title: Guided medication dosing for elderly emergency patients using real-time, computerized decision support.
abstract: OBJECTIVE
  To evaluate the impact of a real-time computerized decision support tool in the emergency department that guides medication dosing for the elderly on physician ordering behavior and on adverse drug events (ADEs).
  
  
  METHODS
  A prospective controlled trial was conducted over 26 weeks. The status of the decision support tool alternated OFF (7/17/06-8/29/06), ON (8/29/06-10/10/06), OFF (10/10/06-11/28/06), and ON (11/28/06-1/16/07) in consecutive blocks during the study period. In patients ≥65 who were ordered certain benzodiazepines, opiates, non-steroidals, or sedative-hypnotics, the computer application either adjusted the dosing or suggested a different medication. Physicians could accept or reject recommendations.
  
  
  METHODS
  The primary outcome compared medication ordering consistent with recommendations during ON versus OFF periods. Secondary outcomes included the admission rate, emergency department length of stay for discharged patients, 10-fold dosing orders, use of a second drug to reverse the original medication, and rate of ADEs using previously validated explicit chart review.
  
  
  RESULTS
  2398 orders were placed for 1407 patients over 1548 visits. The majority (49/53; 92.5%) of recommendations for alternate medications were declined. More orders were consistent with dosing recommendations during ON (403/1283; 31.4%) than OFF (256/1115; 23%) periods (p≤0.0001). 673 (43%) visits were reviewed for ADEs. The rate of ADEs was lower during ON (8/237; 3.4%) compared with OFF (31/436; 7.1%) periods (p=0.02). The remaining secondary outcomes showed no difference.
  
  
  CONCLUSIONS
  Single institution study, retrospective chart review for ADEs.
  
  
  CONCLUSIONS
  Though overall agreement with recommendations was low, real-time computerized decision support resulted in greater acceptance of medication recommendations. Fewer ADEs were observed when computerized decision support was active.
authors: Division of Emergency Medicine, Washington University Institute for Public Health, St. Louis, Missouri, USA. griffeyr@wustl.edu
authors: Richard T
authors: RT
authors: Griffey
authors: Helen G
authors: HG
authors: Lo
authors: Elisabeth
authors: E
authors: Burdick
authors: Carol
authors: C
authors: Keohane
authors: David W
authors: DW
authors: Bates
mesh_terms: D000368:Aged; D003199:Computer Systems; D020000:Decision Support Systems, Clinical; D004360:Drug Therapy, Computer-Assisted; D064420:Drug-Related Side Effects and Adverse Reactions / Q000517:prevention & control*; D004636:Emergency Service, Hospital; D006786:Hospitals, Urban; D006801:Humans; D051188:Knowledge Bases; D004364:Pharmaceutical Preparations / Q000008:administration & dosage; D011446:Prospective Studies
chemical_list: D004364:Pharmaceutical Preparations