Unsupervised Coverage Sampling to Enhance Clinical Chart Review Coverage for Computable Phenotype Development: Simulation and Empirical Study.

ABSTRACT:

Background

Developing computable phenotypes (CP) based on electronic health records (EHR) data requires "gold-standard" labels for the outcome of interest. To generate these labels, clinicians typically chart-review a subset of patient charts. Charts to be reviewed are most often randomly sampled from the larger set of patients of interest. However, random sampling may fail to capture the diversity of the patient population, particularly if smaller subpopulations exist among those with the condition of interest. This can lead to poorly performing and biased CPs.

Objective

This study aimed to propose an unsupervised sampling approach designed to better capture a diverse patient cohort and improve the information coverage of chart review samples.

Methods

Our coverage sa

SUBMITTER: Wang Z 

PROVIDER: S-EPMC12661603 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature