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Related Experiment Videos

Using computerized data to identify adverse drug events in outpatients.

B Honigman1, J Lee, J Rothschild

  • 1University of Colorado Health Sciences Center, Denver, USA. benjamin.honigman@uchsc.edu

Journal of the American Medical Informatics Association : JAMIA
|April 26, 2001
PubMed
Summary
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Computerized programs effectively detect adverse drug events (ADEs) in ambulatory care, with free-text searches proving particularly valuable. These ADEs are common, sometimes requiring hospitalization, highlighting the need for such detection systems.

Area of Science:

  • Pharmacovigilance
  • Health Informatics
  • Clinical Decision Support

Background:

  • Adverse drug events (ADEs) represent a significant patient safety concern in ambulatory settings.
  • Current methods for ADE detection may not fully capture their incidence and impact.
  • Electronic medical records (EMRs) offer potential for automated ADE identification.

Purpose of the Study:

  • To assess the efficacy of a computer program in identifying ADEs within an ambulatory care environment.
  • To compare the effectiveness of four distinct computer search strategies: diagnosis codes, allergy rules, event monitoring rules, and text searching.

Main Methods:

  • A retrospective analysis was conducted on one year of EMR data from 15,665 patients receiving care.
  • The study evaluated the presence of ADEs and the sensitivity and specificity of various computer search methods.

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Main Results:

  • The computer program identified an estimated 864 ADEs, occurring at a rate of 5.5 per 100 patients.
  • Approximately 3.4 ADE-related hospital admissions occurred per 1,000 patients.
  • Free-text searches demonstrated particular utility, with overall search sensitivity at 58% and specificity at 88%.

Conclusions:

  • Computerized search programs, especially those utilizing free-text analysis, are effective tools for detecting ADEs.
  • ADEs are frequent and can lead to hospitalizations, underscoring their clinical significance.
  • These detection systems add value to EMRs and can support quality improvement initiatives.