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First published August 6, 2004 as JAMIA PrePrint; doi:10.1197/jamia.M1586
Journal of the American Medical Informatics Association 2004;11(6):492-498
© 2004 American Medical Informatics Association


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Submitted on March 24, 2004
Accepted on July 1, 2004

Strategies for Detecting Adverse Drug Events Among Older Persons in the Ambulatory Setting

Terry S. Field DSc1*, Jerry H. Gurwitz MD1, Leslie R. Harrold MD, MPH1, Jeffrey M. Rothschild MD, MPH2, Kristin Debellis PharmD3, Andrew C. Seger PharmD3, Leslie S. Fish PharmD3, Lawrence Garber MD3, Michael Kelleher MD3, and David W. Bates MD, MSc4

Affiliation of the authors: 1 Meyers Primary Care Institute; Fallon Foundation; University of Massachusetts Medical School, Worcester, MA; 2 Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital; Partners HealthCare System; Harvard Medical School; Boston, MA; 3 Meyers Primary Care Institute; Fallon Foundation; University of Massachusetts Medical School; Worcester, MA; 4 Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital; Partners HealthCare System; Harvard Medical School, Boston, MA

* To whom correspondence should be addressed.

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 multi-specialty group practice during a 12-month observation period (July 1, 1999 through June 30, 2000).

Measurement Possible drug-related incidents occurring in the ambulatory clinical setting were detected using signals from multiple sources.

Results During the tracking period there were 1523 identified ADEs, of which 28% (n=421) were considered preventable. Across all sources, 23,917 signals were found; 44% were potential incidents that led to review of a patient's medical record and 2266 were presented to physician-reviewers. Although the positive predictive value (PPV) for reports from providers was high compared to 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 from healthcare providers as the principal means for detection of adverse drug events and suggest that multiple strategies are required to detect adverse drug events in geriatric ambulatory patients.




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