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Conference Coverage

How Well Does the Enhancing Oncology Model Capture Treatment Costs in Disease Groups?

Emry Lloyd

Katherine Baker, MD, and colleagues researched how well the Enhancing Oncology Model (EOM) can capture indication-specific treatment costs of care. The EOM compares practice expenditures to their calculated benchmarks in 7 cancer types and applies clinical adjustments to account for any changes in cancer cost that occur. These adjustments are for metastatic (M0 vs M1) and HER2 cancers.  

For the study, the researchers analyzed Medicare’s Part B drug and biological average sales price to estimate the total cost of Medicare for systemic therapy over the course of 6 months for patients with breast cancer, lung cancer, and colorectal cancer. Then, following EOM methodology, they broke down the diseases by M0 vs M1 and HER2. They also considered the clinical phenotypes not covered under the EOM model, such as PD-L1 status, lymph node status, and tumor size.

After Dr Baker and colleagues accounted for EOM clinical adjustments, they found a variety of results within a 6-month period of treatment for patients’ overall treatment costs when based on the clinical features that are not captured in the EOM model. The cost of care for treatment was different by over 220-fold for M0 NSCLC, 72-fold for M0 HER2-high risk breast cancer, 7-fold for M0 HER2+ high risk breast cancer, and 6-fold for M1 colorectal cancer. 

Dr Baker and colleagues concluded that the cost differences between indication-specific treatments for diseases in the EOM model may create performance risks for participating groups. Although the EOM has attempted to reconcile the influence of clinical phenotypes that are not covered, more work needs to be done in the future. 


Baker K, Young G, Bilbrey L, et al. Heterogeneity in costs of standard-of-care drug regimens within high volume Enhancing Oncology Model disease groups: Implications for performance risk outside of a provider’s control. Presented at: the 2023 ASCO Quality Care Symposium; October 27-28, 2023; Boston, MA, and virtual; Abstract 70.
 

Sourced from the Journal of Clinical Pathways

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