Reducing health disparities in foregut cancers by using modifiable barriers to predict risk for inequitable care: a novel implementation science-based approach

项目总结 年，食道癌、胃癌、肝癌、胆道癌和胰腺癌约占新死癌症的20%。 美国每年都会出现这种情况，预计在未来十年中，发病率将增加近70%。这些 是侵袭性的恶性肿瘤，有复杂的治疗方法，需要协调的、专门的多学科护理。确实有 中国循证指南协调治疗(GCT)的使用存在显著的种族和地域差异 前肠癌症。种族和地理位置是癌症护理过程中多个潜在可改变的障碍的替代者 连续体，威胁到获得和接受护理。识别这些障碍对于缩小差距至关重要。 准确识别有非GCT风险的患者是进行干预的重要第一步。然而，目前还没有筛选工具 以确定有非GCT风险的患者。该项目旨在解决前景中的种族和基于位置的差异 通过使用混合方法研究开发风险预测模型和基于临床的筛查工具，利用 可修改的障碍，以确定未接受GCT的风险患者。总之，这在临床上是适用的，在统计上也是如此 有效的模型和高收益的筛查工具将为一种新兴的模型提供信息，该模型可以识别有风险的非 接受护理，并促进个性化、以解决方案为重点的干预措施的管理，这些干预措施可以将 护理过程。 我的长期目标是成为一名独立的研究员，专注于识别、理解和解决 在获得癌症护理方面的差距。这个职业发展奖将帮助我实现目标，填补在 通过个性化培训计划获得知识和技能，包括授课、小长假、体验式 三个领域的培训和指导：(1)注重以病人为中心的混合方法(2)统计 建模和测量发展；(3)实施科学。这项培训计划将支持我提议的项目 并使我能够转变为一名独立的外科医生兼科学家。具体目标是：(1)找出获取 通过以患者为中心和利益相关者知情的方法对直肠癌患者进行GCT(2)以检查 使用定量建模和(3)开发和试点测试的可修改障碍预测非GCT风险的程度 一种基于临床的筛查工具，用于前瞻性地识别有非GCT风险的患者。 这一提议在探索潜在的可修改的壁垒方面是新颖的，以指导模型的开发 预测接受较差的护理，以及基于诊所的筛查工具，以确定在获得医疗服务方面存在差异的风险个人 肿瘤科护理。虽然目前有一系列成功的干预措施，如患者导航，但已显示 在减少治疗差异方面，临床医生没有简化的方法来识别有风险的非 GCT。这项建议将允许以一致的方式识别有健康差异(非GCT)风险的患者 这项研究的结果将用于申请R01到 前瞻性评估所开发的筛查工具在多机构研究中预测护理差异的效用 并通过种族/民族、地点(农村与城市)、社会经济地位和制度类型来测试其不变性。

PROJECT SUMMARY Foregut (esophageal, gastric, liver, biliary and pancreatic) cancers account for approximately 20% of new cancer deaths in the United States each year, with an incidence that is projected to increase by almost 70% over the next ten years. These are aggressive malignancies, with complex therapies that require coordinated, specialized multidisciplinary care. There are significant racial and location-based disparities in the utilization of evidence-based guideline concordant therapy (GCT) in foregut cancers. Race and location serve as proxies for multiple, potentially modifiable, barriers along the cancer care continuum, that threaten access to and receipt of care. Identifying these barriers is critical to reduce disparities. Accurate identification of patients at risk for non-GCT is a vital first step to intervene. However, there is no screening tool to identify patients at risk for non-GCT. This project aims to address racial and location-based disparities in foregut cancers by using mixed methods research to develop a risk prediction model and clinic-based screening tool that utilizes modifiable barriers to identify patients at risk for non-receipt of GCT. Together, this clinically applicable and statistically valid model and the high-yield screening instrument will inform an emerging model that identifies patients at risk for non- receipt of care, and facilitates the administration of personalized, solution-focused interventions that can redirect the course of care. My long-term objective is to become an independent researcher focused on identifying, understanding and addressing disparities in access to cancer care. This career development award will help achieve my objective by filling gaps in knowledge and skills through a personalized training program that will include didactics, mini-sabbaticals, experiential training and mentorship in three areas: (1) mixed methods with a focus on patient-oriented research (2) statistical modeling and measure development and (3) implementation science. This training plan will support my proposed project and enable my transition to an independent surgeon-scientist. The specific aims are (1) to identify barriers in access to GCT in patients with foregut cancers through a patient-centric and stakeholder-informed approach (2) to examine the extent to which modifiable barriers predict risk for non-GCT using quantitative modeling and (3) to develop and pilot test a clinic-based screening tool to prospectively identify patients at risk for non-GCT. This proposal is novel in its exploration of underlying modifiable barriers to inform the development of a model that predicts receipt of inferior care, and a clinic-based screening tool to identifiy individuals at risk for disparities in access to oncologic care. While there are currently a range of successful interventions such as patient navigation that have shown promise in decreasing treatment disparities, there is no streamlined way for clinicians to identify patients at risk for non- GCT. This proposal will allow for the identification of patients at risk for health disparities (non-GCT) in a consistent way across providers and embedded in health systems.The results of this study will be used to apply for an R01 to prospectively evaluate the utility of the developed screening tool in a multi-institution study to predict disparities in care and test its invariance by race/ethnicity, location (rural versus urban), socioeconomic status and type of institution.