Health and Financial Costs of Unequal Care: Colorectal Cancer as a Case Study - ABSTRACT Clinical algorithms that include race, which are often incorporated into electronic health systems meant to facilitate guideline care, are a striking example of overt and systemic differences in recommended care. Differences in care and reasons for these differences are often more difficult to identify and address. Colorectal cancer (CRC) care provides a case study. There is ample evidence of racial disparities in CRC screening and treatment, with unequal care identified at multiple steps in the diagnostic and treatment pathway. Most research has focused on differences between Black and White populations. Compared to White people, Black people are: less likely to be screened for CRC; less likely to receive endoscopic tests at high-quality facilities; more likely to be diagnosed at a later stage; less likely to receive curative treatment – even after accounting for stage at diagnosis; and have shorter stage-specific survival. These differences in care have both health and economic consequences. In addition to worse outcomes, Black people have higher CRC-attributable treatment costs. We propose to extend and apply CRC-SPIN, an established microsimulation model for CRC, to synthesize the available evidence related to CRC risk, CRC care, costs of care, and economic outcomes. We will extend CRC-SPIN, which currently simulates the overall US population by gender, to simulate the natural history of CRC among specific racial and ethnic groups represented in SEER data (Asian, Black, Latinx, and White populations). Extension of CRC-SPIN to include race/ethnicity will focus on incorporating available information about differences in CRC risk. We will also extend CRC-SPIN to simulate insurance status, which mediates the relationship between race/ethnicity and CRC care. We will use the resulting model to simulate the overall impact of disparate care on health and financial outcomes, and to identify elements of the care process that have the largest impact on outcomes to better guide health policy. Health outcomes will include life years lost, disease-free life years lost, excess CRC, and excess late-stage CRC. Financial outcomes will assess individual , provider- and societal-level costs, including screening costs, treatment costs and lost income. We will use Robust Decision Making approaches to address uncertainty in the differential risk of CRC and differential care. These analyses will assist in identify policy changes that are expected to have the greatest impact on health outcomes, and the costs of these policies.
