Spencer S Liu1, Raymond S John. 1. Department of Anesthesiology, Hospital for Special Surgery, 535 E 70th St, New York, NY 10021, USA. liusp@hss.edu
Abstract
BACKGROUND AND OBJECTIVES: Ultrasound guidance for regional anesthesia has increased in popularity. However, the cost of ultrasound versus nerve stimulator guidance is controversial, as multiple and varying cost inputs are involved. Sensitivity analysis allows modeling of different scenarios and determination of the relative importance of each cost input for a given scenario. METHODS: We modeled cost per patient of ultrasound versus nerve stimulator using single-factor sensitivity analysis for 4 different clinical scenarios designed to span the expected financial impact of ultrasound guidance. RESULTS: The primary cost factors for ultrasound were revenue from billing for ultrasound (85% of variation in final cost), number of patients examined per ultrasound machine (10%), and block success rate (2.6%). In contrast, the most important input factors for nerve stimulator were the success rate of the nerve stimulator block (89%) and the amount of liability payout for failed airway due to rescue general anesthesia (9%). Depending on clinical scenario, ultrasound was either a profit or cost center. CONCLUSIONS: If revenue is generated, then ultrasound-guided blocks consistently become a profit center regardless of clinical scenario in our model. Without revenue, the clinical scenario dictates the cost of ultrasound. In an ambulatory setting, ultrasound is highly competitive with nerve stimulator and requires at least a 96% success rate with nerve stimulator before becoming more expensive. In a hospitalized scenario, ultrasound is consistently more expensive as the uniform use of general anesthesia and hospitalization negate any positive cost effects from greater efficiency with ultrasound.
BACKGROUND AND OBJECTIVES: Ultrasound guidance for regional anesthesia has increased in popularity. However, the cost of ultrasound versus nerve stimulator guidance is controversial, as multiple and varying cost inputs are involved. Sensitivity analysis allows modeling of different scenarios and determination of the relative importance of each cost input for a given scenario. METHODS: We modeled cost per patient of ultrasound versus nerve stimulator using single-factor sensitivity analysis for 4 different clinical scenarios designed to span the expected financial impact of ultrasound guidance. RESULTS: The primary cost factors for ultrasound were revenue from billing for ultrasound (85% of variation in final cost), number of patients examined per ultrasound machine (10%), and block success rate (2.6%). In contrast, the most important input factors for nerve stimulator were the success rate of the nerve stimulator block (89%) and the amount of liability payout for failed airway due to rescue general anesthesia (9%). Depending on clinical scenario, ultrasound was either a profit or cost center. CONCLUSIONS: If revenue is generated, then ultrasound-guided blocks consistently become a profit center regardless of clinical scenario in our model. Without revenue, the clinical scenario dictates the cost of ultrasound. In an ambulatory setting, ultrasound is highly competitive with nerve stimulator and requires at least a 96% success rate with nerve stimulator before becoming more expensive. In a hospitalized scenario, ultrasound is consistently more expensive as the uniform use of general anesthesia and hospitalization negate any positive cost effects from greater efficiency with ultrasound.