Community-Engaged Data Science (CEDS): A Case Study of Working with Communities to Use Data to Inform Change.

IF 3.9 3区 医学 Q1 HEALTH POLICY & SERVICES Journal of Community Health Pub Date : 2024-12-01 Epub Date: 2024-07-03 DOI:10.1007/s10900-024-01377-y
Ramona G Olvera, Courtney Plagens, Sylvia Ellison, Kesla Klingler, Amy K Kuntz, Rachel P Chase
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Abstract

Data-informed decision making is a critical goal for many community-based public health research initiatives. However, community partners often encounter challenges when interacting with data. The Community-Engaged Data Science (CEDS) model offers a goal-oriented, iterative guide for communities to collaborate with research data scientists through data ambassadors. This study presents a case study of CEDS applied to research on the opioid epidemic in 18 counties in Ohio as part of the HEALing Communities Study (HCS). Data ambassadors provided a pivotal role in empowering community coalitions to translate data into action using key steps of CEDS which included: data landscapes identifying available data in the community; data action plans from logic models based on community data needs and gaps of data; data collection/sharing agreements; and data systems including portals and dashboards. Throughout the CEDS process, data ambassadors emphasized sustainable data workflows, supporting continued data engagement beyond the HCS. The implementation of CEDS in Ohio underscored the importance of relationship building, timing of implementation, understanding communities' data preferences, and flexibility when working with communities. Researchers should consider implementing CEDS and integrating a data ambassador in community-based research to enhance community data engagement and drive data-informed interventions to improve public health outcomes.

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社区参与的数据科学(CEDS):与社区合作利用数据促进变革的案例研究。
基于数据的决策是许多社区公共卫生研究计划的重要目标。然而,社区合作伙伴在与数据互动时往往会遇到挑战。社区参与数据科学(CEDS)模式为社区通过数据大使与研究数据科学家合作提供了以目标为导向的迭代指南。本研究介绍了将 CEDS 应用于俄亥俄州 18 个县的阿片类药物流行病研究的案例研究,这是 HEALing 社区研究 (HCS) 的一部分。数据大使在授权社区联盟利用 CEDS 的关键步骤将数据转化为行动方面发挥了关键作用,这些步骤包括:确定社区可用数据的数据景观;基于社区数据需求和数据缺口的逻辑模型的数据行动计划;数据收集/共享协议;以及包括门户网站和仪表板在内的数据系统。在整个 CEDS 过程中,数据大使强调可持续的数据工作流程,支持 HCS 之后的持续数据参与。俄亥俄州 CEDS 的实施强调了关系建设、实施时机、了解社区的数据偏好以及与社区合作时灵活性的重要性。研究人员应考虑实施 CEDS,并将数据大使纳入以社区为基础的研究中,以加强社区数据参与,并推动以数据为依据的干预措施,从而改善公共卫生成果。
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来源期刊
CiteScore
10.80
自引率
1.70%
发文量
113
期刊介绍: The Journal of Community Health is a peer-reviewed publication that offers original articles on research, teaching, and the practice of community health and public health. Coverage includes public health, epidemiology, preventive medicine, health promotion, disease prevention, environmental and occupational health, health policy and management, and health disparities. The Journal does not publish articles on clinical medicine. Serving as a forum for the exchange of ideas, the Journal features articles on research that serve the educational needs of public and community health personnel.
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