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Caring for Communities: Comparing Health Care System Patient Populations to Regional Populations.
John P Powers1, Timothy S Carey2, Taylor W Hargrove3
1North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill, Chapel Hill, USA. jppowers@unc.edu.
Integrated health systems serve patients in neighborhoods with both the least and most disadvantage. Comparing UNC Health patients to North Carolina
Area of Science:
- Health Services Research
- Population Health Management
- Health Equity Studies
Background:
- Integrated health care delivery systems are growing in the USA.
- This expansion raises questions about how patient populations compare to the general population served.
- Focusing on neighborhood social determinants of health (SDOH) is crucial for understanding disparities.
Purpose of the Study:
- To develop and demonstrate a method for comparing patient demographics and neighborhood characteristics.
- To analyze the neighborhood social determinants of health (SDOH) of patients within a large public health system.
- To compare these patient characteristics against the broader regional population.
Main Methods:
- Descriptive and graphical analysis comparing UNC Health patients and the North Carolina (NC) population.
- Utilized electronic health record data (5-year period) for patients.
- Employed American Community Survey (ACS) data for neighborhood SDOH indices and demographic comparisons.
Main Results:
- Patients were more concentrated in neighborhoods at the extremes of social disadvantage.
- However, racial and ethnic group distributions across SDOH scores were similar between patients and the NC population.
- This suggests nuanced patterns in how different demographic groups access care within the system.
Conclusions:
- An effective approach was demonstrated for comparing health system patients to the regional population using accessible data.
- Findings highlight similarities in demographic and neighborhood patterns but also point to higher patient concentrations in highly disadvantaged areas.
- This methodology can inform population health strategies and resource allocation within integrated health systems.
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