University of Oslo, Norway.
Health Informatics J. 2019 Sep;25(3):491-499. doi: 10.1177/1460458218796665. Epub 2018 Sep 9.
Within healthcare, information systems are increasingly developed to enable automatic analysis of the large amounts of data that are accumulated. A prerequisite for the practical use of such data analysis is the veracity of the output, that is, that the analysis is clinically valid. Whereas most research focuses on the technical configuration and clinical precision of data analysis systems, the purpose of this article is to investigate how veracity is achieved in practice. Based on a study of a project in Denmark aimed at developing an algorithm for stratification of citizens in preventive healthcare, this article confirms that achieving veracity requires close attention to the clinical validity of the algorithm. It also concludes, however, that the veracity in practice hinges critically on the citizens' ability to report high-quality data and the ability of the health professionals to interpret the outcome in the context of existing care practices.
在医疗保健领域,信息系统越来越多地被开发出来,以实现对大量累积数据的自动分析。这种数据分析实际应用的前提是输出的准确性,也就是说,分析是具有临床有效性的。虽然大多数研究都集中在数据分析系统的技术配置和临床精度上,但本文的目的是调查在实践中如何实现准确性。本文基于对丹麦一个旨在开发一种用于对公民进行预防保健分层的算法的项目的研究,证实了实现准确性需要密切关注算法的临床有效性。然而,本文也得出结论,准确性在实践中关键取决于公民报告高质量数据的能力,以及卫生专业人员在现有护理实践背景下解读结果的能力。