Literature DB >> 15684124

A trial of automated decision support alerts for contraindicated medications using computerized physician order entry.

William L Galanter1, Robert J Didomenico, Audrius Polikaitis.   

Abstract

BACKGROUND: Automated clinical decision support has shown promise in reducing medication errors; however, clinicians often do not comply with alerts. Because renal insufficiency is a common source of medication errors, the authors studied a trial of alerts designed to reduce inpatient administration of medications contraindicated due to renal insufficiency.
METHODS: A minimum safe creatinine clearance was established for each inpatient formulary medication. Alerts recommending cancellation appeared when a medication order was initiated for a patient whose estimated creatinine clearance was less than the minimum safe creatinine clearance for the medication. Administration of medications in patients with creatinine clearances less than the medication's minimum safe clearance were studied for 14 months after, and four months before, alert implementation. In addition, the impact of patient age, gender, degree of renal dysfunction, time of day, and duration of housestaff training on the likelihood of housestaff compliance with the alerts was examined.
RESULTS: The likelihood of a patient receiving at least one dose of contraindicated drug after the order was initiated decreased from 89% to 47% (p < 0.0001) after alert implementation. Analysis of the alerts seen by housestaff showed that alert compliance was higher in male patients (57% vs. 38%, p = 0.02), increased with the duration of housestaff training (p = 0.04), and increased in patients with worsening renal function (p = 0.007).
CONCLUSION: Alerts were effective in decreasing the ordering and administration of drugs contraindicated due to renal insufficiency. Compliance with the alerts was higher in male patients, increased with the duration of housestaff training, and increased in patients with more severe renal dysfunction.

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Year:  2005        PMID: 15684124      PMCID: PMC1090457          DOI: 10.1197/jamia.M1727

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


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