title: Assessing the performance characteristics of signals used by a clinical event monitor to detect adverse drug reactions in the nursing home.
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.
authors.affiliation: Division of Geriatric Medicine, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Handler
authors.forename: Joseph T
authors.initials: JT
authors.lastname: Hanlon
authors.forename: Subashan
authors.initials: S
authors.lastname: Perera
authors.forename: Melissa I
authors.initials: MI
authors.lastname: Saul
authors.forename: Douglas B
authors.initials: DB
authors.lastname: Fridsma
authors.forename: Shyam
authors.initials: S
authors.lastname: Visweswaran
authors.forename: Stephanie A
authors.initials: SA
authors.lastname: Studenski
authors.forename: Yazan F
authors.initials: YF
authors.lastname: Roumani
authors.forename: Nicholas G
authors.initials: NG
authors.lastname: Castle
authors.forename: David A
authors.initials: DA
authors.lastname: Nace
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Becich
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration*; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D016903:Drug Monitoring / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000175:diagnosis*; D006801:Humans; D008991:Monitoring, Physiologic / Q000379:methods*; D009735:Nursing Homes / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity