Machine Learning Approach to Reduce Alert Fatigue Using a Disease Medication-Related Clinical Decision Support System: Model Development and Validation.

ABSTRACT:

Background

Computerized physician order entry (CPOE) systems are incorporated into clinical decision support systems (CDSSs) to reduce medication errors and improve patient safety. Automatic alerts generated from CDSSs can directly assist physicians in making useful clinical decisions and can help shape prescribing behavior. Multiple studies reported that approximately 90%-96% of alerts are overridden by physicians, which raises questions about the effectiveness of CDSSs. There is intense interest in developing sophisticated methods to combat alert fatigue, but there is no consensus on the optimal approaches so far.

Objective

Our objective was to develop machine learning prediction models to predict physicians' responses in order to reduce alert fatigue from disease medicati

SUBMITTER: Poly TN 

PROVIDER: S-EPMC7714650 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature