ISPOR 22nd Annual International Meeting
Boston, MA, USA
Cost Studies (CS)
Budget Impact (BI)
ECONOMIC ANALYSIS OF QUANTAFLO COMPARED WITH DOPPLER ABI, FOR DETECTION OF PERIPHERAL ARTERY DISEASE: A U.S. HOSPITAL PERSPECTIVE
Barclay B1, Ferko N2, Corral M3 1C.R. Bard Inc., Murray Hill, NJ, USA, 2Cornerstone Research Group Inc., Burlington, ON, Canada, 3C.R. Bard Inc., Murray Hill, ON, Canada
OBJECTIVES: The prevalence of peripheral artery disease (PAD) is high, however physician awareness and involvement in diagnosis can be low. An in-office, automated, and quick measurement system, Quantaflo, has been shown to help detect PAD in patients where it was previously unrecognized. An economic analysis was conducted to compare the Quantaflo PAD test with Doppler Ankle Brachial Index (ABI) from the U.S. provider perspective in patients with suspected PAD. METHODS: The analysis was based on 96 (Doppler) and 128 (Quantaflo) patients tested per month for PAD at a single healthcare facility. Testing time per patient was assumed to be 20 minutes with Doppler and 5 minutes with Quantaflo. Prospective, multi-center study results reported Device sensitivity/specificity values of: 54.7%/94.3% and 89.5%/90.0% for Doppler and Quantaflo respectively. Cost parameters included device rental (Quantaflo) or capital costs amortized over useful life (Doppler), maintenance or accessory costs, labor testing costs. Results were expressed over one month for the total population as well as per patient. One-way sensitivity analyses were completed on core model parameters. RESULTS: In the model simulation, Quantaflo was predicted to yield cost savings per test compared with Doppler (i.e., $5.15 vs. $6.16 per test). In total, the model predicted that Quantaflo would result in 32 additional patients being tested per month, and 6 additional potential PAD patients identified based on overall time savings. The average cost per test, as a proportion of reimbursement, was predicted to be 3.7% with Quantaflo and 4.4% with Doppler. Cost saving results remained robust across various sensitivity analyses. CONCLUSIONS: The Quantaflo PAD test was predicted to provide cost savings on a per test basis for U.S. providers primarily due to time saved on test administration, while potentially increasing the detection of PAD patients. Future study should involve further real-world analysis of potential cost-efficiencies with this product.