Optimizing Identification of People Living with HIV from Electronic Medical Records: Computable Phenotype Development and Validation.

ABSTRACT:

Background

Electronic health record (EHR)-based computable phenotype algorithms allow researchers to efficiently identify a large virtual cohort of Human Immunodeficiency Virus (HIV) patients. Built upon existing algorithms, we refined, improved, and validated an HIV phenotype algorithm using data from the OneFlorida Data Trust, a repository of linked claims data and EHRs from its clinical partners, which provide care to over 15 million patients across all 67 counties in Florida.

Methods

Our computable phenotype examined information from multiple EHR domains, including clinical encounters with diagnoses, prescription medications, and laboratory tests. To identify an HIV case, the algorithm requires the patient to have at least one diagnostic code for HIV and meet one of the

SUBMITTER: Liu Y 

PROVIDER: S-EPMC8672443 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature