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Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders.

ABSTRACT: There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy analysis with experts, interviews with institutional leaders, and patient focus groups. This approach is illustrated with an example from the Scalable National Network for Effectiveness Research, which resulted in 91 requirements. These requirements were analyzed against the Fair Information Practice Principles (FIPPs) and Health Insurance Portability and Accountability Act (HIPAA) protected versus non-protected health information. The requirements addressed all FIPPs, showing how a DRN's technical infrastructure is able to fulfill HIPAA regulations, protect privacy, and provide a trustworthy platform for research.

SUBMITTER: Kim KK

PROVIDER: S-EPMC4078279 | biostudies-literature | 2014 Jul-Aug

REPOSITORIES: biostudies-literature

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Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders.

Kim Katherine K KK Browe Dennis K DK Logan Holly C HC Holm Roberta R Hack Lori L Ohno-Machado Lucila L

Journal of the American Medical Informatics Association : JAMIA 20131203 4

There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy ...[more]

PMID: 24302285

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Project description:BackgroundEven though research integrity (RI) training programs have been developed in the last decades, it is argued that current training practices are not always able to increase RI-related awareness within the scientific community. Defining and understanding the capacities and lacunas of existing RI training are becoming extremely important for developing up-to-date educational practices to tackle present-day challenges. Recommendations on how to implement RI education have been primarily made by selected people with specific RI-related expertise. Those recommendations were developed mainly without consulting a broader audience with no specific RI expertise. Moreover, the academic literature lacks qualitative studies on RI training practices. For these reasons, performing in-depth focus groups with non-RI expert stakeholders are of a primary necessity to understand and outline how RI education should be implemented.MethodsIn this qualitative analysis, different focus groups were conducted to examine stakeholders' perspectives on RI training practices. Five stakeholders' groups, namely publishers and peer reviewers, researchers on RI, RI trainers, PhDs and postdoctoral researchers, and research administrators working within academia, have been identified to have a broader overview of state of the art.ResultsA total of 39 participants participated in five focus group sessions. Eight training-related themes were highlighted during the focus group discussions. The training goals, timing and frequency, customisation, format and teaching approach, mentoring, compulsoriness, certification and evaluation, and RI-related responsibilities were discussed. Although confirming what was already proposed by research integrity experts in terms of timing, frequency, duration, and target audience in organising RI education, participants proposed other possible implementations strategies concerning the teaching approach, researchers' obligations, and development an evaluation-certification system.ConclusionsThis research aims to be a starting point for a better understanding of necessary, definitive, and consistent ways of structuring RI education. The research gives an overview of what has to be considered needed in planning RI training sessions regarding objectives, organisation, and teaching approach.

Project description:Introduction: Health research is gradually embracing a more collectivist approach, fueled by a new movement of open science, data sharing and collaborative partnerships. However, the existence of systemic contradictions hinders the sharing of health data and such collectivist endeavor. Therefore, this qualitative study explores these systemic barriers to a fair sharing of health data from the perspectives of Swiss stakeholders. Methods: Purposive and snowball sampling were used to recruit 48 experts active in the Swiss healthcare domain, from the research/policy-making field and those having a high position in a health data enterprise (e.g., health register, hospital IT data infrastructure or a national health data initiative). Semi-structured interviews were then conducted, audio-recorded, verbatim transcribed with identifying information removed to guarantee the anonymity of participants. A theoretical thematic analysis was then carried out to identify themes and subthemes related to the topic of systemic fairness for sharing health data. Results: Two themes related to the topic of systemic fairness for sharing health data were identified, namely (i) the hypercompetitive environment and (ii) the legal uncertainty blocking data sharing. The theme, hypercompetitive environment was further divided into two subthemes, (i) systemic contradictions to fair data sharing and the (ii) need of fair systemic attribution mechanisms. Discussion: From the perspectives of Swiss stakeholders, hypercompetition in the Swiss academic system is hindering the sharing of health data for secondary research purposes, with the downside effect of influencing researchers to embrace individualism for career opportunities, thereby opposing the data sharing movement. In addition, there was a perceived sense of legal uncertainty from legislations governing the sharing of health data, which adds unreasonable burdens on individual researchers, who are often unequipped to deal with such facets of their data sharing activities.

Dataset Information

Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders.

Publications

Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders.

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