Literature DB >> 27543596

Detection of adverse drug events using an electronic trigger tool.

Dennison Lim1, Joe Melucci2, Milisa K Rizer3, Beth E Prier4, Robert J Weber4.   

Abstract

PURPOSE: Implementation and refinement of an integrated electronic "trigger tool" for detecting adverse drug events (ADEs) is described.
METHODS: A three-month prospective study was conducted at a large medical center to test and improve the positive predictive value (PPV) of an electronic health record-based tool for detecting ADEs associated with use of four "trigger drugs": the reversal agents flumazenil, naloxone, phytonadione, and protamine. On administration of a trigger drug to an adult patient, an electronic message was transmitted to two pharmacists, who reviewed cases in near real time (typically, on the same day) to detect actual or potential ADEs. In phase 1 of the study, any use of a trigger drug resulted in an alert message; in subsequent phases, the alerting criteria were narrowed on the basis of clinical criteria and laboratory data with the goal of refining the trigger tool's PPV.
RESULTS: A total of 87 drug administrations were reviewed during the three-month study period, with 27 ADEs detected. PPV values in phases 1, 2, and 3 were 0.33, 0.21, and 0.36, respectively. The relatively low overall PPV of the trigger tool was largely attributable to false-positive trigger messages associated with phytonadione use (such messages were reduced from 35 in phase 1 to 7 in phase 3).
CONCLUSION: Evaluation and refinement of an electronic trigger tool based on detecting the use of the reversal agents flumazenil, naloxone, phytonadione, and protamine found an overall PPV of 0.31 during a three-month study period.
Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

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Year:  2016        PMID: 27543596     DOI: 10.2146/ajhp150481

Source DB:  PubMed          Journal:  Am J Health Syst Pharm        ISSN: 1079-2082            Impact factor:   2.637


  5 in total

1.  Finding Dental Harm to Patients through Electronic Health Record-Based Triggers.

Authors:  M F Walji; A Yansane; N B Hebballi; A M Ibarra-Noriega; K K Kookal; S Tungare; K Kent; R McPharlin; V Delattre; E Obadan-Udoh; O Tokede; J White; E Kalenderian
Journal:  JDR Clin Trans Res       Date:  2019-12-10

2.  Identifying naloxone administrations in electronic health record data using a text-mining tool.

Authors:  Catherine G Derington; Shane R Mueller; Jason M Glanz; Ingrid A Binswanger
Journal:  Subst Abus       Date:  2020-12-15       Impact factor: 3.716

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

Authors:  Sarah N Musy; Dietmar Ausserhofer; René Schwendimann; Hans Ulrich Rothen; Marie-Madlen Jeitziner; Anne Ws Rutjes; Michael Simon
Journal:  J Med Internet Res       Date:  2018-05-30       Impact factor: 5.428

4.  Association between cancer-specific adverse event triggers and mortality: A validation study.

Authors:  Saul N Weingart; Jason Nelson; Benjamin Koethe; Omar Yaghi; Stephan Dunning; Albert Feldman; David Kent; Allison Lipitz-Snyderman
Journal:  Cancer Med       Date:  2020-04-13       Impact factor: 4.452

5.  Developing a cancer-specific trigger tool to identify treatment-related adverse events using administrative data.

Authors:  Saul N Weingart; Jason Nelson; Benjamin Koethe; Omar Yaghi; Stephan Dunning; Albert Feldman; David M Kent; Allison Lipitz-Snyderman
Journal:  Cancer Med       Date:  2020-01-03       Impact factor: 4.452

  5 in total

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