The effect of number of healthcare visits on study sample selection and prevalence estimates in electronic health record data

Introduction: Few studies have addressed how to select a study sample when using electronic health record (EHR) data. Methods: Year 2016 EHR data from three health systems was used to examine how alternate definitions of the study sample, based on number of healthcare visits in one year, affected measures of disease period prevalence. Curated collections of ICD-9, ICD-10, and SNOMED codes were used to define three diseases. Results: Across all health systems, increasing the minimum required number of visits to be included in the study sample monotonically increased crude period prevalence estimates. The rate at which prevalence estimates increased with number of visits varied across sites and across diseases. Conclusions: When using EHR data authors must carefully describe how a study sample is identified and report outcomes for a range of sample definitions, so that others can assess the sensitivity of reported results to sample definition in EHR data.