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Research Oversight Statement Highlights. Sarah Greene Health Care Systems Research Network Russell Rothman Vanderbilt University. Post-It Note Prioritization Ritual. Ethical Barriers. Cultural Barriers. Operational Barriers. Regulatory Barriers. Financial Barriers.
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Research Oversight Statement Highlights Sarah Greene Health Care Systems Research Network Russell Rothman Vanderbilt University
Post-It Note Prioritization Ritual Ethical Barriers Cultural Barriers Operational Barriers Regulatory Barriers Financial Barriers
Prioritized Barriers • Lack of shared principles regarding data ownership, stewardship, governance, rights, and responsibilities. • Heterogeneity in beliefs among patients, clinicians, and researchers about whether data should be freely shared or not. • Uncertainty about potential future uses of data, and accompanying concerns about consequences arising from inappropriate/unauthorized use • Variability across institutions and states in their interpretation of regulations and responsibilities. • Operational challenges including uneven data quality, the cost to procure data, and the lag time between when data is collected and when it is available for use by researchers.
Near Term Solutions • Lack of shared principles regarding data ownership, stewardship, governance, rights, and responsibilities. • Convene high-impact task force or similar panel to create a consensus statement – with signatories – to publicly affirm a set of principles and commitments on the collective benefits of data as a public good • Establish a federal commission to reach agreement about data ownership and data protections Data for the public good
Near Term Solutions (continued) Heterogeneity in beliefs among patients, clinicians, and researchers about whether or not data should be freely shared • Gain deeper understanding of where these beliefs coincide and conflict via national survey(s) and literature review(s) • Publish high-profile journal commentary describing a model policy that incorporates a commitment to openness and sharing, enabling others to compare existing policies with the model policy to improve consistency.
Near Term Solutions (continued) Uncertainty about potential future uses of data, and accompanying concerns about consequences arising from inappropriate or unauthorized use • Improve approaches to communicating with patients in plain language about how data are collected and used • Clarify regulations & penalties for unauthorized data sharing, applying insights from other countries and industries as they either addressed or failed to address data sharing issues Image credit: OpenDataWatch.com
Near Term Solutions (continued) Variability across institutions and states in their interpretation of regulations and responsibilities • Collectively, state governments and organization should press for clearer federal guidance on data sharing policies • HHS or ONC should create a taxonomy of learning activities (research, QI, etc.) with associated legal/regulatory considerations • Convene IRB chairs, regulatory officials and thought leaders to draft guidance and case studies for IRBs and compliance officers with the goal of reducing variability in the interpretation of data use/data sharing regulations
Near Term Solutions (continued) Operational challenges, including uneven data quality, the cost to procure data, and the lag between when data is collected and when it is available for use by researchers • Explore creation of a repository with a curated list of datasets and related metadata to encourage reuse and reduce lag times • Engage ONC and others to push greater standardization of data in electronic health records (EHRs) • Identify and accelerate incentives that encourage data sharing by researchers and other data holders