon as a replacement for provision of full and tailored information when feasible.

An exploration of clinical decision making in mental health triage.

PubMed

Sands, Natisha

2009-08-01

Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.

Factors affecting evidence-based decision making in local health departments.

PubMed

Sosnowy, Collette D; Weiss, Linda J; Maylahn, Christopher M; Pirani, Sylvia J; Katagiri, Nancy J

2013-12-01

Data indicating the extent to which evidence-based decision making (EBDM) is used in local health departments (LHDs) are limited. This study aims to determine use of decision-making processes by New York State LHD leaders and upper-level staff and identify facilitators and barriers to the use of EBDM in LHDs. The New York Public Health Practice-Based Research Network implemented a mixed-methods study in 31 LHDs. There were 20 individual interviews; five small-group interviews (two or three participants each); and two focus groups (eight participants each) conducted with people who had decision-making authority. Information was obtained about each person's background and position, decision-making responsibilities, how decisions are made within their LHD, knowledge and experience with EBDM, use of each step of the EBDM process, and barriers and facilitators to EBDM implementation. Data were collected from June to November 2010 and analyzed in 2011. Overall, participants supported EBDM and expressed a desire to increase their department's use of it. Although most people understood the concept, a relatively small number had substantial expertise and experience with its practice. Many indicated that they applied EBDM unevenly. Factors associated with use of EBDM included strong leadership; workforce capacity (number and skills); resources; funding and program mandates; political support; and access to data and program models suitable to community conditions. EBDM is used inconsistently in LHDs in New York. Despite knowledge and interest among LHD leadership, the LHD capacity, resources, appropriate programming, and other issues serve as impediments to EBDM and optimal implementation of evidence-based strategies. Published by Elsevier Inc.

Characteristics of knowledge content in a curated online evidence library.

PubMed

Varada, Sowmya; Lacson, Ronilda; Raja, Ali S; Ip, Ivan K; Schneider, Louise; Osterbur, David; Bain, Paul; Vetrano, Nicole; Cellini, Jacqueline; Mita, Carol; Coletti, Margaret; Whelan, Julia; Khorasani, Ramin

2018-05-01

To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation. The evidence library is populated with clinical decision rules, professional society guidelines, and locally developed best practice guidelines. Individual recommendations were graded based on a standard methodology and compared using chi-square test. Strength of evidence ranged from grade 1 (systematic review) through grade 5 (recommendations based on expert opinion). Finally, variations in the underlying representation of these recommendations were identified. The library contains 546 individual imaging-related recommendations. Only 15% (16/106) of recommendations from clinical decision rules were grade 5 vs 83% (526/636) from professional society practice guidelines and local best practice guidelines that cited grade 5 studies (P < .0001). Minor head trauma, pulmonary embolism, and appendicitis were topic areas supported by the highest quality of evidence. Three main variations in underlying representations of recommendations were "single-decision," "branching," and "score-based." Most recommendations were grade 5, largely because studies to test and validate many recommendations were absent. Recommendation types vary in amount and complexity and, accordingly, the structure and syntax of statements they generate. However, they can be represented in single-decision, branching, and score-based representations. In a curated evidence library with graded imaging-based recommendations, evidence quality varied widely, with decision rules providing the highest-quality recommendations. The library may be helpful in highlighting evidence gaps, comparing recommendations from varied sources on similar clinical topics, and prioritizing imaging recommendations to inform clinical decision support implementation.

Health informatics 3.0.

PubMed

Kalra, Dipak

2011-01-01

Web 3.0 promises us smart computer services that will interact with each other and leverage knowledge about us and our immediate context to deliver prioritised and relevant information to support decisions and actions. Healthcare must take advantage of such new knowledge-integrating services, in particular to support better co-operation between professionals of different disciplines working in different locations, and to enable well-informed co-operation between clinicians and patients. To grasp the potential of Web 3.0 we will need well-harmonised semantic resources that can richly connect virtual teams and link their strategies to real-time and tailored evidence. Facts, decision logic, care pathway steps, alerts, education need to be embedded within components that can interact with multiple EHR systems and services consistently. Using Health Informatics 3.0 a patient's current situation could be compared with the outcomes of very similar patients (from across millions) to deliver personalised care recommendations. The integration of EHRs with biomedical sciences ('omics) research results and predictive models such as the Virtual Physiological Human could help speed up the translation of new knowledge into clinical practice. The mission, and challenge, for Health Informatics 3.0 is to enable healthy citizens, patients and professionals to collaborate within a knowledge-empowered social network in which patient specific information and personalised real-time evidence are seamlessly interwoven.

The Use of Research-Based Instructional Strategies in Introductory Physics: Where do Faculty Leave the Innovation-Decision Process?

NASA Astrophysics Data System (ADS)

Henderson, Charles; Dancy, Melissa; Niewiadomska-Bugaj, Magdalena

2013-03-01

During the Fall of 2008 a web survey was completed by a representative sample of 722 United States physics faculty. In this talk we will briefly present summary statistics to describe faculty knowledge about and use of 24 specific research-based instructional strategies (RBIS). We will then analyze the results based on a four stage model of the innovation-decision process: knowledge, trial, continuation, and high use. The largest losses occur at the continuation stage, with approximately 1/3 of faculty discontinuing use of all RBIS after trying one or more of these strategies. These results suggest that common dissemination strategies are good at creating knowledge about RBIS and motivation to try a RBIS, but more work is needed to support faculty during implementation and continued use of RBIS. Based on a logistic regression analysis, only nine of the 20 potential predictor variables measured were statistically significant when controlling for other variables. Faculty age, institutional type, and percentage of job related to teaching were not found to be correlated with knowledge or use at any stage. High research productivity and large class sizes were not found to be barriers to use of at least some RBIS. Supported by NSF #0715698.

Research-based-decision-making in Canadian health organizations: a behavioural approach.

PubMed

Jbilou, Jalila; Amara, Nabil; Landry, Réjean

2007-06-01

Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build networks, develop partnerships between professionals locally, regionally and nationally, and also act as change agents in the dissemination and adoption of knowledge and innovations in health services. However, the research focused on knowledge use as a support to decision-making, further research is needed to identify and evaluate effective incentives and strategies to implement so as to enhance RBDM adoption among health decision makers and more theoretical development are to complete in this perspective.

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.

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.

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol.

PubMed

Freebairn, L; Atkinson, J; Kelly, P; McDonnell, G; Rychetnik, L

2016-09-21

Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making. The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants' engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change. The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings.

An Introspective Critique of Past, Present, and Future USGS Decision Support

NASA Astrophysics Data System (ADS)

Neff, B. P.; Pavlick, M.

2017-12-01

In response to increasing scrutiny of publicly funded science, the Water Mission Area of USGS is shifting its approach for informing decisions that affect the country. Historically, USGS has focused on providing sound science on cutting edge, societally relevant issues with the expectation that decision makers will take action on this information. In practice, scientists often do not understand or focus on the needs of decision makers and decision makers often cannot or do not utilize information produced by scientists. The Water Mission Area of USGS has recognized that it can better serve the taxpayer by delivering information more relevant to decision making in a form more conducive to its use. To this end, the Water Mission Area of USGS is seeking greater integration with the decision making process to better inform what information it produces. In addition, recognizing that the transfer of scientific knowledge to decision making is fundamentally a social process, USGS is embracing the use of social science to better inform how it delivers scientific information and facilitates its use. This study utilizes qualitative methods to document the evolution of decision support at USGS and provide a rationale for a shift in direction. Challenges to implementation are identified and collaborative opportunities to improve decision making are discussed.

Behavioral medicine perspectives on the design of health information technology to improve decision-making, guideline adherence, and care coordination in chronic pain management.

PubMed

Midboe, Amanda M; Lewis, Eleanor T; Cronkite, Ruth C; Chambers, Dallas; Goldstein, Mary K; Kerns, Robert D; Trafton, Jodie A

2011-03-01

Development of clinical decision support systems (CDSs) has tended to focus on facilitating medication management. An understanding of behavioral medicine perspectives on the usefulness of a CDS for patient care can expand CDSs to improve management of chronic disease. The purpose of this study is to explore feedback from behavioral medicine providers regarding the potential for CDSs to improve decision-making, care coordination, and guideline adherence in pain management. Qualitative methods were used to analyze semi-structured interview responses from behavioral medicine stakeholders following demonstration of an existing CDS for opioid prescribing, ATHENA-OT. Participants suggested that a CDS could assist with decision-making by educating providers, providing recommendations about behavioral therapy, facilitating risk assessment, and improving referral decisions. They suggested that a CDS could improve care coordination by facilitating division of workload, improving patient education, and increasing consideration and knowledge of options in other disciplines. Clinical decision support systems are promising tools for improving behavioral medicine care for chronic pain.

Intended parents' motivations and information and support needs when seeking extraterritorial compensated surrogacy.

PubMed

Hammarberg, Karin; Stafford-Bell, Martyn; Everingham, Sam

2015-11-01

Cross-border reproductive care (CBRC) is becoming increasingly common. Little is known about the motivations and information and support needs of people who cross borders to access surrogacy. This study aimed to explore: how those considering or undertaking extraterritorial surrogacy reach their decision; what other avenues they have considered and tried to have children; their sources of information and support; and perceptions of how others view their decision. Members of two Australian parenting support forums completed an anonymous online survey. Of the 249 respondents, 51% were gay men, 43% heterosexual women and 7% heterosexual men. Most heterosexual respondents had tried to conceive spontaneously and with assisted reproductive technology before considering surrogacy. Most respondents felt supported in their decision to try extraterritorial surrogacy by close family and friends. Surrogacy-related information was mostly sourced online and from other parents through surrogacy. Few sought information from a local general practitioner or IVF clinic and those who did reported IVF clinic staff were significantly (P < 0.001) more likely than other groups to communicate negative reactions to their decision to seek surrogacy. The apparent negative attitudes to cross-border surrogacy among health professionals warrants further research into health professionals' knowledge, beliefs and attitudes relating to surrogacy. Copyright © 2015 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

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.

Exploration of the functions of health impact assessment in real-world policymaking in the field of social health inequality: towards a conception of conceptual learning.

PubMed

Feyaerts, Gille; Deguerry, Murielle; Deboosere, Patrick; De Spiegelaere, Myriam

2017-06-01

With the implementation of health impact assessment (HIA)'s conceptual model into real-world policymaking, a number of fundamental issues arise concerning its decision-support function. Rooted in a rational vision of the decision-making process, focus regarding both conceptualisation and evaluation has been mainly on the function of instrumental policy-learning. However, in the field of social health inequalities, this function is strongly limited by the intrinsic 'wickedness' of the policy issue. Focusing almost exclusively on this instrumental function, the real influence HIA can have on policymaking in the longer term is underestimated and remains largely unexploited. Drawing insights from theoretical models developed in the field of political science and sociology, we explore the different decision-support functions HIA can fulfill and identify conceptual learning as potentially the most important. Accordingly, dominant focus on the technical engineering function, where knowledge is provided in order to 'rationalise' the policy process and to tackle 'tame' problems, should be complemented with an analysis of the conditions for conceptual learning, where knowledge introduces new information and perspectives and, as such, contributes in the longer term to a paradigm change.

Applying Self-Determination Theory to Adolescent Sexual-Risk Behavior and Knowledge: A Structural Equation Model [Formula: see text].

PubMed

Riley, Bettina H; McDermott, Ryon C

2018-05-01

National health priorities identify adolescent sexual-risk behavior outcomes as research and intervention targets for mental health. Reduce sexual-risk behavioral outcomes by applying self-determination theory to focus on decision-making autonomy. This study examined late adolescents' recollections of parental autonomy support/sexual-risk communication experiences and autonomy motivation as predictors of sexual-risk behaviors/knowledge. A convenience sample ( N = 249) of 19- and 20-year-old university students completed self-report questionnaires. Structural equation modeling with latent variables examined direct/indirect effects in the hypothesized model. Parents contributed uniquely through sexual-risk communication and/or autonomy support to late adolescents' autonomous motivation. The final model evidenced acceptable fit and explained 12% of the variation in adolescent sexual-risk behavior, 7% in adolescent autonomous motivation, and 2% in adolescent sexual-risk knowledge. Psychiatric mental health nurses should conduct further research and design interventions promoting parent autonomy support and adolescent autonomous motivation to reduce sexual risk-behavior and increase sexual-risk knowledge.

Erroneous knowledge of results affects decision and memory processes on timing tasks.

PubMed

Ryan, Lawrence J; Fritz, Matthew S

2007-12-01

On mental timing tasks, erroneous knowledge of results (KR) leads to incorrect performance accompanied by the subjective judgment of accurate performance. Using the start-stop technique (an analogue of the peak interval procedure) with both reproduction and production timing tasks, the authors analyze what processes erroneous KR alters. KR provides guidance (performance error information) that lowers decision thresholds. Erroneous KR also provides targeting information that alters response durations proportionately to the magnitude of the feedback error. On the production task, this shift results from changes in the reference memory, whereas on the reproduction task this shift results from changes in the decision threshold for responding. The idea that erroneous KR can alter different cognitive processes on related tasks is supported by the authors' demonstration that the learned strategies can transfer from the reproduction task to the production task but not visa versa. Thus effects of KR are both task and context dependent.

[Research applications in digital radiology. Big data and co].

PubMed

Müller, H; Hanbury, A

2016-02-01

Medical imaging produces increasingly complex images (e.g. thinner slices and higher resolution) with more protocols, so that image reading has also become much more complex. More information needs to be processed and usually the number of radiologists available for these tasks has not increased to the same extent. The objective of this article is to present current research results from projects on the use of image data for clinical decision support. An infrastructure that can allow large volumes of data to be accessed is presented. In this way the best performing tools can be identified without the medical data having to leave secure servers. The text presents the results of the VISCERAL and Khresmoi EU-funded projects, which allow the analysis of previous cases from institutional archives to support decision-making and for process automation. The results also represent a secure evaluation environment for medical image analysis. This allows the use of data extracted from past cases to solve information needs occurring when diagnosing new cases. The presented research prototypes allow direct extraction of knowledge from the visual data of the images and to use this for decision support or process automation. Real clinical use has not been tested but several subjective user tests showed the effectiveness and efficiency of the process. The future in radiology will clearly depend on better use of the important knowledge in clinical image archives to automate processes and aid decision-making via big data analysis. This can help concentrate the work of radiologists towards the most important parts of diagnostics.

Adaptation by Stealth: Understanding climate information use across scales and decision spaces in water management in the United States

NASA Astrophysics Data System (ADS)

Kirchhoff, C.; Vang Rasmussen, L.; Lemos, M. C.

2016-12-01

While there has been considerable focus on understanding how factors related to the creation of climate knowledge affect its uptake and use, less attention has been paid to the actors, decisions, and processes through which climate information supports, or fails to support, action. This is particularly the case concerning how different scales of decision-making influence information uptake. In this study, we seek to understand how water and resource managers' decision space influences climate information use in two Great Lakes watersheds. We find that despite the availability of tailored climate information, actual use of information in decision making remains low. Reasons include: a) lack of willingness to place climate on agendas because local managers perceive climate change as politically risky and a difficult and intangible problem; b) lack of formal mandate or authority at the city and county scale to translate climate information into on-the-ground action, c) problems with the information itself, and d) perceived lack of demand for climate information by those managers who have the mandate and authority (e.g. at the state level) to use (or help others use) climate information. Our findings suggest that 1) climate scientists and information brokers should produce information that meets a range of decision needs and reserve intensive tailoring efforts for decision makers who have authority and willingness to employ climate information, 2) without support from higher levels of decision-making (e.g. state) it is unlikely that climate information use for adaptation decisions will accelerate significantly in the next few years, and 3) the trend towards adopting more sustainability and resilience practices over climate-specific actions should be supported as an important component of the climate adaptation repertoire.

Computer decision support system for the stomach cancer diagnosis

NASA Astrophysics Data System (ADS)

Polyakov, E. V.; Sukhova, O. G.; Korenevskaya, P. Y.; Ovcharova, V. S.; Kudryavtseva, I. O.; Vlasova, S. V.; Grebennikova, O. P.; Burov, D. A.; Yemelyanova, G. S.; Selchuk, V. Y.

2017-01-01

The paper considers the creation of the computer knowledge base containing the data of histological, cytologic, and clinical researches. The system is focused on improvement of diagnostics quality of stomach cancer - one of the most frequent death causes among oncologic patients.

Modeling the Innovation-Decision Process: Dissemination and Adoption of a Motivational Interviewing Preparatory Procedure in Addiction Outpatient Clinics

PubMed Central

Walitzer, Kimberly S.; Dermen, Kurt H.; Barrick, Christopher; Shyhalla, Kathleen

2015-01-01

Widespread adoption of empirically-supported treatment innovations has the potential to improve effectiveness of treatment received by individuals with substance use disorders. However, the process of disseminating such innovations has been complex, slow, and difficult. We empirically describe the dissemination and adoption of a treatment innovation – an alcohol-treatment preparatory therapeutic procedure based on motivational interviewing (MI) – in the context of Rogers’ (2003) five stages of innovation-decision process (knowledge, persuasion, decision, implementation and confirmation). To this end, 145 randomly-chosen outpatient addiction treatment clinics in New York State received an onsite visit from a project trainer delivering one of three randomly-assigned dissemination intensities: a 15-minute, a half-day or a full-day presentation. Across these clinics, 141 primary administrators and 837 clinicians completed questionnaires assessing aspects of five innovation-decision stages. At each clinic, questionnaire administration occurred immediately pre- and post-dissemination, as well as one and six months after dissemination. Consistent with Rogers’ theory, earlier stages of the innovation-decision process predicted later stages. As hypothesized, dissemination intensity predicted clinicians’ post-dissemination knowledge. Clinician baseline characteristics (including gender, pre-dissemination knowledge regarding the MI preparatory technique, education, case load, beliefs regarding the nature of alcohol problems, and beliefs and behavior with regard to therapeutic style) predicted knowledge and persuasion stage variables. One baseline clinic characteristic (i.e., clinic mean beliefs and behavior regarding an MI-consistent therapeutic style) predicted implementation stage variables. Findings suggest that dissemination strategies should accommodate clinician and clinic characteristics. PMID:25934460

What Can Funders Do to Better Link Science with Decisions? Case Studies of Coastal Communities and Climate Change

NASA Astrophysics Data System (ADS)

Matso, Kalle E.; Becker, Mimi L.

2014-12-01

Many reports and studies have noted that a significant portion of problem-oriented coastal science does not actually link to decisions. Here, three competitively funded project case studies are studied to determine what funders can and should do to better link science with decisions. The qualitative analysis used for this study indicates that the studied program was seen as being unusually attentive to the issue of linking science to decisions, as opposed to simply generating new knowledge. Nevertheless, much of the data indicate that funders can and should do more. Three ideas figured most prominently in the qualitative data: (1) funders should do more to ensure that the problem itself is defined more thoroughly with people who are envisioned as potential users of the science; (2) funders need to allocate more resources and attention to communicating effectively (with users) throughout the project; and (3) funders need to demand more engagement of users throughout the project. These findings have important implications for how funders review and support science, especially when competitive processes are used. Most importantly, funders should adjust what kind of science they ask for. Secondly, funders need to change who is involved in the review process. Currently, review processes focus on knowledge generation, which means that the reviewers themselves have expertise in that area. Instead, review panels should be balanced between those who focus on knowledge generation and those who focus on linking knowledge to decisions; this is a separate but critical discipline currently left out of the review process.

Clinical Decision Support: a 25 Year Retrospective and a 25 Year Vision.

PubMed

Middleton, B; Sittig, D F; Wright, A

2016-08-02

The objective of this review is to summarize the state of the art of clinical decision support (CDS) circa 1990, review progress in the 25 year interval from that time, and provide a vision of what CDS might look like 25 years hence, or circa 2040. Informal review of the medical literature with iterative review and discussion among the authors to arrive at six axes (data, knowledge, inference, architecture and technology, implementation and integration, and users) to frame the review and discussion of selected barriers and facilitators to the effective use of CDS. In each of the six axes, significant progress has been made. Key advances in structuring and encoding standardized data with an increased availability of data, development of knowledge bases for CDS, and improvement of capabilities to share knowledge artifacts, explosion of methods analyzing and inferring from clinical data, evolution of information technologies and architectures to facilitate the broad application of CDS, improvement of methods to implement CDS and integrate CDS into the clinical workflow, and increasing sophistication of the end-user, all have played a role in improving the effective use of CDS in healthcare delivery. CDS has evolved dramatically over the past 25 years and will likely evolve just as dramatically or more so over the next 25 years. Increasingly, the clinical encounter between a clinician and a patient will be supported by a wide variety of cognitive aides to support diagnosis, treatment, care-coordination, surveillance and prevention, and health maintenance or wellness.

Evaluation of Retention of Knowledge and Skills Imparted to First-Year Medical Students through Basic Life Support Training

ERIC Educational Resources Information Center

Pande, Sushma; Pande, Santosh; Parate, Vrushali; Pande, Sanket; Sukhsohale, Neelam

2014-01-01

Poor awareness among medical graduates about basic life support (BLS) is a matter of great concern. The presence of a trained rescuer is the key determinant of ultimate survival from life-threatening emergencies. To achieve this goal, early exposure to such life-saving skills is the right decision to foster these skills for medical students, which…

A Knowledge-based System for Intelligent Support in Pharmacogenomics Evidence Assessment: Ontology-driven Evidence Representation and Retrieval.

PubMed

Lee, Chia-Ju; Devine, Beth; Tarczy-Hornoch, Peter

2017-01-01

Pharmacogenomics holds promise as a critical component of precision medicine. Yet, the use of pharmacogenomics in routine clinical care is minimal, partly due to the lack of efficient and effective use of existing evidence. This paper describes the design, development, implementation and evaluation of a knowledge-based system that fulfills three critical features: a) providing clinically relevant evidence, b) applying an evidence-based approach, and c) using semantically computable formalism, to facilitate efficient evidence assessment to support timely decisions on adoption of pharmacogenomics in clinical care. To illustrate functionality, the system was piloted in the context of clopidogrel and warfarin pharmacogenomics. In contrast to existing pharmacogenomics knowledge bases, the developed system is the first to exploit the expressivity and reasoning power of logic-based representation formalism to enable unambiguous expression and automatic retrieval of pharmacogenomics evidence to support systematic review with meta-analysis.

The Cook Agronomy Farm LTAR: Knowledge Intensive Precision Agro-ecology

NASA Astrophysics Data System (ADS)

Huggins, D. R.

2015-12-01

Drowning in data and starving for knowledge, agricultural decision makers require evidence-based information to enlighten sustainable intensification. The agro-ecological footprint of the Cook Agronomy Farm (CAF) Long-Term Agro-ecosystem Research (LTAR) site is embedded within 9.4 million ha of diverse land uses primarily cropland (2.9 million ha) and rangeland (5.3 million ha) that span a wide annual precipitation gradient (150 mm through 1400 mm) with diverse social and natural capital (see Figure). Sustainable intensification hinges on the development and adoption of precision agro-ecological practices that rely on meaningful spatio-temporal data relevant to land use decisions at within-field to regional scales. Specifically, the CAF LTAR will provide the scientific foundation (socio-economical and bio-physical) for enhancing decision support for precision and conservation agriculture and synergistic cropping system intensification and diversification. Long- and short-term perspectives that recognize and assess trade-offs in ecosystem services inherent in any land use decision will be considered so as to promote the development of more sustainable agricultural systems. Presented will be current and future CAF LTAR research efforts required for the development of sustainable agricultural systems including cropping system cycles and flows of nutrients, water, carbon, greenhouse gases and other biotic and abiotic factors. Evaluation criteria and metrics associated with long-term agro-ecosystem provisioning, supporting, and regulating services will be emphasized.

Elicitation of neurological knowledge with argument-based machine learning.

PubMed

Groznik, Vida; Guid, Matej; Sadikov, Aleksander; Možina, Martin; Georgiev, Dejan; Kragelj, Veronika; Ribarič, Samo; Pirtošek, Zvezdan; Bratko, Ivan

2013-02-01

The paper describes the use of expert's knowledge in practice and the efficiency of a recently developed technique called argument-based machine learning (ABML) in the knowledge elicitation process. We are developing a neurological decision support system to help the neurologists differentiate between three types of tremors: Parkinsonian, essential, and mixed tremor (comorbidity). The system is intended to act as a second opinion for the neurologists, and most importantly to help them reduce the number of patients in the "gray area" that require a very costly further examination (DaTSCAN). We strive to elicit comprehensible and medically meaningful knowledge in such a way that it does not come at the cost of diagnostic accuracy. To alleviate the difficult problem of knowledge elicitation from data and domain experts, we used ABML. ABML guides the expert to explain critical special cases which cannot be handled automatically by machine learning. This very efficiently reduces the expert's workload, and combines expert's knowledge with learning data. 122 patients were enrolled into the study. The classification accuracy of the final model was 91%. Equally important, the initial and the final models were also evaluated for their comprehensibility by the neurologists. All 13 rules of the final model were deemed as appropriate to be able to support its decisions with good explanations. The paper demonstrates ABML's advantage in combining machine learning and expert knowledge. The accuracy of the system is very high with respect to the current state-of-the-art in clinical practice, and the system's knowledge base is assessed to be very consistent from a medical point of view. This opens up the possibility to use the system also as a teaching tool. Copyright © 2012 Elsevier B.V. All rights reserved.

Improving management of small natural features on private lands by negotiating the science-policy boundary for Maine vernal pools.

PubMed

Calhoun, Aram J K; Jansujwicz, Jessica S; Bell, Kathleen P; Hunter, Malcolm L

2014-07-29

Vernal pools are far more important for providing ecosystem services than one would predict based on their small size. However, prevailing resource-management strategies are not effectively conserving pools and other small natural features on private lands. Solutions are complicated by tensions between private property and societal rights, uncertainties over resource location and function, diverse stakeholders, and fragmented regulatory authority. The development and testing of new conservation approaches that link scientific knowledge, stakeholder decision-making, and conservation outcomes are important responses to this conservation dilemma. Drawing from a 15-y history of vernal pool conservation efforts in Maine, we describe the coevolution of pool conservation and research approaches, focusing on how research-based knowledge was produced and used in support of management decisions. As management shifted from reactive, top-down approaches to proactive and flexible approaches, research shifted from an ecology-focused program to an interdisciplinary program based on social-ecological systems. The most effective strategies for linking scientific knowledge with action changed as the decision-makers, knowledge needs, and context for vernal pool management advanced. Interactions among stakeholders increased the extent to which knowledge was coproduced and shifted the objective of stakeholder engagement from outreach to research collaboration and development of innovative conservation approaches. New conservation strategies were possible because of the flexible, solutions-oriented collaborations and trust between scientists and decision-makers (fostered over 15 y) and interdisciplinary, engaged research. Solutions to the dilemma of conserving small natural features on private lands, and analogous sustainability science challenges, will benefit from repeated negotiations of the science-policy boundary.

A multi-faceted tailored strategy to implement an electronic clinical decision support system for pressure ulcer prevention in nursing homes: a two-armed randomized controlled trial.

PubMed

Beeckman, Dimitri; Clays, Els; Van Hecke, Ann; Vanderwee, Katrien; Schoonhoven, Lisette; Verhaeghe, Sofie

2013-04-01

Frail older people admitted to nursing homes are at risk of a range of adverse outcomes, including pressure ulcers. Clinical decision support systems are believed to have the potential to improve care and to change the behaviour of healthcare professionals. To determine whether a multi-faceted tailored strategy to implement an electronic clinical decision support system for pressure ulcer prevention improves adherence to recommendations for pressure ulcer prevention in nursing homes. Two-armed randomized controlled trial in a nursing home setting in Belgium. The trial consisted of a 16-week implementation intervention between February and June 2010, including one baseline, four intermediate, and one post-testing measurement. Primary outcome was the adherence to guideline-based care recommendations (in terms of allocating adequate pressure ulcer prevention in residents at risk). Secondary outcomes were the change in resident outcomes (pressure ulcer prevalence) and intermediate outcomes (knowledge and attitudes of healthcare professionals). Random sample of 11 wards (6 experimental; 5 control) in a convenience sample of 4 nursing homes in Belgium. In total, 464 nursing home residents and 118 healthcare professionals participated. The experimental arm was involved in a multi-faceted tailored implementation intervention of a clinical decision support system, including interactive education, reminders, monitoring, feedback and leadership. The control arm received a hard-copy of the pressure ulcer prevention protocol, supported by standardized 30 min group lecture. Patients in the intervention arm were significantly more likely to receive fully adequate pressure ulcer prevention when seated in a chair (F=16.4, P=0.003). No significant improvement was observed on pressure ulcer prevalence and knowledge of the professionals. While baseline attitude scores were comparable between both groups [exp. 74.3% vs. contr. 74.5% (P=0.92)], the mean score after the intervention was 83.5% in the experimental group vs. 72.1% in the control group (F=15.12, P<0.001). The intervention was only partially successful to improve the primary outcome. Attitudes improved significantly while the knowledge of the healthcare workers remained unsatisfactorily low. Further research should focus on the underlying reasons for these findings. Copyright © 2012 Elsevier Ltd. All rights reserved.

Translating knowledge into practice and policy: the role of knowledge networks in primary health care.

PubMed

Armstrong, Kylie; Kendall, Elizabeth

The translation of information into practice is a well-recognised challenge for the health sector. In the primary healthcare sector, the last decade has seen an explosion of information generated by health systems, universities and a range of other sources. Without a system for translating that knowledge into practice and sharing it in a comprehensible form, it will remain meaningless to most practitioners. We propose the establishment of Knowledge Networks as a promising method for supporting the rapid adoption and generation of health information within the primary health care sector to advance health care services. These networks will be particularly important to the implementation of the national reform agenda, responsive decision-making and the translation of new frameworks or competencies into practice. This paper describes how interdisciplinary Knowledge Networks could be established focusing on a number of priority health research areas. Local Knowledge Networks would be used as a platform to support a collaborative web of evidence designed to influence health policy and planning. Our experience with Knowledge Networks indicates that they must be comprised of health professionals from Divisions of General Practice, researchers, policy-makers, consumers, government and non-government sectors. This paper will describe these networks and show how they might support the translation of knowledge into practice, thus driving systematic and institutional change.

Mobile clinical decision support systems and applications: a literature and commercial review.

PubMed

Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel

2014-01-01

The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.

A qualitative study of nulliparous women's decision making on mode of delivery under China's two-child policy.

PubMed

Gu, Chunyi; Zhu, Xinli; Ding, Yan; Setterberg Simone; Wang, Xiaojiao; Tao, Hua; Zhang, Yu

2018-07-01

To explore nulliparous women's perceptions of decision making regarding mode of delivery under China's two-child policy. Qualitative descriptive design with in-depth semi-structured interviews. Postnatal wards at a tertiary specialized women's hospital in Shanghai, China. 21 nulliparous women 2-3 days postpartum were purposively sampled until data saturation. In-depth semi-structured interviews were conducted between October 8th, 2015 and January 31st, 2016. Two overarching descriptive categories were identified: (1) women's decision-making process: stability versus variability, and (2) factors affecting decision making: variety versus interactivity. Four key themes emerged from each category: (1) initial decision making with certainty: anticipated trial of labour, failed trial of labour, 'shy away' and compromise, anticipated caesarean delivery; (2) initial decision making with uncertainty: anticipated trial of labour, failed trial of labour, 'shy away' and compromise; (3) internal factors affecting decision making: knowledge and attitude, and childbirth self-efficacy; and (4) external factors affecting decision making: social support, and the situational environment. At the initial period of China's two-child policy, nulliparous women have perceived their decision-making process regarding mode of delivery as one with complexity and uncertainty, influenced by both internal and external factors. This may have implications for the obstetric setting to develop a well-designed decision support system for pregnant women during the entire pregnancy periods. And it is recommended that care providers should assess women's preferences for mode of delivery from early pregnancy and provide adequate perinatal support and continuity of care for them. Copyright © 2018 Elsevier Ltd. All rights reserved.

An object-relational model for structured representation of medical knowledge.

PubMed

Koch, S; Risch, T; Schneider, W; Wagner, I V

2006-07-01

Domain specific knowledge is often not static but continuously evolving. This is especially true for the medical domain. Furthermore, the lack of standardized structures for presenting knowledge makes it difficult or often impossible to assess new knowledge in the context of existing knowledge. Possibilities to compare knowledge easily and directly are often not given. It is therefore of utmost importance to create a model that allows for comparability, consistency and quality assurance of medical knowledge in specific work situations. For this purpose, we have designed on object-relational model based on structured knowledge elements that are dynamically reusable by different multi-media-based tools for case-based documentation, disease course simulation, and decision support. With this model, high-level components, such as patient case reports or simulations of the course of a disease, and low-level components (e.g., diagnoses, symptoms or treatments) as well as the relationships between these components are modeled. The resulting schema has been implemented in AMOS II, on object-relational multi-database system supporting different views with regard to search and analysis depending on different work situations.

A knowledge-based decision support system in bioinformatics: an application to protein complex extraction

PubMed Central

2013-01-01

Background We introduce a Knowledge-based Decision Support System (KDSS) in order to face the Protein Complex Extraction issue. Using a Knowledge Base (KB) coding the expertise about the proposed scenario, our KDSS is able to suggest both strategies and tools, according to the features of input dataset. Our system provides a navigable workflow for the current experiment and furthermore it offers support in the configuration and running of every processing component of that workflow. This last feature makes our system a crossover between classical DSS and Workflow Management Systems. Results We briefly present the KDSS' architecture and basic concepts used in the design of the knowledge base and the reasoning component. The system is then tested using a subset of Saccharomyces cerevisiae Protein-Protein interaction dataset. We used this subset because it has been well studied in literature by several research groups in the field of complex extraction: in this way we could easily compare the results obtained through our KDSS with theirs. Our system suggests both a preprocessing and a clustering strategy, and for each of them it proposes and eventually runs suited algorithms. Our system's final results are then composed of a workflow of tasks, that can be reused for other experiments, and the specific numerical results for that particular trial. Conclusions The proposed approach, using the KDSS' knowledge base, provides a novel workflow that gives the best results with regard to the other workflows produced by the system. This workflow and its numeric results have been compared with other approaches about PPI network analysis found in literature, offering similar results. PMID:23368995

Fostering Wisdom-Based Action through Web 2.0 Communities of Practice: An Example of the Early Childhood Family Support Community of Practice

ERIC Educational Resources Information Center

Turnbull, Ann P.; Summers, Jean Ann; Gotto, George; Stowe, Matt; Beauchamp, Donna; Klein, Samara; Kyzar, Kathleen; Turnbull, Rud; Zuna, Nina

2009-01-01

This article discusses a new approach to knowledge translation using Web 2.0 technologies in an online Community of Practice (CoP). The purpose of the CoP is to promote wisdom-based action, a process that encourages people to engage with knowledge, match it to their own values, vision, and contexts, make a well-informed decision, and act on that…

PEP Talk: Prostate Education Program, "Cutting Through the Uncertainty of Prostate Cancer for Black Men Using Decision Support Instruments in Barbershops".

PubMed

Frencher, Stanley K; Sharma, Arun K; Teklehaimanot, Senait; Wadzani, Dennis; Ike, Ijeoma E; Hart, Alton; Norris, Keith

2016-09-01

The objective of this study was to investigate the effectiveness of using decision support instruments (DSI) to assist African-American (AA) men in making a prostate cancer (CaP) screening decision. This nonrandomized pretest-posttest comparison study assessed two DSI that were either culturally tailored or culturally nonspecific. CaP knowledge, intention to screen, and preferences were assessed before and after exposure to DSI using a convenience sample of 120 AA men aged 40 years and above. Participants interested in screening were referred to healthcare providers through a community-based patient navigator to obtain prostate-specific antigen (PSA) testing. We followed up 3 months after to determine if participants screened for CaP. CaP knowledge increased following exposure to both DSI in equivalent proportions. While similar proportions of men ultimately intended on having a PSA test following both DSI, bivariate analysis revealed that the culturally tailored DSI demonstrated a statistically significant increase in intention to screen. Participants' degree of certainty in their decision-making process with regard to CaP screening increased following the culturally tailored DSI (p < .001). The majority of participants planned on discussing CaP screening with a healthcare provider upon completion of the study. Barbershop-based health education can change the knowledge, preferences, intentions, and behaviors of this at-risk population. At 3 months follow-up, half (n = 58) of the participants underwent PSA testing, which led to the diagnosis of CaP in one participant. Community-led interventions for CaP, such as cluster-randomized designs in barbershops, are needed to better assess the efficacy of DSI in community settings.

Analysis of Nursing Clinical Decision Support Requests and Strategic Plan in a Large Academic Health System.

PubMed

Whalen, Kimberly; Bavuso, Karen; Bouyer-Ferullo, Sharon; Goldsmith, Denise; Fairbanks, Amanda; Gesner, Emily; Lagor, Charles; Collins, Sarah

2016-01-01

To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. "Risk Assessments/Risk Reduction/Promotion of Healthy Habits" (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan.

Randomized controlled trial of a video decision support tool for cardiopulmonary resuscitation decision making in advanced cancer.

PubMed

Volandes, Angelo E; Paasche-Orlow, Michael K; Mitchell, Susan L; El-Jawahri, Areej; Davis, Aretha Delight; Barry, Michael J; Hartshorn, Kevan L; Jackson, Vicki Ann; Gillick, Muriel R; Walker-Corkery, Elizabeth S; Chang, Yuchiao; López, Lenny; Kemeny, Margaret; Bulone, Linda; Mann, Eileen; Misra, Sumi; Peachey, Matt; Abbo, Elmer D; Eichler, April F; Epstein, Andrew S; Noy, Ariela; Levin, Tomer T; Temel, Jennifer S

2013-01-20

Decision making regarding cardiopulmonary resuscitation (CPR) is challenging. This study examined the effect of a video decision support tool on CPR preferences among patients with advanced cancer. We performed a randomized controlled trial of 150 patients with advanced cancer from four oncology centers. Participants in the control arm (n = 80) listened to a verbal narrative describing CPR and the likelihood of successful resuscitation. Participants in the intervention arm (n = 70) listened to the identical narrative and viewed a 3-minute video depicting a patient on a ventilator and CPR being performed on a simulated patient. The primary outcome was participants' preference for or against CPR measured immediately after exposure to either modality. Secondary outcomes were participants' knowledge of CPR (score range of 0 to 4, with higher score indicating more knowledge) and comfort with video. The mean age of participants was 62 years (standard deviation, 11 years); 49% were women, 44% were African American or Latino, and 47% had lung or colon cancer. After the verbal narrative, in the control arm, 38 participants (48%) wanted CPR, 41 (51%) wanted no CPR, and one (1%) was uncertain. In contrast, in the intervention arm, 14 participants (20%) wanted CPR, 55 (79%) wanted no CPR, and 1 (1%) was uncertain (unadjusted odds ratio, 3.5; 95% CI, 1.7 to 7.2; P < .001). Mean knowledge scores were higher in the intervention arm than in the control arm (3.3 ± 1.0 v 2.6 ± 1.3, respectively; P < .001), and 65 participants (93%) in the intervention arm were comfortable watching the video. Participants with advanced cancer who viewed a video of CPR were less likely to opt for CPR than those who listened to a verbal narrative.

Effective visualization of integrated knowledge and data to enable informed decisions in drug development and translational medicine

PubMed Central

2013-01-01

Integrative understanding of preclinical and clinical data is imperative to enable informed decisions and reduce the attrition rate during drug development. The volume and variety of data generated during drug development have increased tremendously. A new information model and visualization tool was developed to effectively utilize all available data and current knowledge. The Knowledge Plot integrates preclinical, clinical, efficacy and safety data by adding two concepts: knowledge from the different disciplines and protein binding. Internal and public available data were gathered and processed to allow flexible and interactive visualizations. The exposure was expressed as the unbound concentration of the compound and the treatment effect was normalized and scaled by including expert opinion on what a biologically meaningful treatment effect would be. The Knowledge Plot has been applied both retrospectively and prospectively in project teams in a number of different therapeutic areas, resulting in closer collaboration between multiple disciplines discussing both preclinical and clinical data. The Plot allows head to head comparisons of compounds and was used to support Candidate Drug selections and differentiation from comparators and competitors, back translation of clinical data, understanding the predictability of preclinical models and assays, reviewing drift in primary endpoints over the years, and evaluate or benchmark compounds in due diligence comparing multiple attributes. The Knowledge Plot concept allows flexible integration and visualization of relevant data for interpretation in order to enable scientific and informed decision-making in various stages of drug development. The concept can be used for communication, decision-making, knowledge management, and as a forward and back translational tool, that will result in an improved understanding of the competitive edge for a particular project or disease area portfolio. In addition, it also builds up a knowledge and translational continuum, which in turn will reduce the attrition rate and costs of clinical development by identifying poor candidates early. PMID:24098919

A Design Rationale Capture Tool to Support Design Verification and Re-use

NASA Technical Reports Server (NTRS)

Hooey, Becky Lee; Da Silva, Jonny C.; Foyle, David C.

2012-01-01

A design rationale tool (DR tool) was developed to capture design knowledge to support design verification and design knowledge re-use. The design rationale tool captures design drivers and requirements, and documents the design solution including: intent (why it is included in the overall design); features (why it is designed the way it is); information about how the design components support design drivers and requirements; and, design alternatives considered but rejected. For design verification purposes, the tool identifies how specific design requirements were met and instantiated within the final design, and which requirements have not been met. To support design re-use, the tool identifies which design decisions are affected when design drivers and requirements are modified. To validate the design tool, the design knowledge from the Taxiway Navigation and Situation Awareness (T-NASA; Foyle et al., 1996) system was captured and the DR tool was exercised to demonstrate its utility for validation and re-use.

Perspectives of self-direction: a systematic review of key areas contributing to service users' engagement and choice-making in self-directed disability services and supports.

PubMed

Lakhani, Ali; McDonald, Donna; Zeeman, Heidi

2018-05-01

Self-directed disability support policies aim to encourage greater choice and control for service users in terms of the health and social care they receive. The proliferation of self-directed disability support policies throughout the developed world has resulted in a growing amount of research exploring the outcomes for service users, and their families and carers. Our understanding of the issues faced by people with disabilities, particularly how they make health and social care decisions and the key areas that determine their engagement with service providers within a self-directed environment is limited. A synthesis of research is timely and can provide knowledge for service users and health and social care support providers to ensure their successful participation. A systematic review guided by the PRISMA approach explored (i) the key areas determining service users' engagement with self-directed disability services and supports, and (ii) how service users make informed decisions about providers. In October 2014 and April 2016, three databases - MEDLINE, CINAHL and Web of Science - were searched for research and review articles. Eighteen sources met the search criteria. Findings were mapped into either: key areas determining service user engagement, or service users' informed decision-making. Findings concerning key areas determining engagement fell into three themes - personal responsibility for budgeting, personalised approaches, and a cultural shift in practice and delivery among service providers. Findings about decision-making yielded two themes - supporting informed decision-making and inhibiting informed decision-making. Literature suggests that self-directed models of care may provide service users with increased control over the services that they receive. Increased control for some service users and their families requires independent external decision-making support, particularly around the domains of budgeting, planning and hiring. Future research must continue to investigate the perspectives of service users pertaining to their engagement, as their participation is central to the effectiveness of the approach. © 2016 John Wiley & Sons Ltd.

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).

Design, Development, and Initial Evaluation of a Terminology for Clinical Decision Support and Electronic Clinical Quality Measurement.

PubMed

Lin, Yanhua; Staes, Catherine J; Shields, David E; Kandula, Vijay; Welch, Brandon M; Kawamoto, Kensaku

2015-01-01

When coupled with a common information model, a common terminology for clinical decision support (CDS) and electronic clinical quality measurement (eCQM) could greatly facilitate the distributed development and sharing of CDS and eCQM knowledge resources. To enable such scalable knowledge authoring and sharing, we systematically developed an extensible and standards-based terminology for CDS and eCQM in the context of the HL7 Virtual Medical Record (vMR) information model. The development of this terminology entailed three steps: (1) systematic, physician-curated concept identification from sources such as the Health Information Technology Standards Panel (HITSP) and the SNOMED-CT CORE problem list; (2) concept de-duplication leveraging the Unified Medical Language System (UMLS) MetaMap and Metathesaurus; and (3) systematic concept naming using standard terminologies and heuristic algorithms. This process generated 3,046 concepts spanning 68 domains. Evaluation against representative CDS and eCQM resources revealed approximately 50-70% concept coverage, indicating the need for continued expansion of the terminology.

Dimensions of autonomy: Primary teachers' decisions about involvement in science professional development

NASA Astrophysics Data System (ADS)

Schibeci, Renato A.; Hickey, Ruth L.

2004-01-01

Professional development (PD) for primary science teachers is recognized as an important activity which can support improved science education for students. Analysis of interviews with practicing primary science teachers is used to identify the range of PD experiences of a sample of teachers from Western Australia. Teachers' reasons for attending or avoiding science-related PD are categorized as decision issues which include opportunity, compulsion, convenience, enticement, interest, recommendation, and relevance. Case studies describe the interplay of these issues, which result in teachers' attendance or avoidance of PD. A subset of the sample is used to explore teachers' views of other activities which they recognize as contributing to their science teaching, content knowledge, and pedagogy. These other activities include hobbies, partner's job, and pursuing students' interests. Legitimating teachers' own interests as a source of personally derived PD is supported as an avenue to increase the diversity of topics studied by students and to increase the level of content knowledge held by teachers.

Design, Development, and Initial Evaluation of a Terminology for Clinical Decision Support and Electronic Clinical Quality Measurement

PubMed Central

Lin, Yanhua; Staes, Catherine J; Shields, David E; Kandula, Vijay; Welch, Brandon M; Kawamoto, Kensaku

2015-01-01

When coupled with a common information model, a common terminology for clinical decision support (CDS) and electronic clinical quality measurement (eCQM) could greatly facilitate the distributed development and sharing of CDS and eCQM knowledge resources. To enable such scalable knowledge authoring and sharing, we systematically developed an extensible and standards-based terminology for CDS and eCQM in the context of the HL7 Virtual Medical Record (vMR) information model. The development of this terminology entailed three steps: (1) systematic, physician-curated concept identification from sources such as the Health Information Technology Standards Panel (HITSP) and the SNOMED-CT CORE problem list; (2) concept de-duplication leveraging the Unified Medical Language System (UMLS) MetaMap and Metathesaurus; and (3) systematic concept naming using standard terminologies and heuristic algorithms. This process generated 3,046 concepts spanning 68 domains. Evaluation against representative CDS and eCQM resources revealed approximately 50–70% concept coverage, indicating the need for continued expansion of the terminology. PMID:26958220

Unintended adverse consequences of a clinical decision support system: two cases.

PubMed

Stone, Erin G

2018-05-01

Many institutions have implemented clinical decision support systems (CDSSs). While CDSS research papers have focused on benefits of these systems, there is a smaller body of literature showing that CDSSs may also produce unintended adverse consequences (UACs). Detailed here are 2 cases of UACs resulting from a CDSS. Both of these cases were related to external systems that fed data into the CDSS. In the first case, lack of knowledge of data categorization in an external pharmacy system produced a UAC; in the second case, the change of a clinical laboratory instrument produced the UAC. CDSSs rely on data from many external systems. These systems are dynamic and may have changes in hardware, software, vendors, or processes. Such changes can affect the accuracy of CDSSs. These cases point to the need for the CDSS team to be familiar with these external systems. This team (manager and alert builders) should include members in specific clinical specialties with deep knowledge of these external systems.

Choosing a Model of Maternity Care: Decision Support Needs of Australian Women.

PubMed

Stevens, Gabrielle; Miller, Yvette D; Watson, Bernadette; Thompson, Rachel

2016-06-01

Access to information on the features and outcomes associated with the various models of maternity care available in Australia is vital for women's informed decision-making. This study sought to identify women's preferences for information access and decision-making involvement, as well as their priority information needs, for model of care decision-making. A convenience sample of adult women of childbearing age in Queensland, Australia were recruited to complete an online survey assessing their model of care decision support needs. Knowledge on models of care and socio-demographic characteristics were also assessed. Altogether, 641 women provided usable survey data. Of these women, 26.7 percent had heard of all available models of care before starting the survey. Most women wanted access to information on models of care (90.4%) and an active role in decision-making (99.0%). Nine priority information needs were identified: cost, access to choice of mode of birth and care provider, after hours provider contact, continuity of carer in labor/birth, mobility during labor, discussion of the pros/cons of medical procedures, rates of skin-to-skin contact after birth, and availability at a preferred birth location. This information encompassed the priority needs of women across age, birth history, and insurance status subgroups. This study demonstrates Australian women's unmet needs for information that supports them to effectively compare available options for model of maternity care. Findings provide clear direction on what information should be prioritized and ideal channels for information access to support quality decision-making in practice. © 2015 Wiley Periodicals, Inc.

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.

Personalized health care and health information technology policy: an exploratory analysis.

PubMed

Wald, Jonathan S; Shapiro, Michael

2013-01-01

Personalized healthcare (PHC) is envisioned to enhance clinical practice decision-making using new genome-driven knowledge that tailors diagnosis, treatment, and prevention to the individual patient. In 2012, we conducted a focused environmental scan and informal interviews with fifteen experts to anticipate how PHC might impact health Information Technology (IT) policy in the United States. Findings indicatedthat PHC has a variable impact on current clinical practice, creates complex questions for providers, patients, and policy-makers, and will require a robust health IT infrastructure with advanced data architecture, clinical decision support, provider workflow tools, and re-use of clinical data for research. A number of health IT challenge areas were identified, along with five policy areas including: interoperable clinical decision support, standards for patient values and preferences, patient engagement, data transparency, and robust privacy and security.

Factors that contribute to physician variability in decisions to limit life support in the ICU: a qualitative study.

PubMed

Wilson, Michael E; Rhudy, Lori M; Ballinger, Beth A; Tescher, Ann N; Pickering, Brian W; Gajic, Ognjen

2013-06-01

Our aim was to explore reasons for physician variability in decisions to limit life support in the intensive care unit (ICU) utilizing qualitative methodology. Single center study consisting of semi-structured interviews with experienced physicians and nurses. Seventeen intensivists from medical (n = 7), surgical (n = 5), and anesthesia (n = 5) critical care backgrounds, and ten nurses from medical (n = 5) and surgical (n = 5) ICU backgrounds were interviewed. Principles of grounded theory were used to analyze the interview transcripts. Eleven factors within four categories were identified that influenced physician variability in decisions to limit life support: (1) physician work environment-workload and competing priorities, shift changes and handoffs, and incorporation of nursing input; (2) physician experiences-of unexpected patient survival, and of limiting life support in physician's family; (3) physician attitudes-investment in a good surgical outcome, specialty perspective, values and beliefs; and (4) physician relationship with patient and family-hearing the patient's wishes firsthand, engagement in family communication, and family negotiation. We identified several factors which physicians and nurses perceived were important sources of physician variability in decisions to limit life support. Ways to raise awareness and ameliorate the potentially adverse effects of factors such as workload, competing priorities, shift changes, and handoffs should be explored. Exposing intensivists to long term patient outcomes, formalizing nursing input, providing additional training, and emphasizing firsthand knowledge of patient wishes may improve decision making.

Executable medical guidelines with Arden Syntax-Applications in dermatology and obstetrics.

PubMed

Seitinger, Alexander; Rappelsberger, Andrea; Leitich, Harald; Binder, Michael; Adlassnig, Klaus-Peter

2016-08-12

Clinical decision support systems (CDSSs) are being developed to assist physicians in processing extensive data and new knowledge based on recent scientific advances. Structured medical knowledge in the form of clinical alerts or reminder rules, decision trees or tables, clinical protocols or practice guidelines, score algorithms, and others, constitute the core of CDSSs. Several medical knowledge representation and guideline languages have been developed for the formal computerized definition of such knowledge. One of these languages is Arden Syntax for Medical Logic Systems, an International Health Level Seven (HL7) standard whose development started in 1989. Its latest version is 2.10, which was presented in 2014. In the present report we discuss Arden Syntax as a modern medical knowledge representation and processing language, and show that this language is not only well suited to define clinical alerts, reminders, and recommendations, but can also be used to implement and process computerized medical practice guidelines. This section describes how contemporary software such as Java, server software, web-services, XML, is used to implement CDSSs based on Arden Syntax. Special emphasis is given to clinical decision support (CDS) that employs practice guidelines as its clinical knowledge base. Two guideline-based applications using Arden Syntax for medical knowledge representation and processing were developed. The first is a software platform for implementing practice guidelines from dermatology. This application employs fuzzy set theory and logic to represent linguistic and propositional uncertainty in medical data, knowledge, and conclusions. The second application implements a reminder system based on clinically published standard operating procedures in obstetrics to prevent deviations from state-of-the-art care. A to-do list with necessary actions specifically tailored to the gestational week/labor/delivery is generated. Today, with the latest versions of Arden Syntax and the application of contemporary software development methods, Arden Syntax has become a powerful and versatile medical knowledge representation and processing language, well suited to implement a large range of CDSSs, including clinical-practice-guideline-based CDSSs. Moreover, such CDS is provided and can be shared as a service by different medical institutions, redefining the sharing of medical knowledge. Arden Syntax is also highly flexible and provides developers the freedom to use up-to-date software design and programming patterns for external patient data access. Copyright © 2016. Published by Elsevier B.V.

Development and evaluation of a breast cancer prevention decision aid for higher‐risk women

PubMed Central

Stacey, Dawn; O'Connor, Annette M.; DeGrasse, Cathy; Verma, Shailendra

2003-01-01

Abstract Objective  To develop and evaluate the effectiveness of a breast cancer prevention decision aid for women aged 50 and older at higher risk of breast cancer. Design  Pre‐test–post‐test study using decision aid alone and in combination with counselling. Setting  Breast Cancer Risk Assessment Clinic. Participants  Twenty‐seven women aged 50–69 with 1.66% or higher 5‐year risk of breast cancer. Intervention  Self‐administered breast cancer prevention decision aid. Main outcome measures  Acceptability; decisional conflict; knowledge; realistic expectations; choice predisposition; intention to improve life‐style practices; psychological distress; and satisfaction with preparation for consultation. Results  The decision aid alone, or in combination with counselling, decreased some dimensions of decisional conflict, increased knowledge (P < 0.01), and created more realistic expectations (P < 0.01). The aid in combination with counselling, significantly reduced decisional conflict (P < 0.01) and psychological distress (P < 0.02), helped the uncertain become certain (P < 0.02), and increased intentions to adopt healthier life‐style practices (P < 0.03). Women rated the aid as acceptable, and both women and practitioners were satisfied with the effect it had on the counselling session. Conclusion  The decision aid shows promise as a useful decision support tool. Further research should compare the effect of the decision aid in combination with counselling to counselling alone. PMID:12603624

Effect of a patient decision aid (PDA) for type 2 diabetes on knowledge, decisional self-efficacy, and decisional conflict.

PubMed

Bailey, Robert A; Pfeifer, Michael; Shillington, Alicia C; Harshaw, Qing; Funnell, Martha M; VanWingen, Jeffrey; Col, Nanada

2016-01-14

Patients with type 2 diabetes (T2DM) often have poor glycemic control on first-line pharmacologic therapy and require treatment intensification. Intensification decisions can be difficult because of many available options and their many benefits and risks. The American Diabetes Association recommends patient-centered, evidence-based tools supporting shared decision-making between patients and clinicians. We developed a patient decision aid (PDA) targeting decisions about treatment intensification for T2DM. Our objective was to determine the effectiveness of this PDA for patients with T2DM on metformin who require treatment intensification. This study was a pragmatic randomized controlled trial conducted in 27 US primary care and endocrinology clinics. Subjects were English-speaking adults with T2DM receiving metformin with persistent hyperglycemia who were recommended to consider medication intensification. Subjects were randomized to receive either the PDA or usual care (UC). Main outcome measures were change in knowledge, decisional self-efficacy, and decisional conflict. Of 225 subjects enrolled, 114 were randomized to the PDA and 111 to UC. Mean [SD] age was 52 [1] years, time since T2DM diagnosis was 6 [+/-6] years, 45.3% were male, and most (55.5%) were non-Caucasian. Compared to UC, PDA users had significantly larger knowledge gains (35.0% [22.3] vs 9.9% [22.2]; P < 0.0001) and larger improvements in self-efficacy (3.7 [16.7] vs-3.9 [19.2]; P < 0.0001) and decisional conflict (-22.2 [20.6] vs-7.5 [16.6]; P < 0.0001). The PDA resulted in substantial and significant improvements in knowledge, decisional conflict and decisional self-efficacy. Decisional conflict scores after PDA use were within the range that correlates with effective decision-making. This PDA has the potential to facilitate shared-decision-making for patients with T2DM. NCT02110979.

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.

From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support

PubMed Central

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-01-01

Objectives 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; 3) To ensure the BN model can be used for interventional analysis; 4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. Method The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. Results When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. Conclusions This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. PMID:26830286

From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.

PubMed

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-02-01

(1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; (2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; (3) To ensure the BN model can be used for interventional analysis; (4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. Copyright © 2016 Elsevier B.V. All rights reserved.

Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

PubMed

Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J

2014-12-12

Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p < 0.01). Combining decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based decision aid component performed comparably with the videobooklet decision aid used in clinical practice. Future studies may use this interactive research platform to study patients' decision making processes in real-time, explore interdisciplinary approaches to designing web-based decision aids, and test strategies for tailoring decision support to meet patients' needs and preferences.

[Knowledge management system for laboratory work and clinical decision support].

PubMed

Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

2011-05-01

This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.

Factors influencing U.S. consumer support for genetic modification to prevent crop disease.

PubMed

McComas, Katherine A; Besley, John C; Steinhardt, Joseph

2014-07-01

This study examines support for the genetic modification (GM) of crops in the context of preventing "late blight," a devastating potato and tomato disease that caused the Irish Potato Famine in the 1850s and results in substantial crop loss today. We surveyed U.S. adults who do the primary grocery shopping in their household (n = 859). Half of the respondents were randomly assigned to read a vignette describing late blight before responding to questions about GM, whereas the other half read a vignette about generic crop disease before responding to questions. We also examine how the perceived fairness of decision makers relates to GM support and the perceived legitimacy of GM decision making. We found that disease specificity mattered less to support and legitimacy than the perceived fairness of decision makers. The perceived risks of GM to human and environmental health negatively related to GM support and legitimacy, whereas the perceived benefits (e.g. reduced threats to crops and a more secure food supply) positively related to support and legitimacy. Objective knowledge about GM had a small, negative relationship with legitimacy whereas self-assessed familiarity with GM had a positive relationship. Overall, the results offer additional confirmation of past findings from more localized settings that perceived fairness of decision makers matters to support for GM and underscore the importance of considering how risk managers' behaviors and actions are perceived alongside individuals' perceptions about the risks and benefits. Copyright © 2014 Elsevier Ltd. All rights reserved.

[A network of LIFE projects to promote the transfer and exchange of knowledge on environment and health].

PubMed

Cori, Liliana; Carducci, Annalaura; Donzelli, Gabriele; La Rocca, Cinzia; Bianchi, Fabrizio

2018-01-01

Eleven projects within the LIFE programme (through which the Directorate-General for Environment of the European Commission provides funding for projects aim at protecting environment and nature) addressing environmental-health-related issues have been involved in a collaborative network called KTE LIFE EnvHealth Network. The shared issues tackled by that projects are knowledge transfer and exchange (KTE). The objective of the LIFE programme is to support the implementation of the environmental legislation in the European Union, to provide new tools and knowledge that will help to better protect both the territory and the communities. Transferring knowledge to decision makers, at the appropriate and effective level, is therefore a central function of the projects. The Network promotes national and international networking, which intends to involve other projects, to provide methodological support, to make information and successful practices circulate, with the aim of multiplying the energies of each project involved.

Selection of Construction Methods: A Knowledge-Based Approach

PubMed Central

Skibniewski, Miroslaw

2013-01-01

The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method' selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS) was developed and then validated with construction industry professionals. As a conclusion, the CMKS was perceived as a valuable tool for construction methods' selection, by helping companies to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The described benefits as provided by the system favor a better performance of construction projects. PMID:24453925

Information gathering, management and transfering for geospacial intelligence

NASA Astrophysics Data System (ADS)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-07-01

Information is a key subject in modern organization operations. The success of joint and combined operations with organizations partners depends on the accurate information and knowledge flow concerning the operations theatre: provision of resources, environment evolution, markets location, where and when an event occurred. As in the past and nowadays we cannot conceive modern operations without maps and geo-spatial information (GI). Information and knowledge management is fundamental to the success of organizational decisions in an uncertainty environment. The georeferenced information management is a process of knowledge management, it begins in the raw data and ends on generating knowledge. GI and intelligence systems allow us to integrate all other forms of intelligence and can be a main platform to process and display geo-spatial-time referenced events. Combining explicit knowledge with peoples know-how to generate a continuous learning cycle that supports real time decisions mitigates the influences of fog of everyday competition and provides the knowledge supremacy. Extending the preliminary analysis done in [1], this work applies the exploratory factor analysis to a questionnaire about the GI and intelligence management in an organization company allowing to identify future lines of action to improve information process sharing and exploration of all the potential of this important resource.

Building Information Management as a Tool for Managing Knowledge throughout whole Building Life Cycle

NASA Astrophysics Data System (ADS)

Nývlt, Vladimír; Prušková, Kristýna

2017-10-01

BIM today is much more than drafting in 3D only, and project participants are further challenging, what is the topic of both this paper, and further research. Knowledge of objects, their behaviour, and other characteristics has high impact on whole building life cycle. Other structured and unstructured knowledge is rightfully added (e.g. historically based experience, needs and requirements of users, investors, needs for project and objects revisions) Grasping of all attributes into system for collection, managing and time control of knowledge. Further important findings lie in the necessity of understanding how to manage knowledge needs with diverse and variable ways, when BIM maturity levels are advanced, as defined by Bew and Richards (2008). All decisions made would always rely on good, timely, and correct data. Usage of BIM models in terms of Building Information Management can support all decisions through data gathering, sharing, and using across all disciplines and all Life Cycle steps. It particularly significantly improves possibilities and level of life cycle costing. Experience and knowledge stored in data models of BIM, describing user requirements, best practices derived from other projects and/or research outputs will help to understand sustainability in its complexity and wholeness.

Building University Capacity to Visualize Solutions to Complex Problems in the Arctic

NASA Astrophysics Data System (ADS)

Broderson, D.; Veazey, P.; Raymond, V. L.; Kowalski, K.; Prakash, A.; Signor, B.

2016-12-01

Rapidly changing environments are creating complex problems across the globe, which are particular magnified in the Arctic. These worldwide challenges can best be addressed through diverse and interdisciplinary research teams. It is incumbent on such teams to promote co-production of knowledge and data-driven decision-making by identifying effective methods to communicate their findings and to engage with the public. Decision Theater North (DTN) is a new semi-immersive visualization system that provides a space for teams to collaborate and develop solutions to complex problems, relying on diverse sets of skills and knowledge. It provides a venue to synthesize the talents of scientists, who gather information (data); modelers, who create models of complex systems; artists, who develop visualizations; communicators, who connect and bridge populations; and policymakers, who can use the visualizations to develop sustainable solutions to pressing problems. The mission of Decision Theater North is to provide a cutting-edge visual environment to facilitate dialogue and decision-making by stakeholders including government, industry, communities and academia. We achieve this mission by adopting a multi-faceted approach reflected in the theater's design, technology, networking capabilities, user support, community relationship building, and strategic partnerships. DTN is a joint project of Alaska's National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) and the University of Alaska Fairbanks (UAF), who have brought the facility up to full operational status and are now expanding its development space to support larger team science efforts. Based in Fairbanks, Alaska, DTN is uniquely poised to address changes taking place in the Arctic and subarctic, and is connected with a larger network of decision theaters that include the Arizona State University Decision Theater Network and the McCain Institute in Washington, DC.

Patient Perspectives on Low-Dose Computed Tomography for Lung Cancer Screening, New Mexico, 2014

PubMed Central

Sussman, Andrew L.; Murrietta, Ambroshia M.; Getrich, Christina M.; Rhyne, Robert; Crowell, Richard E.; Taylor, Kathryn L.; Reifler, Ellen J.; Wescott, Pamela H.; Saeed, Ali I.; Hoffman, Richard M.

2016-01-01

Introduction National guidelines call for annual lung cancer screening for high-risk smokers using low-dose computed tomography (LDCT). The objective of our study was to characterize patient knowledge and attitudes about lung cancer screening, smoking cessation, and shared decision making by patient and health care provider. Methods We conducted semistructured qualitative interviews with patients with histories of heavy smoking who received care at a Federally Qualified Health Center (FQHC Clinic) and at a comprehensive cancer center-affiliated chest clinic (Chest Clinic) in Albuquerque, New Mexico. The interviews, conducted from February through September 2014, focused on perceptions about health screening, knowledge and attitudes about LDCT screening, and preferences regarding decision aids. We used a systematic iterative analytic process to identify preliminary and emergent themes and to create a coding structure. Results We reached thematic saturation after 22 interviews (10 at the FQHC Clinic, 12 at the Chest Clinic). Most patients were unaware of LDCT screening for lung cancer but were receptive to the test. Some smokers said they would consider quitting smoking if their screening result were positive. Concerns regarding screening were cost, radiation exposure, and transportation issues. To support decision making, most patients said they preferred one-on-one discussions with a provider. They also valued decision support tools (print materials, videos), but raised concerns about readability and Internet access. Conclusion Implementing lung cancer screening in sociodemographically diverse populations poses significant challenges. The value of tobacco cessation counseling cannot be overemphasized. Effective interventions for shared decision making to undergo lung cancer screening will need the active engagement of health care providers and will require the use of accessible decision aids designed for people with low health literacy. PMID:27536900

Correlates of healthcare and financial decision making among older adults without dementia.

PubMed

Stewart, Christopher C; Yu, Lei; Wilson, Robert S; Bennett, David A; Boyle, Patricia A

2018-03-22

Healthcare and financial decision making among older persons has been previously associated with cognition, health and financial literacy, and risk aversion; however, the manner by which these resources support decision making remains unclear, as past studies have not systematically investigated the pathways linking these resources with decision making. In the current study, we use path analysis to examine the direct and indirect pathways linking age, education, cognition, literacy, and risk aversion with decision making. We also decomposed literacy into its subcomponents, conceptual knowledge and numeracy, in order to examine their associations with decision making. Participants were 937 community-based older adults without dementia from the Rush Memory and Aging Project who completed a battery of cognitive tests and assessments of healthcare and financial decision making, health and financial literacy, and risk aversion. Age and education exerted effects on decision making, but nearly two thirds of their effects were indirect, working mostly through cognition and literacy. Cognition exerted a strong direct effect on decision making and a robust indirect effect working primarily through literacy. Literacy also exerted a powerful direct effect on decision making, as did its subcomponents, conceptual knowledge and numeracy. The direct effect of risk aversion was comparatively weak. In addition to cognition, health and financial literacy emerged as independent and primary correlates of healthcare and financial decision making. These findings suggest specific actions that might be taken to optimize healthcare and financial decision making and, by extension, improve health and well-being in advanced age. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Adult-Onset Type 1 Diabetes: A Qualitative Study of Decision-Making Needs.

PubMed

Jull, Janet; Witteman, Holly O; Ferne, Judi; Yoganathan, Manosila; Stacey, Dawn

2016-04-01

Type 1 diabetes is an autoimmune disease resulting from insulin deficiency and must be carefully managed to prevent serious health complications. Diabetes education and management strategies usually focus on meeting the decision-making needs of children and their families, but little is known about the decisional needs of people with adult-onset type 1 diabetes. The aim of this study was to explore the diabetes-related decision-making needs of people diagnosed with adult-onset type 1 diabetes. An interpretive descriptive qualitative study was conducted. Participants who self-identified as having adult-onset type 1 diabetes were interviewed using a semistructured interview guide. Transcripts were coded to identify needs, supports and barriers using thematic analysis. Participating in the study were 8 adults (2 men, 6 women), ages 33 to 57, with type 1 diabetes for durations of 1 to 20 or more years. Their decision-making needs are summarized in 6 broad themes: 1) people diagnosed with type 1 diabetes are launched into a process of decision-making; 2) being diagnosed with type 1 diabetes means you will always have to make decisions; 3) knowledge is crucial; 4) personal preferences matter; 5) support is critical for decisions about self-care in type 1 diabetes; 6) living with type 1 diabetes means making very individualized decisions about daily life. The findings describe the sudden and ubiquitous nature of type 1 diabetes decision-making and the need to tailor approaches for making care decisions in type 1 diabetes. People diagnosed with adult-onset type 1 diabetes require access to reliable information, support and opportunities for participation in decision-making. Copyright © 2016 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Knowledge Assisted Integrated Design of a Component and Its Manufacturing Process

NASA Astrophysics Data System (ADS)

Gautham, B. P.; Kulkarni, Nagesh; Khan, Danish; Zagade, Pramod; Reddy, Sreedhar; Uppaluri, Rohith

Integrated design of a product and its manufacturing processes would significantly reduce the total cost of the products as well as the cost of its development. However this would only be possible if we have a platform that allows us to link together simulations tools used for product design, performance evaluation and its manufacturing processes in a closed loop. In addition to that having a comprehensive knowledgebase that provides systematic knowledge guided assistance to product or process designers who may not possess in-depth design knowledge or in-depth knowledge of the simulation tools, would significantly speed up the end-to-end design process. In this paper, we propose a process and illustrate a case for achieving an integrated product and manufacturing process design assisted by knowledge support for the user to make decisions at various stages. We take transmission component design as an example. The example illustrates the design of a gear for its geometry, material selection and its manufacturing processes, particularly, carburizing-quenching and tempering, and feeding the material properties predicted during heat treatment into performance estimation in a closed loop. It also identifies and illustrates various decision stages in the integrated life cycle and discusses the use of knowledge engineering tools such as rule-based guidance, to assist the designer make informed decisions. Simulation tools developed on various commercial, open-source platforms as well as in-house tools along with knowledge engineering tools are linked to build a framework with appropriate navigation through user-friendly interfaces. This is illustrated through examples in this paper.

Easing the transition between hospital and home: translating knowledge into action.

PubMed

Baumbusch, Jennifer; Semeniuk, Pat; McDonald, Heather; Khan, Koushambhi Basu; Reimer Kirkham, Sheryl; Tan, Elsie; Anderson, Joan M

2007-10-01

Knowledge translation is an interactive, dynamic approach to the uptake of evidence-based knowledge. In this article, the authors present a collaborative model for knowledge translation that grew out of a program of research focusing on the experiences of patients from ethnoculturally diverse groups as they were discharged home from hospital. Research findings highlight issues around gaps in the continuity of services and language and communication. The authors discuss a number of knowledge translation initiatives that were developed to address these gaps. Key to the success of this process has been a collaborative relationship between researchers and practitioners that is grounded in the shared goal of knowledge translation to support ethically sound decision-making in the delivery of health-care services.

Clinical intuition in the nursing process and decision-making-A mixed-studies review.

PubMed

Melin-Johansson, Christina; Palmqvist, Rebecca; Rönnberg, Linda

2017-12-01

To review what is characteristic of registered nurses' intuition in clinical settings, in relationships and in the nursing process. Intuition is a controversial concept and nurses believe that there are difficulties in how they should explain their nursing actions or decisions based on intuition. Much of the evidence from the body of research indicates that nurses value their intuition in a variety of clinical settings. More information on how nurses integrate intuition as a core element in daily clinical work would contribute to an improved understanding on how they go about this. Intuition deserves a place in evidence-based activities, where intuition is an important component associated with the nursing process. An integrative review strengthened with a mixed-studies review. Literature searches were conducted in the databases CINAHL, PubMed and PsycINFO, and literature published 1985-2016 were included. The findings in the studies were analysed with content analysis, and the synthesis process entailed a reasoning between the authors. After a quality assessment, 16 studies were included. The analysis and synthesis resulted in three categories. The characteristics of intuition in the nurse's daily clinical activities include application, assertiveness and experiences; in the relationships with patients' intuition include unique connections, mental and bodily responses, and personal qualities; and in the nursing process include support and guidance, component and clues in decision-making, and validating decisions. Intuition is more than simply a "gut feeling," and it is a process based on knowledge and care experience and has a place beside research-based evidence. Nurses integrate both analysis and synthesis of intuition alongside objective data when making decisions. They should rely on their intuition and use this knowledge in clinical practice as a support in decision-making, which increases the quality and safety of patient care. We find that intuition plays a key role in more or less all of the steps in the nursing process as a base for decision-making that supports safe patient care, and is a validated component of nursing clinical care expertise. © 2017 John Wiley & Sons Ltd.

Pathways: patient-centred decision counselling for women at risk of cancer-related infertility: a protocol for a comparative effectiveness cluster randomised trial.

PubMed

Woodard, Terri Lynn; Hoffman, Aubri S; Crocker, Laura C; Holman, Deborah A; Hoffman, Derek B; Ma, Jusheng; Bassett, Roland L; Leal, Viola B; Volk, Robert J

2018-02-21

National guidelines recommend that all reproductive-age women with cancer be informed of their fertility risks and offered referral to fertility specialists to discuss fertility preservation options. However, reports indicate that only 5% of patients have consultations, and rates of long-term infertility-related distress remain high. Previous studies report several barriers to fertility preservation; however, initial success has been reported using provider education, patient decision aids and navigation support. This protocol will test effects of a multicomponent intervention compared with usual care on women's fertility preservation knowledge and decision-making outcomes. This cluster-randomised trial will compare the multicomponent intervention (provider education, patient decision aid and navigation support) with usual care (consultation and referral, if requested). One hundred newly diagnosed English-speaking women of reproductive age who are at risk of cancer-related infertility will be recruited from four regional oncology clinics.The Pathways patient decision aid website provides (1) up-to-date evidence and descriptions of fertility preservation and other family-building options, tailored to cancer type; (2) structured guidance to support personalising the information and informed decision-making; and (3) a printable summary to help women prepare for discussions with their oncologist and/or fertility specialist. Four sites will be randomly assigned to intervention or control groups. Participants will be recruited after their oncology consultation and asked to complete online questionnaires at baseline, 1 week and 2 months to assess their demographics, fertility preservation knowledge, and decision-making process and quality. The primary outcome (decisional conflict) will be tested using Fisher's exact test. Secondary outcomes will be assessed using generalised linear mixed models, and sensitivity analyses will be conducted, as appropriate. The University of Texas MD Anderson Cancer Center provided approval and ongoing review of this protocol. Results will be presented at relevant scientific meetings and submitted for publication in a peer-reviewed journal. NCT03141437; Pre-results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Clothing Flammability and Burn Injuries: Public Opinion Concerning an Overlooked, Preventable Public Health Problem.

PubMed

Frattaroli, Shannon; Spivak, Steven M; Pollack, Keshia M; Gielen, Andrea C; Salomon, Michele; Damant, Gordon H

2016-01-01

The objective of this study was to describe knowledge of clothing flammability risk, public support for clothing flammability warning labels, and stronger regulation to reduce the risk. As part of a national survey of homeowners about residential sprinkler systems, the authors included questions about clothing flammability. The authors used an online web panel to sample homeowners and descriptive methods to analyze the resulting data. The sample included 2333 homeowners. Knowledge of clothing flammability and government oversight of clothing flammability risk was low. Homeowners were evenly split about the effectiveness of current standards; however, when presented with clothing-related burn injury and death data, a majority (53%) supported stricter standards. Most homeowners (64%) supported warning labels and indicated that such labels would either have no effect on their purchasing decisions (64%) or be an incentive (24%) to purchase an item. Owners of sprinkler-equipped homes were more likely to support these interventions than owners of homes without sprinkler systems. Public knowledge about clothing flammability risks is low. Most homeowners supported clothing labels to inform consumers of this risk and increased government intervention to reduce the risk.

Adult patient decision-making regarding implantation of complex cardiac devices: a scoping review.

PubMed

Malecki-Ketchell, Alison; Marshall, Paul; Maclean, Joan

2017-10-01

Complex cardiac rhythm management device (CRMD) therapy provides an important treatment option for people at risk of sudden cardiac death. Despite the survival benefit, device implantation is associated with significant physical and psychosocial concerns presenting considerable challenges for the decision-making process surrounding CRMD implantation for patients and physicians. The purpose of this scoping review was to explore what is known about how adult (>16 years) patients make decisions regarding implantation of CRMD therapy. Published, peer reviewed, English language studies from 2000 to 2016 were identified in a search across eight healthcare databases. Eligible studies were concerned with patient decision-making for first time device implantation. Quality assessment was completed using the mixed methods appraisal tool for all studies meeting the inclusion criteria. The findings of eight qualitative and seven quantitative studies, including patients who accepted or declined primary or secondary sudden cardiac death prevention devices, were clustered into two themes: knowledge acquisition and the process of decision-making, exposing similarities and distinctions with the treatment decision-making literature. The review revealed some insight in to the way patients approach decision-making but also exposed a lack of clarity and research activity specific to CRMD patients. Further research is recommended to support the development and application of targeted decision support mechanisms.

78 FR 26069 - Top RX Pharmacy; Decision and Order

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-03

.... 1980) (upholding jury instruction that knowledge may be inferred from evidence that pharmacists... are clearly not issued for legitimate medical purposes, a pharmacist may not intentionally close his... make clear, inaction on the part of a pharmacist who fills a prescription can by, itself, support a...

A Method for Comparative Analysis of Recovery Potential in Impaired Waters Restoration Planning

EPA Science Inventory

Common decision support tools and a growing body of knowledge about ecological recovery can help inform and guide large state and federal restoration programs affecting thousands of impaired waters. Under the federal Clean Water Act (CWA), waters not meeting state Water Quality ...

LCIA framework and cross-cutting issues guidance within the UNEP/SETAC Life Cycle Initiative

EPA Science Inventory

Increasing needs for decision support and advances in scientific knowledge within life cycle assessment (LCA) led to substantial efforts to provide global guidance on environmental life cycle impact assessment (LCIA) indicators under the auspices of the UNEP-SETAC Life Cycle Init...

Representing causal knowledge in environmental policy interventions: Advantages and opportunities for qualitative influence diagram applications

EPA Science Inventory

This article develops and explores a methodology for using qualitative influence diagrams in environmental policy and management to support decision-making efforts that minimize risk and increase resiliency. Influence diagrams are representations of the conditional aspects of a p...

Scientific Literacy and Student Attitudes: Perspectives from PISA 2006 Science

ERIC Educational Resources Information Center

Bybee, Rodger; McCrae, Barry

2011-01-01

International assessments provide important knowledge about science education and help inform decisions about policies, programmes, and practices in participating countries. In 2006, science was the primary domain for the Programme for International Student Assessment (PISA), supported by the Organisation for Economic Cooperation and Development…

Leadership & Technology: What School Board Members Need To Know.

ERIC Educational Resources Information Center

Bailey, Gerald D.; And Others

Board members' role in technology implementation ranges from prompting development of technology plans to gathering community support for funding technology initiatives; they need substantial knowledge to enable them to ask the right questions, absorb new information, make good decisions, set appropriate policies, and lead confidently as…

Knowledge of and Attitudes Toward Evidence-Based Guidelines for and Against Clinical Preventive Services: Results from a National Survey.

PubMed

Lantz, Paula M; Evans, W Douglas; Mead, Holly; Alvarez, Carmen; Stewart, Lisa

2016-03-01

Both the underuse and overuse of clinical preventive services relative to evidence-based guidelines are a public health concern. Informed consumers are an important foundation of many components of the Affordable Care Act, including coverage mandates for proven clinical preventive services recommended by the US Preventive Services Task Force. Across sociodemographic groups, however, knowledge of and positive attitudes toward evidence-based guidelines for preventive care are extremely low. Given the demonstrated low levels of consumers' knowledge of and trust in guidelines, coupled with their strong preference for involvement in preventive care decisions, better education and decision-making support for evidence-based preventive services are greatly needed. Both the underuse and overuse of clinical preventive services are a serious public health problem. The goal of our study was to produce population-based national data that could assist in the design of communication strategies to increase knowledge of and positive attitudes toward evidence-based guidelines for clinical preventive services (including the US Preventive Services Task Force, USPSTF) and to reduce uncertainty among patients when guidelines change or are controversial. In late 2013 we implemented an Internet-based survey of a nationally representative sample of 2,529 adults via KnowledgePanel, a probability-based survey panel of approximately 60,000 adults, statistically representative of the US noninstitutionalized population. African Americans, Hispanics, and those with less than a high school education were oversampled. We then conducted descriptive statistics and multivariable logistic regression analysis to identify the prevalence of and sociodemographic characteristics associated with key knowledge and attitudinal variables. While 36.4% of adults reported knowing that the Affordable Care Act requires insurance companies to cover proven preventive services without cost sharing, only 7.7% had heard of the USPSTF. Approximately 1 in 3 (32.6%) reported trusting that a government task force would make fair guidelines for preventive services, and 38.2% believed that the government uses guidelines to ration health care. Most of the respondents endorsed the notion that research/scientific evidence and expert medical opinion are important for the creation of guidelines and that clinicians should follow guidelines based on evidence. But when presented with patient vignettes in which a physician made a guideline-based recommendation against a cancer-screening test, less than 10% believed that this recommendation alone, without further dialogue and/or the patient's own research, was sufficient to make such a decision. Given these demonstrated low levels of knowledge and mistrust regarding guidelines, coupled with a strong preference for shared decision making, better consumer education and decision supports for evidence-based guidelines for clinical preventive services are greatly needed. © 2016 Milbank Memorial Fund.

Decision-Making for Systemic Water Risks: Insights From a Participatory Risk Assessment Process in Vietnam

NASA Astrophysics Data System (ADS)

Wyrwoll, Paul R.; Grafton, R. Quentin; Daniell, Katherine A.; Chu, Hoang Long; Ringler, Claudia; Lien, Le Thi Ha; Khoi, Dang Kim; Do, Thang Nam; Tuan, Nguyen Do Anh

2018-03-01

Systemic threats to food-energy-environment-water systems require national policy responses. Yet complete control of these complex systems is impossible and attempts to mitigate systemic risks can generate unexpected feedback effects. Perverse outcomes from national policy can emerge from the diverse responses of decision-makers across different levels and scales of resource governance. Participatory risk assessment processes can help planners to understand subnational dynamics and ensure that policies do not undermine the resilience of social-ecological systems and infrastructure networks. Researchers can play an important role in participatory processes as both technical specialists and brokers of stakeholder knowledge on the feedbacks generated by systemic risks and policy decisions. Here, we evaluate the use of causal modeling and participatory risk assessment to develop national policy on systemic water risks. We present an application of the Risks and Options Assessment for Decision-Making (ROAD) process to a district of Vietnam where national agricultural water reforms are being piloted. The methods and results of this project provide general insights about how to support resilient decision-making, including the transfer of knowledge across administrative levels, identification of feedback effects, and the effective implementation of risk assessment processes.

From data mining rules to medical logical modules and medical advices.

PubMed

Gomoi, Valentin; Vida, Mihaela; Robu, Raul; Stoicu-Tivadar, Vasile; Bernad, Elena; Lupşe, Oana

2013-01-01

Using data mining in collaboration with Clinical Decision Support Systems adds new knowledge as support for medical diagnosis. The current work presents a tool which translates data mining rules supporting generation of medical advices to Arden Syntax formalism. The developed system was tested with data related to 2326 births that took place in 2010 at the Bega Obstetrics - Gynaecology Hospital, Timişoara. Based on processing these data, 14 medical rules regarding the Apgar score were generated and then translated in Arden Syntax language.

From data to wisdom: quality improvement strategies supporting large-scale implementation of evidence-based services.

PubMed

Daleiden, Eric L; Chorpita, Bruce F

2005-04-01

The Hawaii Department of Health Child and Adolescent Mental Health Division has explored various strategies to promote widespread use of empirical evidence to improve the quality of services and outcomes for youth. This article describes a core set of clinical decisions and how several general and local evidence bases may inform those decisions. Multiple quality improvement strategies are illustrated in the context of a model that outlines four phases of evidence: data, information, knowledge, and wisdom.

MAVEN-SA: Model-Based Automated Visualization for Enhanced Situation Awareness

DTIC Science & Technology

2005-11-01

34 methods. But historically, as arts evolve, these how to methods become systematized and codified (e.g. the development and refinement of color theory ...schema (as necessary) 3. Draw inferences from new knowledge to support decision making process 33 Visual language theory suggests that humans process...informed by theories of learning. Over the years, many types of software have been developed to support student learning. The various types of