Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

ABSTRACT:

Objectives

Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients from the electronic health record is consequently challenging as current algorithms (computable phenotypes) rely on diagnostic codes (e.g., International Classification of Disease, ICD) in addition to other criteria (e.g., inhaler medications)-but presume an accurate diagnosis. As such, there is no universally accepted or rigorously tested computable phenotype for asthma.

Methods

We compared two established asthma computable phenotypes: the Chicago Area Patient-Outcomes Research Network (CAPriCORN) and Phenotype KnowledgeBase (PheKB

SUBMITTER: Ross MK 

PROVIDER: S-EPMC9113735 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature