Improving the Effectiveness of Health Information Technology: The Case for Situational Analytics.
Improving the Effectiveness of Health Information Technology: The Case for Situational Analytics.
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提高健康信息技术的有效性：情境分析案例。
DOI：
10.1055/s-0039-1697594
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发表时间：
2019
影响因子：
2.9
通讯作者：
Weinger,MatthewB
中科院分区：
文献类型：
--
作者：
Novak,LaurieLovett;Anders,Shilo;Unertl,KimM;France,DanielJ;Weinger,MatthewB
卫生信息技术有助于提高临床环境的质量和安全性。然而，在医疗保健中实施新技术也与引入新的社会技术危害有关，这些危害是通过一系列复杂的相互作用产生的，这些相互作用因社会、物理、时间和技术背景而异。其他行业也面临着这个问题，并开发了先进的分析方法来检查工人的特定背景活动和相关结果。医疗保健中存在的技能和数据可以通过情景分析来开发类似的见解，情景分析被定义为应用分析方法来描述人类活动的情况，并确定受环境因素影响的活动和结果模式。本文描述了情境分析的方法和潜在有用的数据源，包括来自电子健康记录活动的跟踪数据、用户报告、定性现场数据和位置数据。关键的实施要求进行了讨论，包括定性研究人员和数据科学家之间的合作，组织和联邦级的基础设施的要求，以及需要实施一个并行的研究计划，在道德，以了解数据正在使用的组织和政策制定者。
Health information technology has contributed to improvements in quality and safety in clinical settings. However, the implementation of new technologies in health care has also been associated with the introduction of new sociotechnical hazards, produced through a range of complex interactions that vary with social, physical, temporal, and technological context. Other industries have been confronted with this problem and have developed advanced analytics to examine context-specific activities of workers and related outcomes. The skills and data exist in health care to develop similar insights through situational analytics, defined as the application of analytic methods to characterize human activity in situations and identify patterns in activity and outcomes that are influenced by contextual factors. This article describes the approach of situational analytics and potentially useful data sources, including trace data from electronic health record activity, reports from users, qualitative field data, and locational data. Key implementation requirements are discussed, including the need for collaboration among qualitative researchers and data scientists, organizational and federal level infrastructure requirements, and the need to implement a parallel research program in ethics to understand how the data are being used by organizations and policy makers.