Abstract

6651 Background: The Oncology Care Model (OCM) was a value-based care program implemented by the Centers for Medicare & Medicaid Innovation (CMMI) between July 1, 2016, and June 30, 2022, that aimed to provide high-quality care while reducing total cost of care (TCOC). In 2023 CMS plans to implement the Enhancing Oncology Model (EOM), which builds on lessons learned from the OCM. Over 200 novel therapies were approved by the FDA between 2016 and 2022. Novel therapies come with increased cost, leading to concerns that the model could discourage use of novel therapies. CMMI implemented a novel therapy adjustment (NTA) to offset the increased cost of these expensive therapies, when a practice has a higher proportion of novel therapy expenditures. A key change in the EOM is the calculation for NTA at the individual cancer type level compared to full population of episodes in the OCM. We studied the impact of moving from a population-based NTA to a cancer type-based NTA calculation. Methods: Claims and performance data from 10 performance periods (PP) in the OCM (PP1 to PP10) for 14 practices in The US Oncology Network were reviewed. Descriptive statistics for the simulation were evaluated to determine changes from population-based NTA to cancer-based NTA. The OCM NTA methodology was deconstructed to apply the NTA at a cancer type level. We performed a simulation exercise by applying cancer specific NTA methodology systematically to the claims and performance data. We then evaluated the impact of NTA on the EOM cancer types. Results: 20.95% of the TCOC was attributed to novel therapy expenditures in the OCM for all cancer types (range 0.0% - 49.4%) vs 24.2% (range - 3.5% - 43.7%) of TCOC for the EOM cancer types (high-risk breast, colon, lung, high-risk prostate, myeloma, lymphoma and chronic leukemia) in the same time-frame. 75.5% of the novel therapy expenditures in the OCM came from the 7 EOM cancers. In the OCM only 31.8% of eligible performance periods received a NTA. Had the NTA been applied at the cancer type level, 49.5% of eligible episodes would have received an adjustment. The top cancers with the most novel therapy use as a percentage of TCOC were lung, myeloma and high-risk/castrate-resistant prostate. The NTA for these practices adjusted the benchmark by an average of 0.56% (range - 0.21% to 1.1%) over 10 periods. When applied at a cancer type level, NTA increased the adjustment by 3 times to an average of 1.73% (range - 1.16% to 2.11%). Conclusions: The NTA applied at a cancer type level would have resulted in more instances where practices would have qualified for a benchmark adjustment. We believe that the EOM approach to NTA applied at a cancer type level is more favorable for participating practices and provides valuable financial protection when incorporating clinically appropriate novel therapy for cancer treatment. We commend CMMI for making improvements to the NTA risk adjustment methodology within the EOM.

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