Developing an oncology payment model presents unique challenges to healthcare stakeholders due to the high cost, complexity, and variability of cancer treatment in a rapidly evolving clinical landscape. A well-structured model must balance access to high-quality care with financial sustainability for risk-bearing and risk-delegating entities. Here are six things to consider when designing an oncology payment model.

1. Defining the population: Service-based vs. episode-based approaches to an oncology payment model

In service-based models, only patients receiving specific cancer services are in scope. In episodic models, services following an initiating event (such as infused chemotherapy) are at risk. Episodes typically focus on cancer patients receiving active treatment, as follow-up care for patients in remission is usually low cost with little variability.

The choice of which treatments trigger an episode will influence which costs are included, which providers may participate, and how they may be held accountable. The four main treatment types that commonly initiate an oncology care episode are:

• Medical benefit chemotherapy: Drugs (intravenous or otherwise) administered by a provider in a physician’s office or outpatient facility
• Pharmacy benefit chemotherapy: Including self-administered drugs (oral or otherwise) taken at home and white-bagged drugs administered by a provider
• Radiation therapy: Targeted application of ionizing radiation administered in a physician’s office or outpatient facility
• Surgery: Surgical removal of tumors, commonly performed in the facility outpatient or hospital inpatient setting (typically for solid organ cancer)

Each treatment may be included in evidence-based clinical guidelines and features different cost structures and utilization patterns. An episode that begins with chemotherapy may have different downstream costs compared to one initiated by surgery. Cost variability at the patient level is also influenced by the fact that oncology patients often receive multimodal treatments combining treatment types and medical and pharmacy benefits. Cost variability at the provider level is highly influenced by the number of patients under the provider’s care, where the threshold for credibility may be higher than other specialty models due to material variation in costs from one patient to the next.

2. Defining services at risk within an oncology payment model: Total cost of care vs. select services

The most common approaches to defining the scope of financial responsibility in an oncology payment model are:

1. Total cost of care (TCOC)
2. Select services

The choice has a significant influence on risks, incentives, and costs.

TCOC

Providers are held accountable for all services utilized during an oncology episode, including inpatient admissions, outpatient services, drugs (through the medical or pharmacy benefit), and other supportive care. This may include management of chronic conditions, which is typically affected by cancer treatment. Care for injuries or illnesses unrelated to cancer may be included in an episode, as can elective care (although patients rarely seek that when undergoing cancer treatment).

In addition, TCOC provides more care improvement and cost reduction opportunities for patients undergoing complex, costly treatment that typically impacts multiple body systems. It also encourages holistic care management and minimization of unnecessary costs (such as avoidable hospitalizations from treatment complications).

Select services

Providers are held accountable only for oncology-specific services aligned with treatment pathways and clinical guidelines, such as chemotherapy drugs, radiation therapy, cancer-related surgery, and cancer-related hospitalizations. The select services approach may be more appealing to providers because included services are specific to cancer treatment, under providers’ direct control, and can be tailored to the provider’s specific intervention as applicable.

3. Setting an oncology payment model target price or benchmark to reflect real-world experience

An adequate and appropriate target price helps avoid situations in which oncology payment models overestimate costs (leading to overpayment compared to fee-for-service) or underestimate them (placing undue financial risk on providers). Clinical guidelines alone are typically insufficient for this exercise. Real patient experience often differs significantly from clinical guidelines due to:

• Health status, including comorbidities and social determinants of health
• Provider practice variations
• Patient preferences
• Unexpected complications

Using real-world claims data ensures that the target price or benchmark reflects actual treatment patterns and costs, rather than relying solely on idealized guidelines that are developed from clinical trial experience.

4. Accounting for new cancer therapies and expanding indications within an oncology payment model

Oncology is a rapidly evolving area of medicine. New therapies and expansions of existing therapies through new indications approved by the Food and Drug Administration mean claims experience may not reflect current costs, with significant implications for clinical guidelines, cost trends, and payment models.

For example:

• New therapies are often expensive. Targeted therapies and immunotherapies can be orders of magnitude more costly than traditional cytotoxic chemotherapy. Providers may be unfairly penalized for prescribing or administering the latest and most effective therapies following clinical guidelines without payment model adjustments.
• Expanded indications can change care patterns and costs. Therapies approved for certain conditions may later be approved for different cancer types, earlier stages, or earlier lines of therapy. Payment models should consider adjustments to support evidence-based treatment.

Without a financial adjustment mechanism for new therapies and expanded indications for existing therapies, payment models may undercompensate providers when high-cost treatments become standard of care.

5. Adjusting costs for risk variability outside provider control

Many cost drivers of oncology care are entirely outside providers’ control, such as demographics, performance status, comorbidities, cancer type, cancer stage, and cancer biomarkers such as HER2 in breast cancer. Additionally, cancer biomarkers and stage data (other than metastatic disease) are unavailable or underreported in claims data, making it challenging to connect treatment decisions and costs to the stage or progression of cancer in specific patients.

Without adequate risk adjustment, providers may be penalized for treating patients with advanced or complex disease. For these reasons, oncology payment models should avoid penalizing providers for factors they do not control, such as:

• Age, sex, and other demographic characteristics
• Use and sequence of treatment modalities
• Total treatment duration
• Stage and biomarker information such as metastatic disease and, for specific cancer types, estrogen receptor status and hormone resistance
• Comorbidities
• Performance status indicators, such as institutional versus community residence and use of durable medical equipment
• Presence and timing of prior cancer treatments

Standard risk adjustment models do not adequately account for most of these factors, and are often used to predict total costs for a general population. Risk adjustment tailored to the scope of services and population of interest is key to ensuring providers are fairly compensated for managing more complex cases.

6. Ensuring high-quality care through quality measurement within an oncology payment model

Oncology payment models should not sacrifice high-quality patient care for cost containment. For example, oncology treatments may lead to severe and potentially avoidable adverse events, such as hospitalizations due to complications from chemotherapy, infections related to immunosuppression, and severe side effects from radiation therapy.

By integrating quality metrics into the payment model, organizations can align financial incentives with high-quality care, ensuring providers focus on delivering optimal cancer treatment outcomes rather than just reducing costs. While some quality measures can be determined from claims data, certain important patient-reported outcomes (such as symptoms) require data collection from patients that may be too administratively burdensome to be included in oncology payment models.

Common claims-based quality measures include:

• Minimization of hospitalizations and emergency department visits for treatment-related complications
• Adherence to evidence-based guidelines for cancer treatments and follow-up care
• Appropriate use of pain and symptom management protocols to improve patient comfort during treatment and at end of life

Comprehensive oncology payment models commonly include quality measurement to incentivize high-quality care.

Final thoughts on developing an oncology payment model

Designing an effective oncology payment model requires using relevant data to balance clinical, financial, and quality factors. Effective models:

• Clearly define the population to establish accountability for episode-based payment models
• Determine the scope of financial risk, whether TCOC or select services
• Establish realistic target pricing that reflects real-world experience
• Adjust for new therapies, expanded indications, and evolving guidelines to ensure fair payment structures
• Implement robust risk adjustment for demographic and clinical factors outside provider control
• Incorporate quality measures linked to patient experience and other outcomes to balance incentives for cost efficiency and high-quality care

When designing an oncology payment model, healthcare stakeholders should consider the six key factors discussed above to balance the needs of payers and providers while enabling patient access to high-quality cancer care.