Trigger Tool-Based Automated Adverse Event Detection in Electronic Health Records: Systematic Review.

ABSTRACT: BACKGROUND:Adverse events in health care entail substantial burdens to health care systems, institutions, and patients. Retrospective trigger tools are often manually applied to detect AEs, although automated approaches using electronic health records may offer real-time adverse event detection, allowing timely corrective interventions. OBJECTIVE:The aim of this systematic review was to describe current study methods and challenges regarding the use of automatic trigger tool-based adverse event detection methods in electronic health records. In addition, we aimed to appraise the applied studies' designs and to synthesize estimates of adverse event prevalence and diagnostic test accuracy of automatic detection methods using manual trigger tool as a reference standard. METHODS:PubMed, EMBASE

SUBMITTER: Musy SN 

PROVIDER: S-EPMC6000482 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature