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      Willingness to Participate in Health Information Networks with Diverse Data Use: Evaluating Public Perspectives

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          Abstract

          Introduction:

          Health information generated by health care encounters, research enterprises, and public health is increasingly interoperable and shareable across uses and users. This paper examines the US public’s willingness to be a part of multi-user health information networks and identifies factors associated with that willingness.

          Methods:

          Using a probability-based sample (n = 890), we examined the univariable and multivariable relationships between willingness to participate in health information networks and demographic factors, trust, altruism, beliefs about the public’s ethical obligation to participate in research, privacy, medical deception, and policy and governance using linear regression modeling.

          Results:

          Willingness to be a part of a multi-user network that includes health care providers, mental health, social services, research, or quality improvement is low (26 percent–7.4 percent, depending on the user). Using stepwise regression, we identified a model that explained 42.6 percent of the variability in willingness to participate and included nine statistically significant factors associated with the outcome: Trust in the health system, confidence in policy, the belief that people have an obligation to participate in research, the belief that health researchers are accountable for conducting ethical research, the desire to give permission, education, concerns about insurance, privacy, and preference for notification.

          Discussion:

          Our results suggest willingness to be a part of multi-user data networks is low, but that attention to governance may increase willingness. Building trust to enable acceptance of multi-use data networks will require a commitment to aligning data access practices with the expectations of the people whose data is being used.

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          Most cited references33

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          A systematic review of barriers to data sharing in public health

          Background In the current information age, the use of data has become essential for decision making in public health at the local, national, and global level. Despite a global commitment to the use and sharing of public health data, this can be challenging in reality. No systematic framework or global operational guidelines have been created for data sharing in public health. Barriers at different levels have limited data sharing but have only been anecdotally discussed or in the context of specific case studies. Incomplete systematic evidence on the scope and variety of these barriers has limited opportunities to maximize the value and use of public health data for science and policy. Methods We conducted a systematic literature review of potential barriers to public health data sharing. Documents that described barriers to sharing of routinely collected public health data were eligible for inclusion and reviewed independently by a team of experts. We grouped identified barriers in a taxonomy for a focused international dialogue on solutions. Results Twenty potential barriers were identified and classified in six categories: technical, motivational, economic, political, legal and ethical. The first three categories are deeply rooted in well-known challenges of health information systems for which structural solutions have yet to be found; the last three have solutions that lie in an international dialogue aimed at generating consensus on policies and instruments for data sharing. Conclusions The simultaneous effect of multiple interacting barriers ranging from technical to intangible issues has greatly complicated advances in public health data sharing. A systematic framework of barriers to data sharing in public health will be essential to accelerate the use of valuable information for the global good. Electronic supplementary material The online version of this article (doi:10.1186/1471-2458-14-1144) contains supplementary material, which is available to authorized users.
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            Achieving a nationwide learning health system.

            We outline the fundamental properties of a highly participatory rapid learning system that can be developed in part from meaningful use of electronic health records (EHRs). Future widespread adoption of EHRs will make increasing amounts of medical information available in computable form. Secured and trusted use of these data, beyond their original purpose of supporting the health care of individual patients, can speed the progression of knowledge from the laboratory bench to the patient's bedside and provide a cornerstone for health care reform.
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              Medical conspiracy theories and health behaviors in the United States.

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                Author and article information

                Contributors
                Journal
                EGEMS (Wash DC)
                EGEMS (Wash DC)
                2327-9214
                eGEMs
                Ubiquity Press
                2327-9214
                25 July 2019
                2019
                : 7
                : 1
                : 33
                Affiliations
                [1 ]University of Michigan Medical School, Department of Learning Health Sciences, US
                [2 ]University of Michigan School of Public Health, Department of Health Management and Policy, US
                [3 ]University of Michigan School of Information and Michigan Institute for Clinical and Health Research, US
                [4 ]University of Chicago Medicine, US
                [5 ]University of Michigan School of Information, College of Engineering, EECS, and Medical School, Department of Learning Health Systems, US
                [6 ]University of Michigan School of Public Health, Department of Epidemiology, US
                Author notes
                Corresponding author: Jodyn Platt ( jeplatt@ 123456umich.edu )
                Author information
                http://orcid.org/0000-0003-4902-4903
                Article
                10.5334/egems.288
                6659576
                31367650
                c12e483f-3071-4dd7-b789-31feb925c5f2
                Copyright: © 2019 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 July 2018
                : 16 May 2019
                Categories
                Empirical Research

                health data networks,public opinion,trust,learning health systems

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