Computerized survelliance of adverse drug reactions in hospital: pilot study

Br J Clin Pharmacol. 1998 Mar;45(3):309-14. doi: 10.1046/j.1365-2125.1998.00685.x.


Aims: To develop and assess the use of computerized laboratory data as a detection support tool of adverse drug reactions (ADRs) in hospital.

Methods: This was a retrospective observational study of 153 sequential medical admissions during a 2-month period to the 34-bed medical ward at the Hadassah University Hospital, Jerusalem, Israel. Measurements made were 1) Retrospective chart review for recognized and unrecognized adverse drug reactions (ADRs) and 2) Analysis of computerizied laboratory data according to defined automatic laboratory signals (ALS) for adverse reactions.

Results: Forty ADRs have been detected in 38 out of the 153 hospital admissions (24.8%). Nine reactions were considered severe. Altogether 212 ALS were generated involving 86 admissions. In 25 (65.8%) of the ADR-positive admissions ADRs were detected through automatic signals generated from the laboratory data. ALS were detected in 56 out of the 115 (48.7%) ADR-negative admissions. Twenty-four (60%) of the ADRs were not recognized as such by the attending physicians. Two of these reactions were severe. ALS could have generated an alert for 19 (79.2%) of the unrecognized reactions.

Conclusions: Application of automatic laboratory signals can increase the rate of recognition of the ADRs and thereby improve medical care. The sensitivity and specificity of the method might be increased by refinement and redefinition of the signals.

MeSH terms

  • Adult
  • Adverse Drug Reaction Reporting Systems*
  • Aged
  • Aged, 80 and over
  • Computer Systems
  • Drug Monitoring / methods*
  • Drug-Related Side Effects and Adverse Reactions*
  • Female
  • Hospital Information Systems*
  • Hospitals, University / standards
  • Humans
  • Male
  • Mass Screening
  • Middle Aged
  • Patient Admission / standards
  • Pilot Projects
  • Retrospective Studies
  • Sensitivity and Specificity
  • Severity of Illness Index