Impact of Radiation Oncology Advanced Alternative Payment Model on Black Americans

Abstract

<h3>Purpose/Objective(s)</h3> In January 2023, the Centers for Medicare and Medicaid Services (CMS) will implement the Radiation Oncology (RO) Alternative Payment Model (APM) to reform how cancer patients receive radiotherapy (RT) and standardize payments for services. The CMS asserts that the purpose of this model is to "reduce Medicare expenditures while preserving or enhancing the quality of care for Medicare beneficiaries." The RO Model requires mandatory participation for 16 cancer types and encompasses RT providers from "randomly" selected zip codes that includes approximately 30% of all eligible Medicare recipients for these RT claims, with a stated goal of saving $230 million over the initial 5 years the model is to be in place. The purpose of this study is to analyze the potential impact of this model on already existing demographic disparities in cancer care between APM-affected zip codes and unaffected zip codes. <h3>Materials/Methods</h3> Demographic data from the agency for Healthcare Research and Quality and data from Zip Code Tabulation Areas (ZCTAs) for affected zip codes were used to examine demographics within affected and unaffected zip codes. Specific social determinants of health (SDOH) variables such as education, food stamps, median household income, and Gini coefficient were also examined. Data collected from the Surveillance, Epidemiology, and End Results (SEER) Program was used to analyze the difference in 5-year cancer incidence based on race and gender. Each individual APM diagnosis code was analyzed according to race and gender in order to determine the number of people impacted for the 16 different cancer types included within the RO Model. <h3>Results</h3> In total, 20.2% more black persons (1.56 million) and 1.9% fewer (878,000) non-Hispanic white (NHW) persons are included in APM zip codes compared with a randomly-selected U.S. population. There was no significant difference in SDOH variables between affected and unaffected zip codes; however, there is a higher population density (1990 vs. 1273 per sq. mile) and average population (16,000 vs. 10,000 per ZCTA) in APM zip codes. When examining all cancer diagnoses, 7.9% more NHW persons (480.3 per 100,000) than black persons (445.2) were diagnosed with cancer; however, when looking at only APM cancers, 17% more black persons (391.5 per 100,000) than NHW persons (334.5 per 100,000) were diagnosed. A breakdown of race and gender disparities showed 17.4% more black men than NHW men were included in the APM diagnosis codes when compared with a randomly-selected U.S. population. Likewise, NHW women had 15.2% (456.6 per 100,000) more cancer diagnoses than black women (396.4), but when looking at only APM cancer diagnoses, that gap narrowed to 7.2% (319.2 NHW vs. 297.7 black). <h3>Conclusion</h3> These data indicate that the RO APM Model is heavily imbalanced in terms of the number of black persons mandated to participate and further optimization of this model is needed before widespread adoption.