FINANCIAL IMPACT OF USING AN INNOVATIVE DEVICE ALGORITHM TO AUTOMATICALLY OPTIMIZE BIVENTRICULAR PACING DEVICES IN JAPAN
Author(s)
Mura T1, Kamogawa S1, Taguchi W1, Tsintzos S2, Bril SL2, Sato M1
1Medtronic Japan Co, Ltd, Tokyo, Japan, 2Medtronic Global CRDM Headquarters, Mounds View, MN, USA
OBJECTIVES: Incremental improvements are inherent in medical devices; many of these can offer significant financial benefits which, ultimately, improve the cost-effectiveness of already established technologies. Biventricular pacing, commonly combined with a defibrillator (“Cardiac Resynchronization Therapy – Defibrillator” or CRT-D), has been widely used in patients with Heart Failure (HF) to increase survival, improve QoL, and reduce HF hospitalizations. Nevertheless, traditional CRT-D devices require periodic manual reprogramming (a.k.a. “optimization”) guided by echocardiography. Newer devices equipped with innovative algorithms (AdaptivCRT™, Medtronic, MN, USA) monitor heart electrical activity and automatically reprogram the device once-per-minute. In addition to eliminating the manual process, AdaptivCRT™ appeared to positively impact patient allocation to functional classes (as defined by the New York Heart Association – NYHA) against traditional echo-based device optimization. We investigated the financial implications of AdaptivCRT™ in Japan. METHODS: We conducted a Cost-Minimization Analysis (CMA), comparing AdaptivCRT™ with traditional optimization, using Markov processes. Patients progress from early-stage NYHA classes to more advanced disease, or death. The initial allocation of patients to the classes and the transition probabilities were based on the aCRT RCT. Each NYHA class is associated with higher levels of costs. We used the Japanese fee schedule, local HF treatment guidelines and prescription drug labelling to assess resource utilization within each class. RESULTS: Assuming 3,200 patients (the approximate number of Japanese CRT-D patients per annum), our model predicts overall cohort costs (excluding initial implant costs) of ¥16,545M (USD$165M) with AdaptivCRT™ and ¥17,809M (USD$178M) without. This equates to savings of approximately USD$13M overall, or USD$4,000 per patient. CONCLUSIONS: AdaptivCRT™ use appears associated with significant cost-offsets driven by superior outcomes. This demonstrates that incremental device therapy improvements can provide clinical and economic value. Further research should examine AdaptivCRT™ impact on healthcare utility and improvement in the overall cost-effectiveness of CRT-Ds.
Conference/Value in Health Info
2014-05, ISPOR 2014, Palais des Congres de Montreal
Value in Health, Vol. 17, No. 3 (May 2014)
Code
PCV38
Topic
Economic Evaluation
Topic Subcategory
Budget Impact Analysis, Cost-comparison, Effectiveness, Utility, Benefit Analysis
Disease
Cardiovascular Disorders