Author Affiliations: Department of Behavioral and Community Health Sciences, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania (Mss Liu, Boak, and Eggleston and Dr Elias); and Quality Insights, Inc, Charleston, West Virginia (Mss Rodi and Biscardi).
J Public Health Manag Pract. 2024;30:S39-S45. doi: 10.1097/PHH.0000000000001900. Epub 2024 Jun 12.
Pennsylvanians' health is influenced by numerous social determinants of health (SDOH). Integrating SDOH data into electronic health records (EHRs) is critical to identifying health disparities, informing public health policies, and devising interventions. Nevertheless, challenges remain in its implementation within clinical settings. In 2018, the Pennsylvania Department of Health (PADOH) received the Centers for Disease Control and Prevention's DP18-1815 "Improving the Health of Americans Through Prevention and Management of Diabetes and Heart Disease and Stroke" grant to strengthen SDOH data integration in Pennsylvania practices.
Quality Insights was contracted by PADOH to provide training tailored to each practice's readiness, an International Classification of Diseases, Tenth Revision (ICD-10) guide for SDOH, Continuing Medical Education on SDOH topics, and introduced the PRAPARE toolkit to streamline SDOH data integration and address disparities. Dissemination efforts included a podcast highlighting success stories and lessons learned from practices. From 2019 to 2022, Quality Insights and the University of Pittsburgh Evaluation Institute for Public Health (Pitt evaluation team) executed a mixed-methods evaluation.
During 2019-2022, Quality Insights supported 100 Pennsylvania practices in integrating SDOH data into EHR systems. Before COVID-19, 82.8% actively collected SDOH data, predominantly using PRAPARE tool (62.7%) and SDOH ICD-10 codes (80.4%). Amidst COVID-19, these statistics shifted to 65.1%, 45.2%, and 42.7%, respectively. Notably, the pandemic highlighted the importance of SDOH assessment and catalyzed some practices' utilization of SDOH data. Progress was evident among practices, with additional contribution to other DP18-1815 objectives. The main challenge was the variable understanding, utilization, and capability of handling SDOH data across practices. Effective strategies involved adaptable EHR systems, persistent efforts by Quality Insights, and the presence of change champions within practices.
The COVID-19 pandemic strained staffing in many practices, impeding SDOH data integration into EHRs. Addressing the diverse understanding and use of SDOH data requires standardized training and procedures. Customized support and sustained engagement by facilitating organizations are paramount in ensuring practices' efficient SDOH data collection and integration.
宾夕法尼亚州民众的健康受到众多健康社会决定因素（SDOH）的影响。将 SDOH 数据整合到电子健康记录（EHR）中对于识别健康差距、为公共卫生政策提供信息以及设计干预措施至关重要。然而，在临床环境中实施仍然存在挑战。2018 年，宾夕法尼亚州卫生部（PADOH）获得了疾病控制与预防中心的 DP18-1815“通过预防和管理糖尿病以及心脏病和中风来改善美国人的健康”赠款，以加强宾夕法尼亚州实践中的 SDOH 数据整合。
质量洞察公司（Quality Insights）受 PADOH 委托，根据每个实践的准备情况提供定制培训，提供 SDOH 的国际疾病分类，第十版（ICD-10）指南，关于 SDOH 主题的继续医学教育，并引入 PRAPARE 工具包来简化 SDOH 数据整合并解决差异问题。传播工作包括一个播客，重点介绍实践中的成功案例和经验教训。从 2019 年到 2022 年，质量洞察公司和匹兹堡大学公共卫生评估研究所（Pitt 评估团队）执行了一项混合方法评估。
在 2019-2022 年期间，质量洞察公司支持宾夕法尼亚州的 100 家实践将 SDOH 数据整合到 EHR 系统中。在 COVID-19 之前，82.8%的实践积极收集 SDOH 数据，主要使用 PRAPARE 工具（62.7%）和 SDOH ICD-10 代码（80.4%）。在 COVID-19 期间，这些数据分别变为 65.1%、45.2%和 42.7%。值得注意的是，大流行凸显了 SDOH 评估的重要性，并促使一些实践利用 SDOH 数据。实践中取得了进展，对 DP18-1815 的其他目标也有额外贡献。主要挑战是实践之间对 SDOH 数据的理解、利用和处理能力存在差异。有效的策略包括适应性强的 EHR 系统、质量洞察公司的持续努力以及实践内部变革推动者的存在。
COVID-19 大流行使许多实践的人员配备紧张，阻碍了 SDOH 数据向 EHR 的整合。解决 SDOH 数据的多样性理解和使用问题需要标准化的培训和程序。促进组织的定制支持和持续参与对于确保实践高效地收集和整合 SDOH 数据至关重要。
