An algorithm to identify cases of pulmonary arterial hypertension from the electronic medical record.

ABSTRACT:

Background

Study of pulmonary arterial hypertension (PAH) in claims-based (CB) cohorts may facilitate understanding of disease epidemiology, however previous CB algorithms to identify PAH have had limited test characteristics. We hypothesized that machine learning algorithms (MLA) could accurately identify PAH in an CB cohort.

Methods

ICD-9/10 codes, CPT codes or PAH medications were used to screen an electronic medical record (EMR) for possible PAH. A subset (Development Cohort) was manually reviewed and adjudicated as PAH or "not PAH" and used to train and test MLAs. A second subset (Refinement Cohort) was manually reviewed and combined with the Development Cohort to make The Final Cohort, again divided into training and testing sets, with MLA characteristics defined on te

SUBMITTER: Schuler KP 

PROVIDER: S-EPMC9145474 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature