# Caring for Communities: Comparing Health Care System Patient Populations to Regional Populations

## TL;DR

This paper compares the patient population of UNC Health to North Carolina's overall population, focusing on neighborhood characteristics and social determinants of health.

## Contribution

The study introduces a descriptive, graphical approach using open-source tools to compare health system patients with regional populations.

## Key findings

- Patients were more concentrated in neighborhoods with the least and greatest disadvantage.
- Racial and ethnic group patterns across SDOH scores were similar between patients and the general population.
- The approach uses freely available data and open-source software for demographic and neighborhood comparisons.

## Abstract

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.

The online version contains supplementary material available at 10.1007/s11606-025-09867-y.