以解决方案为基础建立数据共享伙伴关系。

Sarah E Wiehe, Marc B Rosenman, David Chartash, Elaine R Lipscomb, Tammie L Nelson, Lauren A Magee, J Dennis Fortenberry, Matthew C Aalsma
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引用次数: 11

摘要

虽然研究人员认识到共享不同的数据可以改善人口健康,但障碍(技术、动机、经济、政治、法律和伦理)限制了进展。在本文中,我们旨在增强van Panhuis等人的数据共享障碍框架;我们提出了一个互补的基于解决方案的数据共享过程,以鼓励新兴和成熟的研究人员,无论是否在学术界,参与数据共享伙伴关系。主要组件的简要描述:我们以三种方式增强van Panhuis等人的框架。首先,我们在组织(例如,刑事司法机构)中确定适当的利益相关者,与他们一起解决每一类障碍。其次,我们提供了一个具有代表性的样本,说明我们在与刑事司法机构、地方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具体挑战。第三,也是最重要的一点,我们提出了针对每一类障碍的成功解决方案。我们将我们的解决方案分为五个核心领域,以跨越障碍和利益相关者群体:准备,明确沟通,资金/支持,非货币性利益和监管保证。我们基于解决方案的流程模型是对增强框架的补充。流程模型的一个重要特征是支撑它的循环迭代过程。通常,与新的数据共享合作伙伴组织的互动始于领导团队,并进展到数据管理和法律团队;然而,这个过程并不总是线性的。结论和后续步骤:数据共享是人口健康研究的有力工具,但重大障碍阻碍了这种伙伴关系。然而,通过追求以社区为基础的参与性研究原则,包括伙伴关系的参与、发展和维护,我们克服了van Panhuis等人框架中确定的障碍,并通过各种数据共享伙伴关系取得了成功。将来,系统地研究数据共享伙伴关系,以阐明基于解决方案的方法的哪些要素对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,因为它既与障碍有关,也与解决方案的潜在可行性有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Solutions-Based Approach to Building Data-Sharing Partnerships.

A Solutions-Based Approach to Building Data-Sharing Partnerships.

A Solutions-Based Approach to Building Data-Sharing Partnerships.

A Solutions-Based Approach to Building Data-Sharing Partnerships.

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.

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