Powers John P, Carey Timothy S, Hargrove Taylor W, Limburg Aubrey, Udalova Victoria, Shaheen Amy, Bowers Robert, Pfaff Emily R, Entwisle Barbara
North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill, Chapel Hill, USA.
Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, USA.
J Gen Intern Med. 2025 Sep 17. doi: 10.1007/s11606-025-09867-y.
Recent years have seen an increase in the number and size of integrated health care delivery systems in the USA. The size and sophistication of these systems afford a greater focus on population health, leading to a fundamental question: How do the patients of these systems compare to the underlying regional populations that the systems serve?
To demonstrate an approach to answering this question for a large public integrated delivery system, with a particular focus on neighborhood social determinants of health (SDOH).
We present a descriptive, graphical comparison of the neighborhood characteristics of UNC Health patients and the overall population of North Carolina (NC).
We leveraged electronic health record data from a 5-year period for patients at UNC Health, an integrated health care delivery system focused on serving the NC population. Estimates for the NC population were obtained from the American Community Survey (ACS).
Measures included neighborhood SDOH indices for NC census tracts derived from ACS data as well as race and ethnicity.
Overall, patients were more concentrated in neighborhoods with the least and greatest disadvantage. However, the density patterns of specific racial and ethnic groups across neighborhood SDOH scores were similar between the patients and NC population.
Using a large, public integrated health care delivery system, we illustrate an approach for comparing the demographic and neighborhood characteristics of the patients of such a system and its underlying regional population using freely available data and open-source software. Our findings indicate many similar patterns between the health care system patients and regional population, but overall higher concentrations of patients in neighborhoods with the least and greatest disadvantage.
近年来，美国综合医疗服务体系的数量和规模都有所增加。这些体系的规模和复杂性使得人们更加关注人群健康，从而引发了一个基本问题：这些体系中的患者与它们所服务的潜在区域人群相比如何？
为一个大型公共综合医疗服务体系展示一种回答这个问题的方法，特别关注邻里健康社会决定因素（SDOH）。
我们对北卡罗来纳大学医疗系统（UNC Health）患者的邻里特征与北卡罗来纳州（NC）的总体人群进行了描述性的图形比较。
我们利用了UNC Health患者五年期间的电子健康记录数据，UNC Health是一个专注于为北卡罗来纳州人群服务的综合医疗服务体系。北卡罗来纳州人群的估计数据来自美国社区调查（ACS）。
指标包括从ACS数据得出的北卡罗来纳州人口普查区的邻里SDOH指数以及种族和民族。
总体而言，患者更多地集中在劣势最小和最大的社区。然而，患者和北卡罗来纳州人群在邻里SDOH评分中特定种族和民族群体的密度模式相似。
通过一个大型公共综合医疗服务体系，我们展示了一种使用免费可得数据和开源软件来比较此类体系患者及其潜在区域人群的人口统计学和邻里特征的方法。我们的研究结果表明，医疗系统患者和区域人群之间有许多相似模式，但总体上患者在劣势最小和最大的社区中集中度更高。
