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BMJ Qual Saf 21:670-675 doi:10.1136/bmjqs-2011-000643
  • Original research

Signal and noise: applying a laboratory trigger tool to identify adverse drug events among primary care patients

Open Access
  1. Urmimala Sarkar1,3
  1. 1Division of General Internal Medicine, San Francisco General Hospital, University of California, San Francisco, California, USA
  2. 2Department of Medicine, California Pacific Medical Center, San Francisco, California, USA
  3. 3Department of Medicine, Center for Vulnerable Populations, San Francisco General Hospital, University of California, San Francisco, California, USA
  1. Correspondence to Dr Urmimala Sarkar, Medicine, University of California, San Francisco, 1001 Potrero Av, Ward 13, San Francisco, CA 94110, USA; usarkar{at}medsfgh.ucsf.edu
  1. Contributors SB performed chart review of all triggers, and wrote the first draft of the manuscript. AD performed secondary chart review and provided intellectual contribution in editing the manuscript. AL conducted analysis and created tables and figures. CH oversaw data collection and provided intellectual contribution in editing the manuscript. US conceived the study, oversaw data collection and provided intellectual contribution in editing the manuscript.

  • Accepted 7 April 2012
  • Published Online First 23 May 2012

Abstract

Background The extent of outpatient adverse drug events (ADEs) remains unclear. Trigger tools are used as a screening method to identify care episodes that may be ADEs, but their value in a population with high chronic-illness burden remains unclear.

Methods The authors used six abnormal laboratory triggers for detecting ADEs among adults in outpatient care. Eligible patients were included if they were >18 years, sought primary or urgent care between November 2008 and November 2009 and were prescribed at least one medication. The authors then used the clinical / administrative database to identity patients with these triggers. Two physicians conducted in-depth chart review of any medical records with identified triggers.

Results The authors reviewed 1342 triggers representing 622 unique episodes among 516 patients. The trigger tool identified 91 (15%) ADEs. Of the 91 ADEs included in the analysis, 49 (54%) occurred during medication monitoring, 41 (45%) during patient self-administration, and one could not be determined. 96% of abnormal international normalised ratio triggers were ADEs, followed by 12% of abnormal blood urea nitrogen triggers, 9% of abnormal alanine aminotransferase triggers, 8% of abnormal serum creatinine triggers and 3% of aspartate aminotransferase triggers.

Conclusions The findings imply that other tools such as text triggers or more complex automated screening rules, which combine data hierarchically are needed to effectively screen for ADEs in chronically ill adults seen in primary care.

Footnotes

  • Funding Funds were provided by the National Centre for Research Resources KL2RR024130 (to US) and Agency for Healthcare Research and Quality K08 HS017594 (to US). None of the funders had any role in study design; in the collection, analysis, and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.

  • Competing interests None.

  • Ethics approval Ethics approval was granted by the University of California San Francisco Committee on Human Research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

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