Article ID: | iaor20164692 |
Volume: | 63 |
Issue: | 4 |
Start Page Number: | 772 |
End Page Number: | 788 |
Publication Date: | Aug 2015 |
Journal: | Operations Research |
Authors: | Gupta Diwakar, Mehrotra Mili |
Keywords: | information, combinatorial optimization, quality & reliability, government |
The Centers for Medicare and Medicaid Services (CMS) has introduced a ‘bundled payments for care improvement’ (BPCI) initiative. Each bundle pertains to a specific medical condition, a set of linked services, and a length of time referred to as an episode of care. Proposers choose bundles, design service chains, and propose target values of quality metrics and payments per episode. Expert panels evaluate proposals based on CMS‐announced relative weights, but there is no limit on the number of proposers that may be selected. Moreover, there is no minimum score that will guarantee selection, which makes selection uncertain for proposers. We develop normative models for the parameter selection problems faced by potential proposers within the CMS’ proposal selection process. Proposers have private information about their costs of achieving different quality targets, which determine their equilibrium responses. We show that an optimal strategy for CMS, under its current approach, may be to either announce a fixed threshold or keep the selection process uncertain, depending on market characteristics. We also formulate and solve the proposer selection problem as a constrained mechanism design problem, which reveals that CMS’ current approach is not optimal. We present policy guidelines for government agencies pursuing bundled payment innovations.