Evaluating Population Coverage in a Regional Distributed Data Network: Implications for Electronic Health...

Area of Science:

• Public Health
• Health Informatics
• Data Science

Background:

• Electronic health records (EHRs) are increasingly recognized for their potential in public health surveillance.
• However, understanding how populations represented in EHRs compare to those in traditional health and demographic surveys is crucial for accurate surveillance.
• Regional distributed data networks (DDNs) aggregate EHR data, raising questions about their representativeness.

Purpose of the Study:

• To compare the demographic and geographic characteristics of a population represented in a regional distributed data network (DDN) with those from established health and demographic surveys.
• To assess the representativeness of EHR data as a public health surveillance tool by evaluating population coverage and demographic distributions.

Main Methods:

• A cross-sectional design was used to analyze aggregated EHR data from ten healthcare organizations in a Colorado DDN for 2017.
• DDN population data (n=609,840 adults in 7 counties) were compared with survey data from the American Community Survey (ACS), Colorado Health Access Survey, and Behavioral Risk Factor Surveillance System.
• Comparisons included population size, sex, age group, race/ethnicity, and poverty level to assess surveillance system representativeness.

Main Results:

• The DDN captured 25% of the general adult population in the study region, with county-level coverage ranging from 15% to 35%.
• Demographic distributions between the DDN and surveys were similar for many characteristics.
• The DDN exhibited higher proportions of women, older adults, Hispanic individuals, and people in high-poverty neighborhoods compared to the ACS population.

Conclusions:

• The DDN population is not a random sample and is influenced by healthcare utilization patterns and participating organizations.
• The strengths and limitations of DDNs and survey-based approaches are complementary for public health surveillance.
• Regional DDNs represent a promising tool for public health surveillance, offering unique insights when used in conjunction with traditional methods.