Multisite validation of a simple electronic health record algorithm for identifying diagnosed obstructive sleep apnea.

ABSTRACT:

Study objectives

We examined the performance of a simple algorithm to accurately distinguish cases of diagnosed obstructive sleep apnea (OSA) and noncases using the electronic health record (EHR) across six health systems in the United States.

Methods

Retrospective analysis of EHR data was performed. The algorithm defined cases as individuals with ≥ 2 instances of specific International Classification of Diseases (ICD)-9 and/or ICD-10 diagnostic codes (327.20, 327.23, 327.29, 780.51, 780.53, 780.57, G4730, G4733 and G4739) related to sleep apnea on separate dates in their EHR. Noncases were defined by the absence of these codes. Using chart reviews on 120 cases and 100 noncases at each site (n = 1,320 total), positive predictive value (PPV) and negative predictive value (NPV

SUBMITTER: Keenan BT 

PROVIDER: S-EPMC7053021 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature