Safran C
Charles Safran, MD, Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA, E-mail:
Yearb Med Inform. 2014 Aug 15;9(1):52-4. doi: 10.15265/IY-2014-0013.
To provide an overview of the benefits of clinical data collected as a by-product of the care process, the potential problems with large aggregations of these data, the policy frameworks that have been formulated, and the major challenges in the coming years.
This report summarizes some of the major observations from AMIA and IMIA conferences held on this admittedly broad topic from 2006 through 2013. This report also includes many unsupported opinions of the author.
The benefits of aggregating larger and larger sets of routinely collected clinical data are well documented and of great societal benefit. These large data sets will probably never answer all possible clinical questions for methodological reasons. Non-traditional sources of health data that are patient-sources will pose new data science challenges.
If we ever hope to have tools that can rapidly provide evidence for daily practice of medicine we need a science of health data perhaps modeled after the science of astronomy.
概述作为医疗过程副产品收集的临床数据的益处、这些数据大量汇总存在的潜在问题、已制定的政策框架以及未来几年的主要挑战。
本报告总结了2006年至2013年就这个公认宽泛的主题举行的美国医学信息学会(AMIA)和国际医学信息学会(IMIA)会议的一些主要观点。本报告还包含了作者的许多未经证实的观点。
越来越多常规收集的临床数据汇总的益处有充分记录且具有重大社会效益。由于方法学原因,这些大数据集可能永远无法回答所有可能的临床问题。以患者为来源的非传统健康数据来源将带来新的数据科学挑战。
如果我们希望拥有能够迅速为日常医学实践提供证据的工具,我们需要一门健康数据科学,或许可以仿照天文学的科学模式。