BACKGROUND: Little is known about differences in costs to provide anesthesia care for different surgical subspecialties and which factors influence the subspecialty-specific costs. METHODS: In this retrospective study, the authors determined main cost components (preoperative visit, intraoperative personnel costs, material and pharmaceutical costs, and others) for 10,843 consecutive anesthesia cases from a 6-month period in the 10 largest anesthesia subspecialties in their university hospital: ophthalmology; general surgery; obstetrics and gynecology; ear, nose, and throat surgery; oral and facial surgery; neurosurgery; orthopedics; cardiovascular surgery; traumatology; and urology. Using regression analysis, the effect of five presumed cost drivers (anesthesia duration, emergency status, American Society of Anesthesiologists physical status of III or higher, patient age younger 6 yr, and placement of invasive monitoring) on subspecialty-specific costs per anesthesia minute were analyzed. RESULTS: Both personnel costs for anesthesiologists and total costs calculated per anesthesia minute were inversely correlated with the duration of anesthesia (adjusted R2 = 0.75 and 0.69, respectively), i.e., they were higher for subspecialties with short cases and lower for subspecialties with longer cases. The multiple regression model showed that differences in anesthesia duration alone accounted for the majority of the cost differences, whereas the other presumed cost drivers added only little to explain subspecialty-specific cost differences. CONCLUSIONS: Different anesthesia subspecialties show significant and financially important differences regarding their specific costs. Personnel costs and total costs are highest for subspecialties with the shortest cases. Other analyzed cost drivers had little effect on subspecialty-specific costs. In the light of these cost differences, a detailed cost analysis seems necessary before the profitability of an anesthesia subspecialty can be assessed.
BACKGROUND: Little is known about differences in costs to provide anesthesia care for different surgical subspecialties and which factors influence the subspecialty-specific costs. METHODS: In this retrospective study, the authors determined main cost components (preoperative visit, intraoperative personnel costs, material and pharmaceutical costs, and others) for 10,843 consecutive anesthesia cases from a 6-month period in the 10 largest anesthesia subspecialties in their university hospital: ophthalmology; general surgery; obstetrics and gynecology; ear, nose, and throat surgery; oral and facial surgery; neurosurgery; orthopedics; cardiovascular surgery; traumatology; and urology. Using regression analysis, the effect of five presumed cost drivers (anesthesia duration, emergency status, American Society of Anesthesiologists physical status of III or higher, patient age younger 6 yr, and placement of invasive monitoring) on subspecialty-specific costs per anesthesia minute were analyzed. RESULTS: Both personnel costs for anesthesiologists and total costs calculated per anesthesia minute were inversely correlated with the duration of anesthesia (adjusted R2 = 0.75 and 0.69, respectively), i.e., they were higher for subspecialties with short cases and lower for subspecialties with longer cases. The multiple regression model showed that differences in anesthesia duration alone accounted for the majority of the cost differences, whereas the other presumed cost drivers added only little to explain subspecialty-specific cost differences. CONCLUSIONS: Different anesthesia subspecialties show significant and financially important differences regarding their specific costs. Personnel costs and total costs are highest for subspecialties with the shortest cases. Other analyzed cost drivers had little effect on subspecialty-specific costs. In the light of these cost differences, a detailed cost analysis seems necessary before the profitability of an anesthesia subspecialty can be assessed.
Authors: J-P Braun; M Walter; M Lein; J Roigas; B Schwilk; M Moshirzadeh; K Eveslage; B Rehberg-Klug; D Hansen; C Spies Journal: Anaesthesist Date: 2005-12 Impact factor: 1.041