Small-area estimation for public health surveillance using electronic health record data: reducing the impact of underrepresentation.

ABSTRACT:

Background

Electronic Health Record (EHR) data are increasingly being used to monitor population health on account of their timeliness, granularity, and large sample sizes. While EHR data are often sufficient to estimate disease prevalence and trends for large geographic areas, the same accuracy and precision may not carry over for smaller areas that are sparsely represented by non-random samples.

Methods

We developed small-area estimation models using a combination of EHR data drawn from MDPHnet, an EHR-based public health surveillance network in Massachusetts, the American Community Survey, and state hospitalization data. We estimated municipality-specific prevalence rates of asthma, diabetes, hypertension, obesity, and smoking in each of the 351 municipalities in Massachu

SUBMITTER: Chen T 

PROVIDER: S-EPMC9364501 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature