Population-Based Payment Models: Overcoming Barriers, Accelerating Adoption

Health care payment systems are undergoing a dramatic transformation, shifting away from traditional fee-for-service models and toward those that better reward providers for the quality of care they deliver to their patients, rather than the volume. One of the vehicles driving this change has been the emergence of Alternative Payment Models (APMs). These APMs are transforming how payers and providers work together, because they require mutually agreed-upon goals and collaborative efforts to achieve cost and quality targets.

On the spectrum of APMs, population-based payment (PBP) models are the most comprehensive. A key strategy for moving from volume to value, these models reward providers for meeting population-level targets. The core premise of a PBP model is that providers are accountable for patient-centric care for a specific population over a fixed timeframe and across the full continuum of care.

PBP models reside in Categories 3 and 4 of the APM Framework developed by the LAN’s Alternative Payment Model Framework and Progress Tracking Work Group. PBP models in both categories hold providers accountable for the full continuum of patient care, from preventive to end-of-life care. The models are structured in a way that encourage providers to deliver high-quality, well-coordinated, person-centered care within a defined population-based budget.    

Aligning payer principles and practices

To make these wins a reality, alignment among public and private payers on principles, practices, and key elements of methodology, when possible, will help to make participation in PBP models an attractive proposition for providers. Alignment should alleviate a pressing provider problem, namely, the administrative burden of responding to the varying requirements of multiple payer models. Unfortunately, differences in the ways the elements of PBP models are implemented in the public and private sectors—and even within a single market—vary considerably and often lack alignment. The resulting administrative burden is distracting and without value to the patients these models serve. the LAN’s PBP Work Group is addressing four priority areas essential to accelerating adoption of PBP models:  patient attribution, financial benchmarking, data sharing, and performance measurement. By developing a multi-stakeholder approach, the PBP Work Group hopes to increase the adoption and long-term success of PBP models by ensuring payers and providers are working together to identify and address barriers to implementation.

Attributing patients to providers

Patient attribution, the process of identifying the population that a provider organization is agreeing to be accountable for, is a fundamental element of PBP models that makes it possible for the provider organization to proactively and effectively manage care and costs for the covered population. When it is available, patient self-reported information about the provider they consider to be their regular personal doctor should be considered the gold standard for attribution. However, if patient self-reported information is unavailable, empirical evidence strongly supports the accuracy of attribution through careful and systematic use of claims or encounter data. The PBP Work Group’s Patient Attribution White Paper highlights ten recommendations to guide the attribution process.

Assessing financial benchmarks

Setting appropriate benchmarks in a PBP model is essential to their success. These benchmarks need to reflect the priorities of purchasers, payers, patients, and communities to reduce health care spending in a timely manner and a realistic assessment of the pace at which providers can make the changes needed. Establishing and maintaining financial benchmarks, while important to all stakeholders, requires a fundamentally different relationship between payers and providers. At the outset, the need for transparency and trust between both groups is paramount. Both must have a mutual understanding of risk-sharing parameters and the target of the financial benchmark, as well as the ability to adapt to unforeseen events, such as the approval of a new blockbuster drug.

The PBP Work Group’s Financial Benchmarking White Paper provides a blueprint for establishing and updating financial benchmarks in PBP models, with a discussion of approaches to risk adjustment. We recommend payers and providers create a shared goal to move away from historic provider benchmarks to regional and, ultimately, national benchmarks over a period of time. One issue for consideration is the time it takes to converge on a regional or national benchmark. During that time, provider organizations may succeed, improve, or fail based on performance. Meeting the financial benchmark is one measure of success.

Accelerating adoption

PBP Work Group members recently released a draft Performance Measurement White Paper and are developing a draft Data Sharing White Paper. The draft Performance Measurement White Paper is open for public comment through May 23. Together, the recommendations in the Work Group’s papers provide a solid foundation to address key barriers to accelerating PBP model adoption. As providers and payers reinvent their relationship and reinvest in effective and sustainable ways to serve their shared constituencies, PBP models can deliver on their promise of high-value, patient-centric care.

Please note that guest blogs from Guiding Committee and Work Group members represent the views of the individual authors and do not represent official positions of the Guiding Committee, Work Groups, CAMH, or CMS.

Glenn Steele, Jr.

Mr. Steele serves as co-chair of the Health Care Payment Learning & Action Network’s Population-Based Payment Work Group. He is Chairman of xG Health Solutions, an independently operated venture launched by Geisinger Health System to help health care organizations create value and improve quality by leveraging Geisinger intellectual property and expertise on issues such as population-health data analytics, care management, and health information technology.