A Computable Phenotype Improves Cohort Ascertainment in a Pediatric Pulmonary Hypertension Registry.

ABSTRACT:

Objectives

To compare registry and electronic health record (EHR) data mining approaches for cohort ascertainment in patients with pediatric pulmonary hypertension (PH) in an effort to overcome some of the limitations of registry enrollment alone in identifying patients with particular disease phenotypes.

Study design

This study was a single-center retrospective analysis of EHR and registry data at Boston Children's Hospital. The local Informatics for Integrating Biology and the Bedside (i2b2) data warehouse was queried for billing codes, prescriptions, and narrative data related to pediatric PH. Computable phenotype algorithms were developed by fitting penalized logistic regression models to a physician-annotated training set. Algorithms were applied to a candidate patient

SUBMITTER: Geva A 

PROVIDER: S-EPMC5572538 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature