Model / Framework

A SolutionsBased Approach to Building DataSharing Partnerships

Authors: {'first_name': 'Sarah E.', 'last_name': 'Wiehe'},{'first_name': 'Marc B.', 'last_name': 'Rosenman'},{'first_name': 'David', 'last_name': 'Chartash'},{'first_name': 'Elaine R.', 'last_name': 'Lipscomb'},{'first_name': 'Tammie L.', 'last_name': 'Nelson'},{'first_name': 'Lauren A.', 'last_name': 'Magee'},{'first_name': 'J. Dennis', 'last_name': 'Fortenberry'},{'first_name': 'Matthew C.', 'last_name': 'Aalsma'}


Introduction: Although researchers recognize that sharing disparate data can improve population health, barriers (technical, motivational, economic, political, legal, and ethical) limit progress. In this paper, we aim to enhance the van Panhuis et al. framework of barriers to data sharing; we present a complementary solutions-based data-sharing process in order to encourage both emerging and established researchers, whether or not in academia, to engage in data-sharing partnerships.

Brief Description of Major Components: We enhance the van Panhuis et al. framework in three ways. First, we identify the appropriate stakeholder(s) within an organization (e.g., criminal justice agency) with whom to engage in addressing each category of barriers. Second, we provide a representative sample of specific challenges that we have faced in our data-sharing partnerships with criminal justice agencies, local clinical systems, and public health. Third, and most importantly, we suggest solutions we have found successful for each category of barriers. We grouped our solutions into five core areas that cut across the barriers as well as stakeholder groups: Preparation, Clear Communication, Funding/Support, Non-Monetary Benefits, and Regulatory Assurances.

Our solutions-based process model is complementary to the enhanced framework. An important feature of the process model is the cyclical, iterative process that undergirds it. Usually, interactions with new data-sharing partner organizations begin with the leadership team and progress to both the data management and legal teams; however, the process is not always linear.

Conclusions and Next Steps: Data sharing is a powerful tool in population health research, but significant barriers hinder such partnerships. Nevertheless, by aspiring to community-based participatory research principles, including partnership engagement, development, and maintenance, we have overcome barriers identified in the van Panhuis et al. framework and have achieved success with various data-sharing partnerships.

In the future, systematically studying data-sharing partnerships to clarify which elements of a solutions-based approach are essential for successful partnerships may be helpful to academic and non-academic researchers. The organizational climate is certainly a factor worth studying also because it relates both to barriers and to the potential workability of solutions.

Keywords: data sharingpartnershipspopulation healthelectronic health records 

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