Assessing the performance characteristics of signals used by a clinical event monitor to detect adverse drug reactions in the nursing home

AMIA Annu Symp Proc. 2008 Nov 6;2008:278-82.

Abstract

Adverse drug reactions (ADRs) are a common cause of morbidity and mortality in the nursing home (NH) setting. Traditional non-automated mechanisms for ADR detection are time-consuming, costly, and fail to detect the majority of ADRs. We describe the implementation and pharmacist evaluation of a clinical event monitor using signals previously developed by our research team to detect potential ADRs in the NH. The overall positive predictive value (PPV) for all signals combined was 81% (54/67), with individual signal PPVs ranging from 0-100%. The PPVs were 53% (10/19) for the antidote signals category and 96% (44/46) for the laboratory/ medication combination signals category. The majority 75% (12/16) of the preventable ADRs were laboratory/medication combination signals. The results suggest that ADRs can be detected in the NH setting with a high degree of accuracy using a clinical event monitor that employs a set of signals derived by expert consensus.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adverse Drug Reaction Reporting Systems / organization & administration*
  • Decision Support Systems, Clinical / organization & administration*
  • Diagnosis, Computer-Assisted / methods*
  • Drug Monitoring / methods*
  • Drug-Related Side Effects and Adverse Reactions / diagnosis*
  • Humans
  • Monitoring, Physiologic / methods*
  • Nursing Homes / statistics & numerical data
  • Reproducibility of Results
  • Sensitivity and Specificity