Secondary use of electronic health record data: spontaneous triggered adverse drug event reporting

Pharmacoepidemiol Drug Saf. 2010 Dec;19(12):1211-5. doi: 10.1002/pds.2027.


Purpose: Physicians in the United States report fewer than 1% of adverse drug events (ADEs) to the Food and Drug Administration (FDA), but frequently document ADEs within electronic health records (EHRs). We developed and implemented a generalizable, scalable EHR-based system to automatically send electronic ADE reports to the FDA in real-time.

Methods: Proof-of-concept study involving 26 clinicians given access to EHR-based ADE reporting functionality from December 2008 to May 2009.

Measurements: Number and content of ADE reports; severity of adverse reactions (clinician and computer algorithm defined); clinician survey.

Results: During the study period, 26 clinicians submitted 217 reports to the FDA. The clinicians defined 23% of the ADEs as serious and a computer algorithm defined 4% of the ADEs as serious. The most common drug classes were cardiovascular drugs (40%), central nervous system drugs (19%), analgesics (13%), and endocrine drugs (7%). The reports contained information, pre-filled from the EHR, about comorbid conditions (207 reports [95%] listed 1899 comorbid conditions), concurrent medications (193 reports [89%] listed 1687 concurrent medications), weight (209 reports [96%]), and laboratory data (215 reports [99%]). It took clinicians a mean of 53 seconds to complete and send the form. In the clinician survey, 21 of 23 respondents (91%) said they had submitted zero ADE reports to the FDA in the prior 12 months.

Conclusions: EHR-based, triggered ADE reporting is efficient and acceptable to clinicians, provides detailed clinical information, and has the potential to greatly increase the number and quality of spontaneous reports submitted to the FDA.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adverse Drug Reaction Reporting Systems / organization & administration*
  • Algorithms
  • Data Collection
  • Electronic Data Processing
  • Electronic Health Records / organization & administration*
  • Humans
  • Middle Aged
  • Pilot Projects
  • Practice Patterns, Physicians'
  • Severity of Illness Index
  • United States
  • United States Food and Drug Administration*