Discovering the Value of Imaging: A Collaborative Training Program in Biomedical Big Data and Comparative Effectiveness Research for the Field of Radiology

 描述(申请人提供)：在过去的50年里，美国的医疗保健成本大幅增加，相当于2.9万亿美元，相当于2013年国内生产总值(GDP)的17.4%。过去几年，成像成本也大幅增加，在2000年至2010年期间累计增长了70%。这一成像成本增加的很大一部分原因是CT和MR等先进成像技术的增长，从2000年到2010年，这一数字翻了一番以上。尽管缺乏研究记录这些成像研究改善了患者的结果和价值，但这种增加还是发生了。这种成像的增加，特别是CT的增加，也导致患者的辐射暴露显著增加，并潜在地增加了辐射引起的恶性肿瘤的发生率。为了确保正确和经济高效地使用成像--确保在正确的时间、正确的时间、针对正确的患者以正确的方式进行成像--迫切需要进行比较 有效性研究(CER)。缺乏成像CER研究的一个原因是，CER方面的培训以及使用CER在成像方面固有的生物医学大数据的培训只对极少数医学成像者可用，而且只需支付相当高的费用。为更广泛的医学成像员社区创建有效的CER和大数据分析培训，超出了单个成像培训计划的能力范围。为了满足成像者对CER和大数据培训的独特而重要的需求，我们在CER培训和生物医学大数据的使用方面提出了一个协作性和可广泛访问的分层计划。Tier 1是一套关于CER和大数据基础的8个讲座，可在网上获得，也可在美国放射病理研究所举办，这是一个为期1个月的高强度培训课程，美国和加拿大90%-95%的放射科住院医师参加。Tier 2是一个高级CER和生物医学大数据培训计划，包括继续指导CER和使用大数据的潜力，面向医学成像社区并可供其使用。为了确保这一计划产生最大的影响，我们将使用在线和面对面互动课程的混合教育结构。我们的建议是独一无二的，因为它已经得到了主要的国家成像组织(包括美国放射学会、美国伦琴射线学会、北美放射学会、学术放射科主任协会、放射学项目主任协会、大学放射学家协会、美国神经放射学会、骨骼放射学会)以及成像行业成员(包括飞利浦医疗和西门子医疗解决方案)的支持。

 DESCRIPTION (provided by applicant): Over the past 50 years, the cost of health care in the United States has dramatically increased, equaling $2.9 trillion and equating to 17.4% of the Gross Domestic Product (GDP) in 2013. Imaging costs have also significantly increased over the past several years, a cumulative 70% between 2000 and 2010. A large portion of this imaging cost increase was due to an increase in advanced imaging such as CT and MR, which more than doubled from 2000 to 2010. This increase has occurred despite the lack of studies documenting improved patient outcomes and value from these imaging studies. This rise in imaging, particularly that of CT, has also led to significant increases in radiation exposure to patients and potential increased incidence of radiation induced malignancies. To ensure the appropriate and cost effective use of imaging ‒ to make sure that imaging is performed the right way, at the right time, for the right patient's ‒ there is a critical need to perform comparative effectiveness research (CER). One reason for the lack of research in imaging CER is that training in CER, and in the use of biomedical big data that is inherent to CER in imaging, is only available to a very small subset of medical imagers, and is available only at significant cost. Creating effective training in CER and big data analytics for the broader community of medical imagers is beyond the capabilities of individual imaging training programs. In order to address the unique and important need for CER and big data training for imagers, we propose a collaborative and broadly accessible tiered program in CER training and the use of biomedical big data. Tier 1 is a set of 8 lectures on the fundamentals of CER and big data to be available online and also presented at the American Institute for Radiologic Pathology, an intense, 1 month training course attended by 90-95% of all radiology residents in the United States and Canada. Tier 2 is an advanced CER and biomedical big data training program including the potential for continued mentorship in CER and the use of big data, directed toward and available to the medical imaging community. To ensure that this program has the greatest impact, we will use a hybrid educational structure with both online and in-person interactive sessions. Our proposal is unique in that it already has the support of the major national imaging organizations (including the American College of Radiology, American Roentgen Ray Society, Radiological Society of North America, Society of Chairs of Academic Radiology Departments, Association of Program Directors in Radiology, Association of University Radiologists, American Society of Neuroradiology, Society of Skeletal Radiology) as well as members of the imaging industry (including Philips Healthcare and Siemens Medical Solutions).