Evaluating a remotely delivered, digital health CRC screening intervention among racially diverse patients of a community health center

项目摘要/摘要 结直肠癌(CRC)筛查是降低癌症发病率和死亡率的最有效手段之一。 然而，在农村地区获得联邦资格的卫生中心(FQHC)的CRC筛查率落后于更多的人 资源丰富的医疗保健系统和国家目标。改善农村食品检疫中心结直肠癌筛查工作值得重视 以满足其患者群体的需求以及用于实施的有限资源；然而，几乎 研究已经测试了具有文化响应性、背景相关性的FQHC的CRC筛查计划 减轻执行负担。我们的长期目标是扩大实施CRC筛查的规模 将减少FQHC负担的不平等的解决方案。我们的团队开发了一种新型的数字健康 平台mPATH-Cloud，有可能通过以下方式帮助减轻临床团队的实施负担 自动化许多关键流程，同时提供CRC筛查通信、培训和 以已被证明符合文化要求、以患者为中心和有效的方式提供服务。因此，我们的研究 寻求与农村FQHC一起评估mPATH-Cloud，以证明在改进指南方面的有效性 协调筛选并确定将影响未来的关键实施流程和结果 传播性和可扩展性。我们将使用嵌入式实验混合方法模型，该模型包括 多组分干预的个体随机试验，定量和定性措施 确定改进定制消息传递的方法，并调整策略以提高跨不同领域的效率 患者概况，以及过程和结果的定量和定性测量，以改进 实施。我们的团队完全有能力领导这项研究，如果研究成功，将会取得进展 旨在减少FQHC服务的低收入农村社区的不平等。

Project Summary/Abstract Colorectal cancer (CRC) screening is one of the most effective tools to reduce cancer morbidity and mortality. Yet, CRC screening rates at federally qualified health centers (FQHCs) in rural areas lag behind more well- resourced healthcare systems and national goals. Improving CRC screening in rural FQHCs requires attention to the needs of their patient populations as well as their limited resources for implementation; yet, little research has tested CRC screening programs with FQHCs that are culturally responsive, contextually relevant and alleviate implementation burden. Our long-term goal is to scale implementation of CRC screening solutions that will reduce inequities that burden FQHCs. Our team has developed a novel digital health platform, mPATH-Cloud, that has the potential to help alleviate implementation burden on clinical teams by automating many key processes, all the while delivering CRC screening communication, education, and services in ways that have proven to be culturally responsive, patient-centered, and effective. Thus, our study seeks to evaluate mPATH-Cloud with rural FQHCs to demonstrate effectiveness at improving guideline concordant screening and identify critical implementation processes and outcomes that will impact future dissemination and scalability. We will use an embedded experimental mixed methods model, which includes an individual randomized trial of the multi-component intervention, quantitative and qualitative measures to identify ways to improve tailored messaging and adapt strategies to improve effectiveness across diverse patient profiles, and quantitative and qualitative measures of processes and outcomes to improve implementation. Our team is well-situated to lead this research, which if successful, will lead to progress toward reducing inequities in low-income rural communities served by FQHCs.