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临床数据二次利用的评估考量:基于证据的二次分析政策与实施方法原则

Evaluation Considerations for Secondary Uses of Clinical Data: Principles for an Evidence-based Approach to Policy and Implementation of Secondary Analysis.

作者信息

Scott P J, Rigby M, Ammenwerth E, McNair J Brender, Georgiou A, Hyppönen H, de Keizer N, Magrabi F, Nykänen P, Gude W T, Hackl W

出版信息

Yearb Med Inform. 2017 Aug;26(1):59-67. doi: 10.15265/IY-2017-010. Epub 2017 Sep 11.

Abstract

To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. Working Group review of selected literature and policy approaches. We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy. We make the case for a multi-level and multi-factorial approach to the evaluation of secondary uses of clinical data and describe a methodological framework for best practice. We emphasise the importance of evaluating the governance of secondary uses of health data in maintaining trust, which is essential for such uses. We also offer examples of the re-use of routine health data to demonstrate how it can support evaluation of clinical performance and optimize health IT system design. Great expectations are resting upon "Big Data" and innovative analytics. However, to build and maintain public trust, improve data reliability, and assure the validity of analytic inferences, there must be independent and transparent evaluation. A mature and evidence-based approach needs not merely data science, but must be guided by the broader concerns of applied health informatics.

摘要

为了设定科学背景,进而提出基于证据的临床数据二次利用方法的原则,涵盖数据二次利用的评估以及基于数据二次利用的卫生系统和服务评估。工作组对选定的文献和政策方法进行审查。我们从治理与信任、理论、语义和政策等角度,阐述临床数据二次利用评估中的重要考量因素。我们主张采用多层次、多因素的方法来评估临床数据的二次利用,并描述最佳实践的方法框架。我们强调评估卫生数据二次利用治理对于维持信任的重要性,而信任对于此类利用至关重要。我们还提供常规卫生数据再利用的示例,以展示其如何支持临床绩效评估并优化卫生信息技术系统设计。人们对“大数据”和创新分析寄予厚望。然而,为了建立和维护公众信任、提高数据可靠性并确保分析推断的有效性,必须进行独立且透明的评估。一种成熟且基于证据的方法不仅需要数据科学,还必须以应用卫生信息学的更广泛关注点为指导。

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