7 resultados para Information Sharing

em Duke University


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This paper considers incentives to provide goods that are non-excludable along social or geographic links. We find, first, that networks can lead to specialization in public good provision. In every social network there is an equilibrium where some individuals contribute and others free ride. In many networks, this extreme is the only outcome. Second, specialization can benefit society as a whole. This outcome arises when contributors are linked, collectively, to many agents. Finally, a new link increases access to public goods, but reduces individual incentives to contribute. Hence, overall welfare can be higher when there are holes in a network. © 2006 Elsevier Inc. All rights reserved.

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BACKGROUND: Web-based decision aids are increasingly important in medical research and clinical care. However, few have been studied in an intensive care unit setting. The objectives of this study were to develop a Web-based decision aid for family members of patients receiving prolonged mechanical ventilation and to evaluate its usability and acceptability. METHODS: Using an iterative process involving 48 critical illness survivors, family surrogate decision makers, and intensivists, we developed a Web-based decision aid addressing goals of care preferences for surrogate decision makers of patients with prolonged mechanical ventilation that could be either administered by study staff or completed independently by family members (Development Phase). After piloting the decision aid among 13 surrogate decision makers and seven intensivists, we assessed the decision aid's usability in the Evaluation Phase among a cohort of 30 surrogate decision makers using the Systems Usability Scale (SUS). Acceptability was assessed using measures of satisfaction and preference for electronic Collaborative Decision Support (eCODES) versus the original printed decision aid. RESULTS: The final decision aid, termed 'electronic Collaborative Decision Support', provides a framework for shared decision making, elicits relevant values and preferences, incorporates clinical data to personalize prognostic estimates generated from the ProVent prediction model, generates a printable document summarizing the user's interaction with the decision aid, and can digitally archive each user session. Usability was excellent (mean SUS, 80 ± 10) overall, but lower among those 56 years and older (73 ± 7) versus those who were younger (84 ± 9); p = 0.03. A total of 93% of users reported a preference for electronic versus printed versions. CONCLUSIONS: The Web-based decision aid for ICU surrogate decision makers can facilitate highly individualized information sharing with excellent usability and acceptability. Decision aids that employ an electronic format such as eCODES represent a strategy that could enhance patient-clinician collaboration and decision making quality in intensive care.

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BACKGROUND: Child maltreatment is underreported in the United States and in North Carolina. In North Carolina and other states, mandatory reporting laws require various professionals to make reports, thereby helping to reduce underreporting of child maltreatment. This study aims to understand why emergency medical services (EMS) professionals may fail to report suspicions of maltreatment despite mandatory reporting policies. METHODS: A web-based, anonymous, voluntary survey of EMS professionals in North Carolina was used to assess knowledge of their agency's written protocols and potential reasons for underreporting suspicion of maltreatment (n=444). Results were based on descriptive statistics. Responses of line staff and leadership personnel were compared using chi-square analysis. RESULTS: Thirty-eight percent of respondents were unaware of their agency's written protocols regarding reporting of child maltreatment. Additionally, 25% of EMS professionals who knew of their agency's protocol incorrectly believed that the report should be filed by someone other than the person with firsthand knowledge of the suspected maltreatment. Leadership personnel generally understood reporting requirements better than did line staff. Respondents indicated that peers may fail to report maltreatment for several reasons: they believe another authority would file the report, including the hospital (52.3%) or law enforcement (27.7%); they are uncertain whether they had witnessed abuse (47.7%); and they are uncertain about what should be reported (41.4%). LIMITATIONS: This survey may not generalize to all EMS professionals in North Carolina. CONCLUSIONS: Training opportunities for EMS professionals that address proper identification and reporting of child maltreatment, as well as cross-agency information sharing, are warranted.

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Large urban jails have become a collection point for many persons with severe mental illness. Connections between jail and community mental health services are needed to assure in-jail care and to promote successful community living following release. This paper addresses this issue for 2855 individuals with severe mental illness who received community mental health services prior to jail detention in King County (Seattle), Washington over a 5-year time period using a unique linked administrative data source. Logistic regression was used to determine the probability that a detainee with severe mental illness received mental health services while in jail as a function of demographic and clinical characteristics. Overall, 70 % of persons with severe mental illness did receive in-jail mental health treatment. Small, but statistically significant sex and race differences were observed in who received treatment in the jail psychiatric unit or from the jail infirmary. Findings confirm the jail's central role in mental health treatment and emphasize the need for greater information sharing and collaboration with community mental health agencies to minimize jail use and to facilitate successful community reentry for detainees with severe mental illness.

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BACKGROUND: Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. METHODOLOGY: The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. PRINCIPAL FINDINGS: The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. CONCLUSIONS: Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.

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INTRODUCTION: The ability to reproducibly identify clinically equivalent patient populations is critical to the vision of learning health care systems that implement and evaluate evidence-based treatments. The use of common or semantically equivalent phenotype definitions across research and health care use cases will support this aim. Currently, there is no single consolidated repository for computable phenotype definitions, making it difficult to find all definitions that already exist, and also hindering the sharing of definitions between user groups. METHOD: Drawing from our experience in an academic medical center that supports a number of multisite research projects and quality improvement studies, we articulate a framework that will support the sharing of phenotype definitions across research and health care use cases, and highlight gaps and areas that need attention and collaborative solutions. FRAMEWORK: An infrastructure for re-using computable phenotype definitions and sharing experience across health care delivery and clinical research applications includes: access to a collection of existing phenotype definitions, information to evaluate their appropriateness for particular applications, a knowledge base of implementation guidance, supporting tools that are user-friendly and intuitive, and a willingness to use them. NEXT STEPS: We encourage prospective researchers and health administrators to re-use existing EHR-based condition definitions where appropriate and share their results with others to support a national culture of learning health care. There are a number of federally funded resources to support these activities, and research sponsors should encourage their use.

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Email exchange in 2013 between Kathryn Maxson (Duke) and Kris Wetterstrand (NHGRI), regarding country funding and other data for the HGP sequencing centers. Also includes the email request for such information, from NHGRI to the centers, in 2000, and the aggregate data collected.