Abramson Cancer Center Support Grant

项目总结/摘要 结直肠癌是第四大最常见的癌症诊断和第二大最常见的癌症死亡原因 在美国费城县CRC的年龄调整发病率-持续高贫困 面积-比全国平均水平高出近25%。通过结肠镜检查或粪便检查进行基于指南的CRC筛查 免疫组化（FIT）可降低CRC相关死亡率。尽管定期的好处已被证明 结肠镜检查，CRC筛查完成率在费城县仅为50%左右， 非洲裔美国人的死亡率比费城县的白色人低10 - 15%。不良 健康社会决定因素，如高度贫困，导致不依从CRC筛查 对非洲裔美国人和其他少数族裔社区来说不成比例。认识到这一点，2011年，宾夕法尼亚大学 医学创建了一个导航程序，以增加患者筛查结肠镜检查的机会， 费城西部、南部和西南部服务不足的地区，提供减少交通障碍的服务， 癌症筛查，包括交通援助和肠道准备的详细说明。 成功增加结肠镜检查，扩大该导航计划的关键挑战是识别患者 CRC风险增加的人群，他们可能从及时导航中受益最多。自动化机器 基于常规电子健康记录（EHR）数据的学习（ML）算法准确地估计患者的 CRC的相对风险。高风险个体可能特别有动力遵守疾病筛查 建议，并有针对性地与一个有效的，但资源有限的导航程序。 本行政补充的总体目标是支持艾布拉姆森癌症中心（ACC） 使命是提高居住在偏远地区的高危人群的结直肠癌（CRC）筛查完成率。 通过设计、实施、传播和评估电子健康档案， 基于自动识别程序，针对有效的，文化敏感的CRC筛查导航， 未完成结肠镜检查或粪便免疫化学试验（FIT）的个体。具体地说， 本附录的目标是：1）使以前验证过的基于EHR的机器学习算法适应于 通过使用来自初级保健诊所提供zip服务的患者的数据重新训练模型来预测CRC检测 与居住在费城县的种族和少数民族的比例很高的代码，持续的贫困 县;和2）实施和评估基于算法的CRC导航的可行性和有效性 在7个初级保健实践之一的344名患者中增加结直肠癌筛查的计划 在费城县的CRC高风险人群中，有未完成的结肠镜检查。所有这些 项目旨在增加循证筛查，以减轻高危人群中CRC的负担。 通过利用循证、有针对性、对文化敏感的儿童权利委员会， 筛查导航，部分解决了阻止结直肠癌筛查的社会因素。

PROJECT SUMMARY/ABSTRACT Colorectal cancer is the 4th most common cancer diagnosed and the 2nd most common cause of cancer death in the United States. The age-adjusted incidence of CRC in Philadelphia County – a persistently high poverty area– is nearly 25% above the national average. Guideline-based screening for CRC via colonoscopy or fecal immunohistochemistry (FIT) reduces CRC-associated mortality. Despite the proven benefit of regular colonoscopy, CRC screening completion rates remain only around 50% in Philadelphia County and are consistently 10-15% lower for African-Americans than White individuals living in Philadelphia County. Adverse social determinants of health such as high poverty contribute to CRC screening nonadherence disproportionately for African-American and other minority communities. Recognizing this, in 2011, Penn Medicine created a navigation program to increase access to screening colonoscopies for patients in underserved areas of West, South, and Southwest Philadelphia by providing services that reduce barriers to cancer screening, including transportation assistance and detailed instructions on bowel prep. Despite initial success in increasing colonoscopies, a key challenge in scaling this navigation program is identifying patient populations at increased risk of CRC, who may benefit most from timely navigation. Automated machine learning (ML) algorithms based on routine electronic health record (EHR) data accurately estimate a patient’s relative risk of CRC. High-risk individuals may be particularly motivated to comply with disease screening recommendations and be targeted with an effective but resource-constrained navigator program. The overarching goals of this Administrative Supplement is to support the Abramson Cancer Center (ACC) mission to increase colorectal cancer (CRC) screening completion among high-risk individuals living in a persistent poverty county by designing, conducting, disseminating and evaluating an electronic health record- based automated identification program to target effective, culturally-sensitive CRC screening navigation to individuals who have not completed an ordered colonoscopy or fecal immunochemical test (FIT). Specifically, the goals of this supplement are to: 1) Adapt a previously validated EHR-based machine learning algorithm to predict CRC detection by retraining the model using data from patients seen in primary care clinics serving zip codes with a high proportion of racial and ethnic minorities living in Philadelphia County, a persistent poverty county; and 2) Implement and evaluate the feasibility and effectiveness of an algorithm-based CRC navigation program to increase colorectal cancer screening among 344 patients seen at one of 7 primary care practices within Philadelphia county who are at high risk of CRC, have uncompleted colonoscopies. Together, these projects aim to increase evidence-based screening in order to reduce the burden of CRC among high-risk individuals living in a persistent poverty county by utilizing evidence-based, targeted, culturally-sensitive CRC screening navigation that in part addresses social factors that prevent colorectal cancer screening.