Guided medication dosing for elderly emergency patients using real-time, computerized decision support

Richard T. Griffey, Helen G. Lo, Elisabeth Burdick, Carol Keohane, David W. Bates

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

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). Design: 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 sedativehypnotics, the computer application either adjusted the dosing or suggested a different medication. Physicians could accept or reject recommendations. Measurements: 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. Limitations: Single institution study, retrospective chart review for ADEs. Conclusion: 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.

Original languageEnglish
Pages (from-to)86-93
Number of pages8
JournalJournal of the American Medical Informatics Association
Volume19
Issue number1
DOIs
StatePublished - Jan 2012

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