External validation of a machine learning classifier to identify unhealthy alcohol use in hospitalized patients.

ABSTRACT:

Background and aims

Unhealthy alcohol use (UAU) is one of the leading causes of global morbidity. A machine learning approach to alcohol screening could accelerate best practices when integrated into electronic health record (EHR) systems. This study aimed to validate externally a natural language processing (NLP) classifier developed at an independent medical center.

Design

Retrospective cohort study.

Setting

The site for validation was a midwestern United States tertiary-care, urban medical center that has an inpatient structured universal screening model for unhealthy substance use and an active addiction consult service.

Participants/cases

Unplanned admissions of adult patients between October 23, 2017 and December 31, 2019, with EHR documentation of manual

SUBMITTER: Lin Y 

PROVIDER: S-EPMC9296269 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature