Evaluation of a Novel System to Enhance Clinicians' Recognition of Preadmission Adverse Drug Reactions.

ABSTRACT:

Background

Often unrecognized by providers, adverse drug reactions (ADRs) diminish patients' quality of life, cause preventable admissions and emergency department visits, and increase health care costs.

Objective

This article evaluates whether an automated system, the Adverse Drug Effect Recognizer (ADER), could assist clinicians in detecting and addressing inpatients' ongoing preadmission ADRs.

Methods

ADER uses natural language processing to extract patients' medications, findings, and past diagnoses from admission notes. It compares excerpted information to a database of known medication adverse effects and promptly warns clinicians about potential ongoing ADRs and potential confounders via alerts placed in patients' electronic health records (EHRs). A 3-month int

SUBMITTER: Smith JC 

PROVIDER: S-EPMC5943080 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature