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

发现影像的价值：放射学领域生物医学大数据和比较有效性研究的协作培训项目

基本信息

批准号：
9312810
负责人：
Constantin F. Aliferis
金额：
$ 16.76万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-30 至 2019-06-30
项目状态：
已结题

项目摘要

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).

描述（由申请人提供）：过去 50 年来，美国的医疗保健费用急剧增加，达到 2.9 万亿美元，相当于 2013 年国内生产总值 (GDP) 的 17.4%。影像费用也大幅增加过去几年增加了，2000 年至 2010 年间累计增加了 70%。成像成本增加的很大一部分是由于先进成像技术的增加，例如CT 和 MR 的数量从 2000 年到 2010 年增加了一倍多。尽管缺乏记录这些影像学研究改善患者结果和价值的研究，但影像学（尤其是 CT）的增加也导致了显着增加。患者受到辐射照射以及辐射诱发的恶性肿瘤发病率可能增加。为了确保成像的适当且具有成本效益的使用，以确保在正确的时间以正确的方式对正确的患者进行成像。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 培训以及 CER 成像所固有的生物医学大数据的使用仅适用于一小部分医学成像仪。为更广泛的医学成像人员群体提供有效的 CER 和大数据分析培训超出了个人成像培训计划的能力，以满足对 CER 和大数据培训的独特而重要的需求。成像仪，我们提出了一个协作和广泛参与的 CER 培训和生物医学大数据使用分层计划是一套关于 CER 和大数据基础知识的 8 个讲座，可在线观看，并在美国放射病理学研究所进行，这是一个密集的 1 课程。美国和加拿大 90-95% 的放射科住院医师参加了为期一个月的培训课程，Tier 2 是一项先进的 CER 和生物医学大数据培训计划，包括 CER 方面的持续指导和大数据的使用。为了确保该计划产生最大影响，我们将采用在线和面对面互动会议的混合教育结构。主要国家影像组织（包括美国放射学会、美国伦琴射线学会、北美放射学会、学术放射学系主席学会、放射学项目主任协会、大学放射科医生协会、美国神经放射学会、美国放射学会）骨骼放射学）以及成像行业的成员（包括飞利浦医疗保健和西门子医疗解决方案）。