Potential Role of Network Meta-Analysis in Value-Based Insurance Design

Objectives Value-based insurance design (V-BID) has emerged as an approach to improve health outcomes and contain healthcare costs by encouraging use of high-value care. We estimated the impact of a V-BID for osteoporosis treatments using comparative effectiveness evidence and real-world data from a California health insurance plan to estimate the benefits of the design's implementation. Methods This study consisted of 4 steps. First, we reviewed randomized clinical trials including osteoporosis treatments-alendronate, ibandronate, risedronate, raloxifene, and teriparatide-reported in a recent Agency for Health Research Quality systematic review. Second, we performed a network meta-analysis to synthesize data from the clinical trials and estimate the comparative effectiveness of included treatments. Third, we implemented a V-BID by removing co-payments for the most effective treatments. Fourth, using a Monte Carlo simulation, we estimated the impact of the V-BID in terms of fracture reduction and cost-savings. Results Thirty-two randomized controlled trials were included in the network meta-analysis. We estimated that alendronate, risedronate, and teriparatide have the highest probability of being most effective across each fracture type-vertebral, hip, and nonvertebral/nonhip. After eliminating co-payments, (ie, reducing them to zero), for these treatments, we estimated the health plan would experience a 7% (n = 287) decrease in fractures and an 8% ($6.8 million) decrease in costs. Conclusions Our study illustrates the benefits of comparative effectiveness evidence in V-BID development. We show that where clinical trials are lacking, network meta-analysis can provide valuable insights into the potential clinical and economic benefits of V-BID.