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

Journal of Medical Internet Research
Sarah N MusyMichael Simon

Abstract

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. 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. PubMed, EMBASE, CINAHL, and the Cochrane Library were queried. We included observational studies, applying trigger tools in acute care settings, and excluded studies using nonhospital and outpatient settings. Eligible articles were divided into diagnostic test accuracy studies and prevalence studies. We derived the study prevalence and estimates for the positive predictive value. We assessed bias risks and applicability concerns using Quality Assessment tool for Diagnostic Accuracy Stu...Continue Reading

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Citations

Jan 1, 2019·Therapeutic Innovation & Regulatory Science·Scott R Walter, Blanca Gallego
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Aug 28, 2021·International Journal of Environmental Research and Public Health·Sung-Hee HwangJu-Yeun Lee

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Software Mentioned

Global Trigger Tool ( GTT )
SAS Text Miner

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