Strategies for Detecting Adverse Drug Events among Older Persons in the Ambulatory Setting
- Terry S Field,
- Jerry H Gurwitz,
- Leslie R Harrold,
- Jeffrey M Rothschild,
- Kristin Debellis,
- Andrew C Seger,
- Leslie S Fish,
- Lawrence Garber,
- Michael Kelleher,
- David W Bates
- Affiliations of the authors: Meyers Primary Care Institute, Fallon Foundation and University of Massachusetts Medical School, Worcester, MA (TSF, JHG, LRH, KD, ACS, LSF, LG, MK); Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital and Partners HealthCare System and Harvard Medical School, Boston, MA (JMR, DWB)
- Correspondence and reprints: Terry S. Field, DSc, Meyers Primary Care Institute, Fallon Healthcare System and University of Massachusetts Medical School, 630 Plantation Street, Worcester, MA 01605; e-mail: <tfield{at}meyersprimary.org or terry.field{at}umassmed.edu>
- Received 24 March 2004
- Accepted 1 July 2004
Abstract
Objective To examine various strategies for the identification of adverse drug events (ADEs) among older persons in the ambulatory clinical setting.
Design A cohort study of Medicare enrollees (n = 31,757 per month) receiving medical care from a large multispecialty group practice during a 12-month observation period (July 1, 1999 through June 30, 2000).
Measurements Possible drug-related incidents occurring in the ambulatory clinical setting were detected using signals from multiple sources.
Results During the tracking period, there were 1,523 identified ADEs, of which 421 (28%) were considered preventable. Across all sources, 23,917 signals were found; 12,791 (53%) were potential incidents that led to review of a patient's medical record and 2,266 (9%) were presented to physician reviewers. Although the positive predictive value (PPV) for reports from providers was high compared with other sources (54%), only 11% of the ADEs and 6% of the preventable ADEs were identified through this source. PPVs for other sources ranged from a low of 4% for administrative incident reports to a high of 12% for free-text review of electronic notes. Computer-generated signals were the source for 31% of the ADEs and 37% of the preventable ADEs. Electronic notes were the source for 39% of the ADEs and 29% of the preventable ADEs. There was little overlap in the ADEs identified across all sources.
Conclusion Our findings emphasize the limitations of voluntary reporting by health care providers as the principal means for detection of ADEs and suggest that multiple strategies are required to detect ADEs in geriatric ambulatory patients.
Footnotes
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Supported by research grant AG 15979 from the National Institute on Aging, Bethesda, MD. The contents are solely the responsibility of the authors and do not necessarily reflect the official views of the National Institute on Aging.
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The authors thank Jill Auger, RPh, and Leslie Garber, RPh, for assistance with data collection relevant to this study. Mary Ellen Stansky and Jackie Cernieux, MPH, are acknowledged for their assistance with technical aspects of this study and Bessie Petropoulos for assistance with manuscript preparation.
