The Future of Value-Based Care, Payment Models in Oncology

In this panel presented at the 2025 Patient-Centered Oncology Care (PCOC) Conference, hosted by The American Journal of Managed Care, oncology leaders examined the evolution in value-based care initiatives, both from government-driven models to partnerships with commercial payers and from the Oncology Care Model to the current Enhancing Oncology Model.

Lalan Wilfong, MD

Stuart Staggs, MSIE

Aaron Lyss, MBA

David Johnson, MD, MPH

Sophia Humphreys, PharmD, MHA, BCBBS

The discussion, moderated by Lalan Wilfong, MD, senior vice president for value-based care at Thyme Care, highlighted the growing complexity in balancing quality, cost, patient access, and outcomes.

“I think with any kind of value-based care model in this arena, it [has] to be very nimble and has to keep up, otherwise it’s not going to last,” said Stuart Staggs, MSIE, vice president of transformation and shared services at McKesson. “On the commercial side, they kind of try things and then stop, and then you’re trying to see something that’s going to stick; it’s just trying to navigate those waters and [putting] the patient first.”

Early value-based efforts prioritized adopting new technology and tracking quality metrics; however, as the landscape matured, scalability and standardization have become bigger challenges, given the lack of a national consensus, along with administrative burdens in documentation and reporting. Advanced therapies and innovations have further complicated payment model design, making it more difficult to leverage cost-saving opportunities and, therefore, requiring new models that can quickly adapt to changes in clinical practice and cost structures.

“I do think there is an attempt to experiment in all these different types of specialty payment model constructs,” said David Johnson, MD, MPH, chief physician executive at Atlas Oncology Partners. “There’s a limited number of contract terms and mechanics that we can use to create a value-based contract, but ultimately, what we’re trying to do is get paid for something that did not happen that was undesirable. How do we measure the counterfactual of what didn’t happen? That’s the inherent challenge in value-based payment models in general.”

The panel agreed that population-level, longitudinal payment models, as opposed to episodic or narrowly defined models, offer greater sustainability and improved outcomes but require new ways of handling risk adjustment, case mix, and rapid medical advancements. Therefore, continuous evolution and adjustment are necessary to keep pace with changes in oncology care while also aligning financial incentives with desired clinical outcomes.

Drug Market Realities

New innovations, advanced therapies, and personalized medicine have dramatically escalated expenses for health systems and payers. Although biosimilars initially provided savings, many cost-reduction opportunities have already been utilized, making further savings harder to achieve.

Today’s arrangements, such as episodic payment models and bundled payments, are increasingly challenged by new therapies that can reach very high cost levels, which are highly specific to patient subtypes. This creates unpredictability and makes standardization of care, and thus payment, difficult. The panel emphasized the need for payment models that can rapidly adjust benchmarks and risk and consider approaches where pharmaceutical manufacturers are also held accountable for therapy outcomes, especially with extremely high-cost cell and gene therapies.

“The reason why we have to figure out the answer to this question is because the math just doesn’t work in terms of when we see the rates at which we’re getting meaningfully innovative new therapies that carry substantially higher costs, constantly,” said Aaron Lyss, MBA, senior director of payment and policy innovation at OneOncology. “That is going to outpace Medicare’s ability to fund access to those therapies, and it’s going to outpace the private sector’s ability to fund access to those therapies without employers and consumers taking on much higher premium costs. That is the reality that we’re dealing with. The only way to get there, where we can afford to pay the higher cost for clinically meaningful [and] more valuable therapies, is to pay substantially less for the ones that are less clinically meaningful and less valuable. There’s no other way.”

The Population Segmentation Challenge

Patient populations in oncology are highly heterogeneous, varying by disease severity, cancer subtype, comorbidity, socioeconomic status, and other factors. Therefore, successful population-level payment models must account for a mixed cohort and fair benchmarking to adjust for these differences.

Models need to incorporate case mix adjustment and dynamically update as therapies—and thus, population risk—evolve. However, even with standardized protocols, outliers will significantly affect costs and outcomes, in which meaningful segmentation is required.

Additionally, stratifying patient results by ethnicity or area deprivation index has revealed persistent outcome gaps, underscoring the importance of considering social determinants of health when evaluating both clinical and financial performance in population contracts.

Where Does Health Equity Fit In?

Health equity is a vital but often underemphasized element in value-based care and payment models. Health equity should remain front and center, as outcome disparities exist among ethnic groups, even when patients have the same insurance and socioeconomic status.

“In my view, this is something we need to always consider,” said Sophia Humphreys, PharmD, MHA, BCBBS, who was executive director of pharmacy at Providence at the time of the PCOC meeting. “Not that we have to look for studies that incorporate every racial representation, but when we consider value-based care, when we consider offering a population health contract…in my mind, the population includes everyone.”

Adjusting payment benchmarks and risk arrangements to account for the higher severity or disparities or disparate outcomes often found in certain demographic groups can ensure that providers are not financially penalized for caring for higher-risk populations. Additionally, using real-world data and clinical trial evidence to identify where these disparities exist and then designing performance metrics or incentive structures that reward improvements in equity could help address these gaps.

By implementing these strategies, the panelists believe that value-based models can address current inequities in oncology care and drive improvements for disadvantaged populations.