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Title Development and impact of a computerized pediatric antiinfective decision support program
Author(s) Mullett CJ, Evans RS, Christenson JC, Dean JM
Source Pediatrics (Electronic Pages e75), Vol. 108, No. 4
Publication Date October 2001
Abstract OBJECTIVE: Computerized medical decision support tools have been shown to improve the quality of care and have been cited by the Institute of Medicine as one method to reduce pharmaceutical errors. We evaluated the impact of an antiinfective decision support tool in a pediatric intensive care unit (PICU). METHODS: We enhanced an existing adult antiinfective management tool by adding and changing medical logic to make it appropriate for pediatric patients. Process and outcomes measures were monitored prospectively during a 6-month control and a 6-month intervention period. Mandatory use of the decision support tool was initiated for all antiinfective orders in a 26-bed PICU during the intervention period. Clinician opinions of the decision support tool were surveyed via questionnaire. RESULTS: The rate of pharmacy interventions for erroneous drug doses declined by 59%. The rate of anti-infective subtherapeutic patient days decreased by 36%, and the rate of excessive-dose days declined by 28%. The number of orders placed per antiinfective course decreased 11.5%, and the robust estimate of the antiinfective costs per patient decreased 9%. The type of anti-infectives ordered and the number of antiinfective doses per patient remained similar, as did the rates of adverse drug events and antibiotic-bacterial susceptibility mismatches. The surveyed clinicians reported that use of the program improved their antiinfective agent choices as well as their awareness of impairments in renal function and reduced the likelihood of adverse drug events. CONCLUSIONS: Use of the pediatric antiinfective decision support tool in a PICU was considered beneficial to patient care by the clinicians and reduced the rates of erroneous drug orders, improved therapeutic dosage targets, and was associated with a decreased robust estimate of antiinfective costs per patient.

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