Predicting benzodiazepine prescriptions: A proof-of-concept machine learning approach.

ABSTRACT:

Introduction

Benzodiazepines are the most commonly prescribed psychotropic medications, but they may place users at risk of serious adverse effects. Developing a method to predict benzodiazepine prescriptions could assist in prevention efforts.

Methods

The present study applies machine learning methods to de-identified electronic health record data, in order to develop algorithms for predicting benzodiazepine prescription receipt (yes/no) and number of benzodiazepine prescriptions (0, 1, 2+) at a given encounter. Support-vector machine (SVM) and random forest (RF) approaches were applied to outpatient psychiatry, family medicine, and geriatric medicine data from a large academic medical center. The training sample comprised encounters taking place between January 2020 and De

SUBMITTER: Kinney KL 

PROVIDER: S-EPMC10036348 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature