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Electronically Screening Discharge Summaries for Adverse Medical Events

Affiliations of the authors: Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts. Dr. Murff and Dr. Peterson are currently in the Division of General Internal Medicine, Vanderbilt University Medical Center, Nashville, TN; Ms. Fiskio, Dr. Heiman, and Dr. Bates are currently in the Division of General Internal Medicine, Brigham & Women's Hospital, and Harvard Medical School, Boston, MA; Dr. Forster is currently at the University of Ottawa, Clinical Epidemiology Unit, Ottawa Health Research Unit, Ottawa Hospital, Ottawa, Ontario, Canada

Correspondence and reprints: David W. Bates,MD, MSc, Chief, Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA 02115; e-mail: <dbates{at}partners.org>.

Received for publication: 08/08/02; accepted for publication: 01/29/03.

Objective: Detecting adverse events is pivotal for measuring and improving medical safety, yet current techniques discourage routine screening. The authors hypothesized that discharge summaries would include information on adverse events, and they developed and evaluated an electronic method for screening medical discharge summaries for adverse events.

Design: A cohort study including 424 randomly selected admissions to the medical services of an academic medical center was conducted between January and July 2000. The authors developed a computerized screening tool that searched free-text discharge summaries for trigger words representing possible adverse events.

Measurements: All discharge summaries with a trigger word present underwent chart review by two independent physician reviewers. The presence of adverse events was assessed using structured implicit judgment. A random sample of discharge summaries without trigger words also was reviewed.

Results: Fifty-nine percent (251 of 424) of the discharge summaries contained trigger words. Based on discharge summary review, 44.8% (327 of 730) of the alerted trigger words indicated a possible adverse event. After medical record review, the tool detected 131 adverse events. The sensitivity and specificity of the screening tool were 69% and 48%, respectively. The positive predictive value of the tool was 52%.

Conclusion: Medical discharge summaries contain information regarding adverse events. Electronic screening of discharge summaries for adverse events using keyword searches is feasible but thus far has poor specificity. Nonetheless, computerized clinical narrative screening methods could potentially offer researchers and quality managers a means to routinely detect adverse events.