title: Clinical decision support for atypical orders: detection and warning of atypical medication orders submitted to a computerized provider order entry system.
abstract: The specificity of medication-related alerts must be improved to overcome the pernicious effects of alert fatigue. A systematic comparison of new drug orders to historical orders could improve alert specificity and relevance. Using historical order data from a computerized provider order entry system, we alerted physicians to atypical orders during the prescribing of five medications: calcium, clopidogrel, heparin, magnesium, and potassium. The percentage of atypical orders placed for these five medications decreased during the 92 days the alerts were active when compared to the same period in the previous year (from 0.81% to 0.53%; p=0.015). Some atypical orders were appropriate. Fifty of the 68 atypical order alerts were over-ridden (74%). However, the over-ride rate is misleading because 28 of the atypical medication orders (41%) were changed. Atypical order alerts were relatively few, identified problems with frequencies as well as doses, and had a higher specificity than dose check alerts.
authors.affiliation: American Society of Health-System Pharmacists, Wisconsin Avenue, Bethesda, Maryland, USA.
authors.forename: Allie D
authors.initials: AD
authors.lastname: Woods
authors.forename: David P
authors.initials: DP
authors.lastname: Mulherin
authors.forename: Allen J
authors.initials: AJ
authors.lastname: Flynn
authors.forename: James G
authors.initials: JG
authors.lastname: Stevenson
authors.forename: Christopher R
authors.initials: CR
authors.lastname: Zimmerman
authors.forename: Bruce W
authors.initials: BW
authors.lastname: Chaffee
mesh_terms: D000328:Adult; D020000:Decision Support Systems, Clinical; D004360:Drug Therapy, Computer-Assisted; D006784:Hospitals, Teaching; D006801:Humans; D050316:Medical Order Entry Systems; D008508:Medication Errors / Q000517:prevention & control*; D008510:Medication Systems, Hospital; D019982:Organizational Case Studies
keywords: clinical decision support systems; clinical pharmacy information systems; computer-assisted; drug therapy; medical order entry systems; pharmacy service