Equivalence of electronic health record data for measuring hypertension prevalence: a retrospective comparison to BRFSS with data from two Indiana health systems, 2021

• Published in: BMC public health Vol. 25; no. 1; pp. 1285 - 8
• Main Authors: Allen, Katie S., Stiles, Justin, Daye, Veronica M., Wiensch, Ashley, Valvi, Nimish, Dixon, Brian E.
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 04.04.2025; BioMed Central; BMC
• Subjects: Adolescent; Adult; Age groups; Aged; Analysis; Behavioral Risk Factor Surveillance System; Blood pressure; Chronic conditions; Chronic diseases; Chronic illnesses; Demographics; Electronic health records; Electronic Health Records - statistics & numerical data; Electronic medical records; Electronic records; Equivalence; Estimates; Ethnicity; Female; Gender; Genotype & phenotype; Health surveillance; Humans; Hypertension; Hypertension - epidemiology; Hypotheses; Indiana - epidemiology; Infectious diseases; Male; Medical records; Middle Aged; Patients; Phenotypes; Prevalence; Prevalence studies (Epidemiology); Prevention; Public health; Public health surveillance; Retrospective Studies; Risk factors; Risk taking; Subpopulations; Surveillance systems; Young Adult; Indiana; United States > US; Public health surveillance; Chronic conditions; Public health
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-025-22425-9

Public health surveillance requires timely access to actionable data at every level. Current approaches for accessing chronic disease surveillance data are not sufficient, and health departments are increasingly looking to augment surveillance efforts using electronic health records (EHRs). While proven effective for acute syndromic surveillance, the utilization of EHR systems and health data networks for monitoring chronic conditions remains sparse. This study tested the generalizability of a previously validated hypertension computable phenotype. A previously developed phenotype was used to estimate prevalence of hypertension in a geographically and clinically distinct region from its development. To test validity, the results were compared to available, statewide Behavioral Risk Factor Surveillance System (BRFSS) data using the two one-sided t-test (TOST) of equivalence between BRFSS- and EHR-based prevalence estimates. The TOST was performed at the overall level as well as stratified by age, gender, and race/ethnicity. Compared to statewide hypertension prevalence of 34.5% in the BRFSS, an EHR-based phenotype estimated an overall prevalence of 24.1%. Estimates were not equivalent overall or across most subpopulations. Like BRFSS, we observed higher prevalence among Black men and women as well as increasing prevalence with age. With caveats, this study demonstrates that EHR-derived prevalence estimates may serve as a complement for population-based survey estimates. Utilizing available EHR data should increase timeliness of surveillance as well as enhance the ability of states and local health agencies to more readily address the burden of chronic disease in their respective jurisdictions.