Development of an Electronic Algorithm to Identify in Real Time Adults Hospitalized With Suspected Community-Acquired Pneumonia.

ABSTRACT:

Background

Community-acquired pneumonia (CAP) is a major driver of hospital antibiotic use. Efficient methods to identify patients treated for CAP in real time using the electronic health record (EHR) are needed. Automated identification of these patients could facilitate systematic tracking, intervention, and feedback on CAP-specific metrics such as appropriate antibiotic choice and duration.

Methods

Using retrospective data, we identified suspected CAP cases by searching for patients who received CAP antibiotics AND had an admitting International Classification of Diseases, Tenth Revision (ICD-10) code for pneumonia OR chest imaging within 24 hours OR bacterial urinary antigen testing within 48 hours of admission (denominator query). We subsequently explored

SUBMITTER: Jones G 

PROVIDER: S-EPMC8231365 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature