New EHR-based multimorbidity index for diverse populations across the lifespan: development, validation, and application

项目摘要/摘要 几乎所有的美国成年人都会在晚年患上多病(多种慢性病并存) 成人期。后遗症是巨大的：易患急性疾病、疾病恶化、住院、 残疾、与健康相关的生活质量差和死亡率。尽管如此，没有可行的、以患者为中心的 电子健康记录(EHR)中多病的衡量标准，包括全面的 根据它们对社区成年人身体功能的影响而产生的情况，因此广泛地 适用于一般人群。这些工具的缺乏阻碍了开发的系统性努力 对多发病患者的有效干预。为了弥合这些差距，这项提案旨在发展和 验证稳健、临床相关、易于获得的基于EHR的多病合并症加权指数(EMWI) 使用电子病历数据准确确定疾病的存在，适用于 寿命。中心假设是一个综合的多发病指数，它基于以下条件对病情进行加权 它们对身体功能的影响可以更准确地量化多发性疾病，并提供更好的模型拟合 预测关键的健康结果，而不是以前的措施。这一假设得到了我们初步研究的有力支持 使用大型全国调查和与调查相关的索赔数据的结果，在这些数据中，我们严格制定和 验证了91种慢性病的综合集合，根据它们对身体的平均影响进行加权 在疾病的生命过程中发挥作用，从而将疾病负担和身体功能结合到一个 适用于普通人群的具有临床意义的措施。作为多发性疾病的变革性步骤 使用电子病历数据衡量患者护理、人群健康和研究，该团队的目标是1)改进 通过更准确地确定疾病病例并将这些病例与已验证的病例合并来测量多病 身体功能疾病权重，以创建适用于不同人群的以患者为中心的新eMWI； 2)通过与关键临床结果的关联来评估eMWI的有效性：多病进展， 住院和死亡率；以及3)通过以下方式测试eMWI对国家人口健康和政策的适用性 应用它来评估接种疫苗和未接种疫苗的成年人患严重和致命新冠肺炎的风险 关于他们的多发病。这项研究使用了来自加州6个医疗系统(600万英镑)的大量、多样化的电子病历数据 成年人)与人口普查数据有独特的数据链接，以及最大、最具全国代表性的国家 COVID Cohort Collaborative(N3C)数据集(&gt；500万例)。结果将产生一个新的，经过验证的， 以患者为中心的EHR数据多病指数-eMWI-帮助指导临床决策，人群- 针对不同人群的健康管理、政策和研究。该团队预计，eMWI可以直接 影响多发病和功能状态影响日常治疗的未来实践和结果 决定和结果。EMWI将以标准化代码形式随时提供给其他电子病历数据。总的来说， 这些结果将改善患有多发病的不同老年成年人的护理质量和健康结果。

Project Summary / Abstract Virtually all U.S. adults will develop multimorbidity (coexistence of multiple chronic conditions) by late adulthood. The sequelae are substantial: vulnerability to acute illness, disease exacerbation, hospitalization, disability, poor health-related quality of life, and mortality. Despite this, there are no viable, patient-centered measures for multimorbidity in the electronic health record (EHR) that include a comprehensive inventory of conditions based on their impacts on physical functioning in community-dwelling adults and are thus broadly applicable for the general population. The absence of such tools impedes systematic efforts to develop effective interventions for patients with multimorbidity. To bridge these gaps, this proposal aims to develop and validate a robust, clinically relevant, readily-available EHR-based multimorbidity-weighted index (eMWI) that accurately ascertains disease presence using EHR data and is applicable for diverse populations across the lifespan. The central hypothesis is that a comprehensive multimorbidity index that weights conditions based on their impacts on physical functioning can more precisely quantify multimorbidity and provide a better model fit to predict key health outcomes than prior measures. This hypothesis is strongly supported by our preliminary results using large national surveys and survey-linked claims data, in which we rigorously developed and validated a comprehensive set of 91 chronic conditions weighted by their average impacts on physical functioning over the disease life course, thus incorporating illness burden and physical functioning into a clinically meaningful measure applicable for the general population. As a transformative step for multimorbidity measurement in patient care, population health, and research using EHR data, the team aims to 1) improve multimorbidity measurement by more accurately ascertaining disease cases, and merging these with validated physical functioning disease weights to create a new patient-centered eMWI applicable to diverse populations; 2) assess the validity of eMWI via its association with key clinical outcomes: multimorbidity progression, hospitalization, and mortality; and 3) test the applicability of eMWI to national population health and policy by applying it to evaluate the risk of severe and fatal COVID-19 among vaccinated vs. unvaccinated adults based on their multimorbidity. This study uses large, diverse EHR data from 6 California health systems (>6 million adults) with unique data linkages to census data, and the largest, most nationally-representative National COVID Cohort Collaborative (N3C) dataset (>5 million COVID cases). The results will yield a new, validated, patient-centered multimorbidity index for EHR data – the eMWI – to help guide clinical decisions, population- health management, policy, and research for diverse populations. The team anticipates that eMWI can directly impact future practice and outcomes in which multimorbidity and functional status impact everyday treatment decisions and outcomes. eMWI will be readily available in standardized code for other EHR data. Overall, these results will improve the quality of care and health outcomes for diverse, aging adults with multimorbidity.