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Intensive Care Med ; 34(6): 1083-90, 2008 Jun.
Article in English | MEDLINE | ID: mdl-18345530

ABSTRACT

OBJECTIVE: To identify and reduce medication-prescribing errors by introducing systematic physician education and post-cardiac surgery admission prescription forms. DESIGN: Errors were defined as: incomplete prescriptions; potential adverse drug events (ADEs), i.e. either intercepted or non-intercepted incorrect prescriptions not resulting in an ADE; and incorrect prescriptions that resulted in ADEs. Two baseline blinded pre-intervention data collection periods of 4 weeks and 1 week were followed by implementation of a post-cardiac surgery templated physician order and prescription form and systematic physicians' education. Twelve post-intervention data collections of 1-week duration were completed over a 3-year period and were either blinded or informed with reinforcement of physicians' education. SETTING: Tertiary paediatric cardiac intensive care unit. RESULTS: A total of 3648 prescriptions were evaluated at baseline (mean +/- SD of 687+/- 8 per week) and 811 +/- 129 prescriptions during each post-intervention period. Total baseline errors of 16.8% decreased to 8.4% after the first blinded data collection and to 4.8% at the final data collection (p<0.001). The occurrence of incomplete prescriptions fell from 15.3% at baseline to 3.6% at final data collection (p<0.001); intercepted potential ADEs fell from 1.3% to 1.1%; non-intercepted potential ADEs fell from 0.17% to zero; and post-operative prescribing errors fell from 44% to 4.6% (p<0.001), with the major reduction seen in incomplete prescriptions. CONCLUSION: The incidence of incomplete prescriptions significantly improved with education of physicians and use of post-cardiac surgery templated physician order and prescription forms. There was no impact on potential ADEs.


Subject(s)
Cardiac Surgical Procedures , Drug Prescriptions/statistics & numerical data , Intensive Care Units, Pediatric , Medication Errors/prevention & control , Chi-Square Distribution , Humans , Medication Errors/statistics & numerical data , Prospective Studies
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