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

项目摘要 前肠（食管癌、胃癌、肝癌、胆管癌和胰腺癌）癌约占20%的新发癌症死亡， 在美国，每年的发病率预计将在未来十年内增加近70%。这些 是侵袭性恶性肿瘤，需要协调的、专门的多学科护理的复杂疗法。有 在使用循证指南一致性治疗（GCT）方面存在显著的种族和地区差异， 前肠癌种族和地理位置是癌症治疗过程中沿着多个潜在的、可改变的障碍的代表 这是一个连续体，威胁到获得和接受护理的机会。查明这些障碍对减少差距至关重要。 准确识别有非GCT风险的患者是干预的重要第一步。但是，没有筛选工具 以识别非GCT风险患者。该项目旨在解决前肠的种族和位置差异， 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， 可修改的障碍，以识别存在未接受GCT风险的患者。总之，这一临床适用性和统计学 有效的模型和高产量的筛选工具将告知一个新兴的模型，确定患者的风险， 接受护理，并促进个性化的管理，以解决方案为重点的干预措施，可以重新定向 护理过程。 我的长期目标是成为一名独立的研究人员，专注于识别，理解和解决 在获得癌症护理方面的差距。这个职业发展奖将有助于实现我的目标，填补空白， 知识和技能，通过个性化的培训计划，将包括教学法，迷你休假，体验 在三个领域进行培训和指导：（1）混合方法，重点是以患者为导向的研究（2）统计 建模和测量发展;（3）实施科学。这个培训计划将支持我提出的项目 让我能够成为一名独立的外科医生兼科学家具体目标是：（1）查明获得 GCT在前肠癌患者中通过以患者为中心和患者知情的方法（2）检查 使用定量建模和（3）开发和试点测试可修改障碍预测非GCT风险的程度 一种基于临床的筛查工具，用于前瞻性识别有非GCT风险的患者。 这一建议是新颖的，它探索了潜在的可修改的障碍，以告知一个模型的发展， 预测接受劣质护理，以及基于诊所的筛查工具，以确定个人在获得差异的风险 肿瘤护理。虽然目前有一系列成功的干预措施，如患者导航， 在减少治疗差异方面的承诺，临床医生没有一种简化的方法来识别有风险的患者， GCT。该提案将允许以一致的方式识别存在健康差异风险的患者（非GCT） 这项研究的结果将用于申请R 01， 前瞻性评估多机构研究中开发的筛查工具的效用，以预测护理差异 并通过种族/民族、地点（农村与城市）、社会经济地位和机构类型来检验其不变性。

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.