Economic impact of standardized orders for antimicrobial prophylaxis program

OBJECTIVE: To assess the effect and economic impact of an intervention aime d at standardizing the timing of preoperative antimicrobial prophylaxis fro m the perspective of a major teaching hospital. DESIGN: A pre/post study design in which a random sample of 60 procedures f rom a 12-month period in the preintervention phase were reviewed. A compara tive sample of 60 procedures during a seven-month postintervention phase wa s selected. For each prophylactic course, preoperative dose administration details were classified as early (>2 h prior to incision), on time (0-2 h p rior), delayed (0-3 h after), or late (>3 after). To determine the economic impact of this intervention, we used a predictive decision analytic model using institutional costs and the published probabilities of inpatient surg ical wound infections (SWIs) following administration of antimicrobials tim ed according to the above criteria. Two conditions were analyzed: (1) an in terdisciplinary two-stage therapeutic interchange program involving staff e ducation and modification of preoperative antimicrobial orders to ensure ti mely administration and (2) no intervention. SETTING: An 1100-bed tertiary care, university-affiliate institution. PATIENTS: 120 randomly selected procedures involving inpatients who receive d a preoperative antibiotic. OUTCOME MEASURES: Differences in preoperative antimicrobial timing and cost avoidance associated with the intervention. RESULTS: In the preintervention phase, 68% of prophylactic courses were on lime, 22% were early, and the balance were delayed or late. The incidence o f on-time prophylaxis increased to 97% during the postintervention phase (p = 0.001). Operating room staff involvement in antimicrobial administration increased from 57% to 92% (p = 0.001). Based on a setup and annual interve ntion cost of $9100 CAN ($1 CAN = $0.68 US), an annual inpatient SWI avoida nce of 51 cases, an average infection-associated extended hospital slay of four days, and an average treatment cost of $1957 CAN per inpatient SWI, we estimated that 153 hospital days were avoided and there was an annual cost avoidance of $90 707 CAN ($1779 CAN saved per inpatient infection avoided) due to this intervention. Using sensitivity analyses, no plausible changes in the base case estimates altered the results of the economic model. CONCLUSIONS: An interdisciplinary approach to optimizing the timing of preo perative antimicrobial doses can impact positively on practice patterns and result in substantial cost avoidance. Costs incurred to implement such an intervention are small when compared with the annual cost avoidance to the institution.