Wiehe Sarah E, Rosenman Marc B, Chartash David, Lipscomb Elaine R, Nelson Tammie L, Magee Lauren A, Fortenberry J Dennis, Aalsma Matthew C
Indiana University School of Medicine, US.
Ann and Robert H. Lurie Children's Hospital of Chicago, US.
EGEMS (Wash DC). 2018 Aug 22;6(1):20. doi: 10.5334/egems.236.
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 . 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.
We enhance the van Panhuis . 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.
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 . 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.
尽管研究人员认识到共享不同的数据可以改善人群健康，但障碍（技术、动机、经济、政治、法律和伦理方面）限制了进展。在本文中，我们旨在完善范·潘胡伊斯的数据共享障碍框架；我们提出一个基于解决方案的数据共享补充流程，以鼓励新兴研究人员和资深研究人员（无论是否在学术界）参与数据共享伙伴关系。
我们通过三种方式完善范·潘胡伊斯的框架。首先，我们确定组织（如刑事司法机构）内与解决各类障碍相关的合适利益相关者。其次，我们提供了在与刑事司法机构、当地临床系统和公共卫生机构的数据共享伙伴关系中所面临的特定挑战的代表性样本。第三，也是最重要的，我们提出了针对各类障碍已被证明成功的解决方案。我们将解决方案分为五个核心领域，这些领域跨越障碍以及利益相关者群体：准备、清晰沟通、资金/支持、非货币利益和监管保障。我们基于解决方案的流程模型是对完善框架的补充。该流程模型的一个重要特征是支撑它的循环迭代过程。通常，与新的数据共享伙伴组织的互动始于领导团队，然后推进到数据管理团队和法律团队；然而，这个过程并非总是线性的。
数据共享是人群健康研究中的一个有力工具，但重大障碍阻碍了此类伙伴关系。尽管如此，通过秉持基于社区的参与性研究原则，包括伙伴关系的参与、发展和维护，我们克服了范·潘胡伊斯框架中所确定的障碍，并在各种数据共享伙伴关系中取得了成功。未来，系统地研究数据共享伙伴关系，以明确基于解决方案的方法的哪些要素对于成功的伙伴关系至关重要，这可能对学术和非学术研究人员有所帮助。组织氛围当然也是一个值得研究的因素，因为它既与障碍相关，也与解决方案的潜在可行性相关。
