title: An empirical model to estimate the potential impact of medication safety alerts on patient safety, health care utilization, and cost in ambulatory care.
abstract: BACKGROUND
  Because ambulatory care clinicians override as many as 91% of drug interaction alerts, the potential benefit of electronic prescribing (e-prescribing) with decision support is uncertain.
  
  
  METHODS
  We studied 279 476 alerted prescriptions written by 2321 Massachusetts ambulatory care clinicians using a single commercial e-prescribing system from January 1 through June 30, 2006. An expert panel reviewed a sample of common drug interaction alerts, estimating the likelihood and severity of adverse drug events (ADEs) associated with each alert, the likely injury to the patient, and the health care utilization required to address each ADE. We estimated the cost savings due to e-prescribing by using third-party-payer and publicly available information.
  
  
  RESULTS
  Based on the expert panel's estimates, electronic drug alerts likely prevented 402 (interquartile range [IQR], 133-846) ADEs in 2006, including 49 (14-130) potentially serious, 125 (34-307) significant, and 228 (85-409) minor ADEs. Accepted alerts may have prevented a death in 3 (IQR, 2-13) cases, permanent disability in 14 (3-18), and temporary disability in 31 (10-97). Alerts potentially resulted in 39 (IQR, 14-100) fewer hospitalizations, 34 (6-74) fewer emergency department visits, and 267 (105-541) fewer office visits, for a cost savings of 402,619 USD (IQR, 141,012-1,012,386 USD). Based on the panel's estimates, 331 alerts were required to prevent 1 ADE, and a few alerts (10%) likely accounted for 60% of ADEs and 78% of cost savings.
  
  
  CONCLUSIONS
  Electronic prescribing alerts in ambulatory care may prevent a substantial number of injuries and reduce health care costs in Massachusetts. Because a few alerts account for most of the benefit, e-prescribing systems should suppress low-value alerts.
authors.affiliation: Center for Patient Safety, Dana-Farber Cancer Institute, 44 Binney St, Boston, MA 02115, USA. saul_weingart@dfci.harvard.edu
authors.forename: Saul N
authors.initials: SN
authors.lastname: Weingart
authors.forename: Brett
authors.initials: B
authors.lastname: Simchowitz
authors.forename: Harper
authors.initials: H
authors.lastname: Padolsky
authors.forename: Thomas
authors.initials: T
authors.lastname: Isaac
authors.forename: Andrew C
authors.initials: AC
authors.lastname: Seger
authors.forename: Michael
authors.initials: M
authors.lastname: Massagli
authors.forename: Roger B
authors.initials: RB
authors.lastname: Davis
authors.forename: Joel S
authors.initials: JS
authors.lastname: Weissman
mesh_terms: D000465:Algorithms; D000553:Ambulatory Care / Q000191:economics / Q000592:standards* / Q000706:statistics & numerical data; D017046:Cost Savings / Q000706:statistics & numerical data; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions / Q000517:prevention & control*; D055695:Electronic Prescribing; D006801:Humans; D017751:Safety Management