Electronically screening discharge summaries for adverse medical events

Harvey J. Murff, Alan J. Forster, Josh F. Peterson, Julie M. Fiskio, Heather L. Heiman, David W. Bates*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

72 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)339-350
Number of pages12
JournalJournal of the American Medical Informatics Association
Volume10
Issue number4
DOIs
StatePublished - 2003

ASJC Scopus subject areas

  • Health Informatics

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