A computer alert system to prevent injury from adverse drug events: development and evaluation in a community teaching hospital

JAMA. 1998 Oct 21;280(15):1317-20. doi: 10.1001/jama.280.15.1317.

Abstract

Context: Adverse drug events (ADEs) are the most common type of iatrogenic injury occurring in hospitalized patients. Errors leading to ADEs are often due to restricted availability of information at the time of physician order writing.

Objectives: To develop, implement, and evaluate a computer alert system designed to correct errors that might lead to ADEs and to detect ADEs before maximum injury occurs.

Design: Prospective case series.

Setting: A 650-bed community teaching hospital in Phoenix, Ariz.

Patients: Consecutive sample of 9306 nonobstetrical adult patients admitted during the last 6 months of 1997.

Interventions: Thirty-seven drug-specific ADEs were targeted. Our hospital information system was programmed to generate alerts in clinical situations with increased risk for ADE-related injury. A clinical system was developed to ensure physician notification of alerts.

Main outcome measures: A true-positive alert was defined as one in which the physician wrote orders consistent with the alert recommendation after alert notification.

Results: During the 6-month study period, the alert system fired 1116 times and 596 were true-positive alerts (positive predictive value of 53%). The alerts identified opportunities to prevent patient injury secondary to ADEs at a rate of 64 per 1000 admissions. A total of 265 (44%) of the 596 true-positive alerts were unrecognized by the physician prior to alert notification.

Conclusions: Clinicians can use hospital information systems to detect opportunities to prevent patient injury secondary to a broad range of ADEs.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computer Systems
  • Decision Support Systems, Clinical
  • Drug Therapy, Computer-Assisted*
  • Drug-Related Side Effects and Adverse Reactions*
  • Hospital Bed Capacity, 500 and over
  • Hospital Information Systems*
  • Hospitals, Teaching
  • Humans
  • Medication Errors / prevention & control*
  • Prospective Studies