Interdisciplinary Research Training Center in Cancer Care Delivery

为癌症患者提供护理是一项高风险、高容量和高成本的奋进。在联合 在美国，2016年有超过160万成年人新诊断为浸润性癌症，预计患病率将达到 到2024年将覆盖1900万美国人。国家医学科学院，以及其他机构， 关于癌症护理连续体中患者接受的护理质量的持续问题。快速 如果不能在一个合适的环境中进行治疗，那么癌症治疗的令人印象深刻的进展可能会变得毫无意义。 安全、有效、高效、公平和以患者为中心的方式在不同的治疗环境中。鉴于 最佳癌症护理服务的普遍挑战，需要额外的研究能力来加速 发现护理差距，开发和测试有效的干预措施，并将发现纳入日常工作 临床实践拟议的培训将使来自不同学科的科学家做好准备，以推动这一所需的工作。 研究和了解和改善癌症护理服务，从而填补了癌症研究的关键空白。 这个新的T32应用程序（癌症护理提供跨学科研究培训）的目标是 培养3名博士前和14名博士后学员成为独立的科学家，进行癌症护理 三个重点领域的交付研究：1）描述性发现; 2）干预发展和 测试;（3）实施科学。该计划将通过提供一个坚实的基础来培养独立的科学家。 研究方法和相关理论的基础，在实质性科学领域的知识深度 相关的癌症护理提供，在进行研究的经验，和社会化到规范 高质量、道德敏感的研究行为。培训主要通过四项活动提供： 研究经验，课程工作，选定的重点领域，和专业发展， 社会化学员将有一个个性化的发展计划和一个由一个 一个主要的导师与积极的研究计划，在癌症护理提供和二级导师与内容 和/或方法学专门知识。在六个顶级的研究生院-工程，护理，医学， 药学，公共卫生和社会工作- 22个小学和10个中学教师与癌症护理交付 研究专家承诺指导受训人员。密歇根大学提供了一个杰出的 环境，以支持癌症护理提供研究培训。主要机构资产包括Rogel 癌症中心，医疗保健政策和创新研究所，密歇根数据科学研究所， 社会研究所密歇根大学护理学院，一个前十名的计划，将房子 该计划并实施强有力的战略，以招募和留住多样化的受训人员。 该培训计划与国家癌症研究所和Moonshot Blue的既定优先事项保持一致 丝带小组建议通过最大限度地减少癌症治疗的 使人衰弱的副作用，扩大预防和早期发现，并挖掘数据来预测患者的结果。

Care delivery for patients with cancer is a high-risk, high-volume, and high-cost endeavor. In the United States, over 1.6 million adults received new diagnoses of invasive cancer in 2016 and prevalence is expected to reach 19 million Americans by 2024. The National Academy of Medicine, among others, have raised persistent questions regarding the quality of care patients receive across the cancer care continuum. Rapid and impressive advances in cancer therapies may be rendered moot if such therapies cannot be given in a safe, effective, efficient, equitable, and patient-centered manner across diverse treatment settings. Given the pervasive challenges to optimal cancer care delivery, additional research capacity is needed to hasten the discovery of care gaps, develop and test efficacious interventions, and implement discoveries into routine clinical practice. The proposed training will prepare scientists from diverse disciplines to advance this needed research and to understand and improve cancer care delivery, thus filling a critical void in cancer research. The goal of this new T32 application, Interdisciplinary Research Training in Cancer Care Delivery, is to prepare three pre and 14 postdoctoral trainees to become independent scientists who conduct cancer care delivery research across three emphasis areas: 1) descriptive discovery; 2) intervention development and testing, and; 3) implementation science. The program will produce independent scientists by providing a solid foundation in research methods and pertinent theory, depth of knowledge in a substantive science area pertinent to cancer care delivery, experience in the conduct of research, and socialization into the normative behavior of high quality, ethically sensitive research. Training is provided through four main activities: mentored research experiences, course work, a selected emphasis area, and professional development and socialization. Trainees will have an individualized development plan and a mentorship team composed of a primary mentor with an active research program in cancer care delivery and a secondary mentor with content and/or methodological expertise. Across six top-ranked graduate schools – Engineering, Nursing, Medicine, Pharmacy, Public Health, and Social Work – 22 primary and 10 secondary faculty with cancer care delivery research expertise have pledged to mentor trainees. The University of Michigan provides an outstanding environment to support cancer care delivery research training. Key institutional assets include the Rogel Cancer Center, the Institute for Healthcare Policy and Innovation, the Michigan Institute for Data Science, and the Institute for Social Research. The University of Michigan School of Nursing, a top ten program, will house the program and implement robust strategies to recruit and retain a diverse pool of trainees. This training program aligns with stated priorities of the National Cancer Institute and the Moonshot Blue Ribbon Panel Recommendations to lessen the burden of cancer through minimizing cancer treatment’s debilitating side effects, expand prevention and early detection, and mine data to predict patient outcomes.