Health and Financial Costs of Unequal Care: Colorectal Cancer as a Case Study

摘要 人们越来越意识到美国医疗保健中的系统性种族主义。包括种族的临床算法， 这些通常被纳入电子健康系统，旨在促进指导性护理，是一个引人注目的 推荐治疗中明显和系统性差异的示例。护理差异及其原因 差异往往更难以确定和处理。结直肠癌（CRC）护理提供了一个案例 study.有充分的证据表明，在结直肠癌护理连续体的每一步都存在种族差异， 早期发现到治疗，尤其是黑人患者和白色患者之间的差异。相比 对于白色人，黑人不太可能接受CRC筛查， 高质量的设施，更有可能在后期诊断，不太可能得到治愈性治疗- 即使在考虑诊断时的分期后，也有40%的高死亡率和较短的分期特异性生存率。 这些护理方面的差异对健康和经济都有影响。除了更糟糕的结果，黑色 人们有较高的CRC归因于治疗费用。我们建议扩展和应用CRC-SPIN， 建立CRC的微观模拟模型，综合现有的种族和民族相关证据， CRC风险、CRC护理和护理费用的差异。我们将扩展CRC-SPIN，它目前模拟 总体美国人群，以模拟特定种族和族裔群体中的CRC自然史 在SEER数据中表示的（美洲印第安人/阿拉斯加原住民、亚洲人或太平洋岛民、黑人、白色和 西班牙裔/非西班牙裔）。扩展CRC-SPIN以纳入种族/族裔，将侧重于纳入现有的 关于CRC风险差异的信息。我们还将扩展CRC-SPIN以模拟患者特征 除了与筛选相关的种族/民族之外，例如介导关系的保险状况 种族/民族和CRC护理之间的关系。我们将使用生成的模型来模拟 不同的护理对CRC结果的影响，并确定护理过程中对 以更好地指导卫生政策。健康结果将包括生命年损失、无病生命年损失、 过多的CRC和过多的晚期CRC。财务结果将评估社会成本，包括筛查 总体和特定种族/族裔群体的医疗费用、治疗费用和收入损失。我们将使用鲁棒 决策方法，以解决CRC的不同风险和不同CRC护理的不确定性。 我们将使用该模型来预测旨在减少种族/民族差异的政策方案的影响， 儿童权利委员会协助确定减少儿童权利委员会种族/族裔差距的最有效政策方案。

ABSTRACT There is increasing awareness of systematic racism in US health care. 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 every step of the colorectal cancer care continuum, from early detection to treatment, especially for differences between Black patients and White patients. 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 40% higher mortality and 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 racial and ethnic differences in CRC risk, CRC care, and costs of care. We will extend CRC-SPIN, which currently simulates the overall US population, to simulate the natural history of CRC among specific racial and ethnic groups represented in SEER data (American Indian/Alaska Native, Asian or Pacific Islander, Black, White and Hispanic/non-Hispanic). 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 patient characteristics beyond race/ethnicity that are related to screening, such as insurance status, which mediate the relationship between race/ethnicity and CRC care. We will use the resulting model to simulate the overall impact of disparate care on CRC 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 societal costs, including screening costs, treatment costs and lost income both overall and for specific racial/ethnic groups. We will use robust decision making approaches to address uncertainty in the differential risk of CRC and differential CRC care. We will use the model to project the impact of policy scenarios designed to reduce racial/ethnic disparities in CRC to assist in identify the most effective policy scenarios for reducing racial/ethnic disparities in CRC.