Case Study
Paying for Value: Improving Outcomes, Costs, and Access through a Condition-based Bundle Payment Model
Published date
Topics
Aortic stenosis (AS) affects around 1.5 million people in the United States and occurs when the heart’s aortic valve narrows, potentially causing heart failure, syncope, and sudden cardiac death. Chronically underdiagnosed, AS is often only identified when the severity of the disease has progressed to the point where patients need an aortic valve replacement. Currently, the intervention can either be performed through surgical aortic valve replacement (SAVR) or transcatheter aortic valve replacement (TAVR). While there are benefits and risks associated with either intervention, traditional procedure-based reimbursement may deter provider systems from building capacity to offer both options to appropriately meet patient needs.
In this paper we outline a conceptual design for a bundled payment model agnostic to procedure type, a first step to a condition-based AS model that can reduce or eliminate misaligned incentives around treatment choice. The conceptual model we propose seeks to promote improved long-term outcomes by aligning payment with appropriate choice of procedure (including device), promoting shared decision-making between patients and providers, and coordination of longer-term post-acute care. We developed this proposal in response to the FY2020 President’s Budget calling on CMMI to identify more bundled payment arrangements for high-value devices, and incorporate device manufacturers into risk-sharing;1 evolving label expansion of TAVR devices by the Food and Drug Administration (FDA); and CMS’s relaxed procedure volume requirements in their coverage criteria. Ideas presented in this paper are the first steps to identifying an opportunity for CMMI to test an innovative approach to payment for medical device use in the broader health care continuum. We hope to ultimately design, with the input of all stakeholders affected – CMS, commercial payers, physicians, hospital administrators and patients – an analysis of Medicare data, an actionable payment model that expands bundles to encompass longer time horizons, improved condition management, that better account for patient and provider risk factors, gives providers flexibility to choose the treatment that will result in the best long-term outcomes, and involves manufacturers in sharing risk for quality and costs.
Duke-Margolis Authors
Christina Silcox, PhD
Research Director, Digital Health
Adjunct Assistant Professor
Senior Team Member
Margolis Core Faculty
Beena Bhuiyan Khan, MSc
Research Director for Payment and Coverage Policy
Aparna Higgins
Senior Policy Advisor
Marianne Hamilton Lopez, PhD, MPA
Senior Research Director, Biomedical Innovation
Faculty Director of the Duke-Margolis Postdoctoral Associates & Affiliated Fellows Program
Adjunct Associate Professor
Senior Team Member
Margolis Core Faculty
Mark McClellan, MD, PhD
Director of the Duke-Margolis Institute for Health Policy
Robert J. Margolis, MD, Professor of Business, Medicine and Policy
Margolis Executive Core Faculty