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Precision in EOM Methodology Has Implications for EOM Decision Making

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The EOM prediction model and benchmarking methodology are more precise than that of the OCM, which will heighten the ability of participants to directly manage costs, including oncolytic spend.

The Enhancing Oncology Model (EOM) is an episode-based, oncology-focused payment model from the Center for Medicare & Medicaid Innovation (CMMI). The EOM will begin July 1, 2023, and is the successor to CMMI’s Oncology Care Model (OCM), which ended June 30, 2022.

The EOM methodology design was informed by learnings from the OCM; the new methodology reduces the number of included beneficiaries, reduces the monthly enhanced oncology services payment amount, and increases the level of participant risk sharing. The CMMI also refined the episode cost-prediction model to be cancer-type specific, which will improve the accuracy of benchmark prices and ultimately impact participants’ ability to earn a performance-based payment.

To examine how payment methodology changes in the EOM will impact the benchmark price calculation, Avalere assessed average benchmark prices relative to actual expenditures under the OCM and EOM methodologies for multiple myeloma and chronic leukemia.


In all seven EOM cancer types, the average EOM benchmark price is predicted to be much closer to the average total spend than the OCM benchmark price was to total spend. However, the increased accuracy of the model has differential impacts across cancer types when assessing “better” or “worse” performance relative to OCM.

Figure 1 illustrates the difference between the average total spend and benchmark price for multiple myeloma and chronic leukemia episodes under the EOM versus the OCM. The OCM prediction model’s lack of precision at the cancer-type level resulted in considerable underprediction for multiple myeloma episodes. Under the OCM, total expenditures were 19% above the benchmark price. Meanwhile, the EOM’s cancer-specific prediction model, trend factor, and novel therapy adjustment is expected to result in a more accurate benchmark price for these episodes and thus result in “better” performance (2% below benchmark).

While the OCM underprediction for multiple myeloma episodes, there was overprediction for chronic leukemia episodes. The increased accuracy in the EOM prediction model will correct for this overprediction for chronic leukemia episodes. This correction is predicted to result in “worse” performance for these episodes, with total expenditures shifting from 5% below the benchmark under the OCM to 1% above under the EOM.

Figure 1. Predicted Performance Under OCM and EOM Methodology, Multiple Myeloma and Chronic Leukemia, PP5–PP8 Average
Figure 1. Predicted Performance Under OCM and EOM Methodology, Multiple Myeloma and Chronic Leukemia, PP5–PP8 Average

Note, the values above include 6-month episodes initiated in OCM performance periods (PP) 5–8 (July 2, 2019, through July 1, 2020) and attributed to the 126 OCM practices active at the start of the last performance period (January 2, 2022). Practice-level performance varies from the overall result presented above.


Oncology practices submitted non-binding EOM applications in October 2022 and will make final participation decisions, if approved by the CMMI for model participation, in spring 2023. During the interim period, practices are evaluating participation decisions and designing care transformation strategies aimed at achieving financial success.

Given that the EOM prediction model updates will result in more precise benchmark prices, future participants will seek cost-control opportunities with greater feasibility. A recent Avalere assessment found that the majority of OCM episode costs were from oncolytics, accounting for about 75% of total episode expenditures in multiple myeloma and chronic leukemia episodes. As such, participants will likely focus on managing their oncolytic spend, as treatment selection is within their control. To manage drug costs, practices may implement EOM-preferred regimens selected by practice- or network-level decision makers and implement compliance measures to assess adherence to certain protocols.

Since prior to the launch of the OCM, Avalere has partnered with key stakeholders in oncology and hematology to assess previous OCM and future EOM practice performance, generate cancer specific insights, and create economic and budget impact models to determine effects on broader practice economics. As the oncology payment landscape evolves, Avalere is working with stakeholders to navigate implications of concurrent payment models and policies to assess impact, refine market strategy, and shape customer engagement. To better understand how the EOM and the Inflation Reduction Act will inform cancer care management considerations of costs, evidence, and clinical outcomes, connect with us.


Avalere performed this analysis using Medicare Part A/B Fee-for-Service claims and Part D prescription drug event data accessed via a research collaboration with Inovalon, Inc., and governed by a research-focused Centers for Medicare & Medicaid Services (CMS) data-use agreement. Avalere replicated the OCM and EOM program methodologies developed by CMS. This analysis includes the 126 practices active in the OCM as of January 1, 2022. The baseline period includes episodes initiated between January 1, 2012, and December 31, 2014, and the intervention period used for this analysis includes episodes initiated between July 2, 2018, and July 1, 2020 (OCM PP5–8).

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