Implementing Electronic Health Care Predictive Analytics: Considerations And Challenges
Implementing Electronic Health Care Predictive Analytics: Considerations And Challenges
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DOI：
10.1377/hlthaff.2014.0352
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发表时间：
2014-07-01
期刊：
影响因子：
9.7
通讯作者：
Xie, Bin
中科院分区：
文献类型：
--
作者：
Amarasingham, Ruben;Patzer, Rachel E.;Xie, Bin
在实时临床决策中使用预测建模越来越被认为是实现改善结果、增强患者体验和降低医疗保健成本三重目标的一种方式。临床实践预测模型的开发和验证只是走向主流实施实时护理点预测的第一步。将电子卫生保健预测分析（e-HPA）集成到临床工作流程中，在患者群体中测试e-HPA，并随后在美国卫生保健系统中广泛传播e-HPA，需要深思熟虑的计划。随着该领域的发展，需要政策制定者、卫生保健主管、研究人员和从业人员的投入。本文描述了实施e-HPA的一些注意事项和挑战，包括需要确保患者隐私，建立卫生系统监测团队来监督实施，将预测分析纳入医学教育，并确保电子系统不会取代或排挤医生和患者的决策。
The use of predictive modeling for real-time clinical decision making is increasingly recognized as a way to achieve the Triple Aim of improving outcomes, enhancing patients' experiences, and reducing health care costs. The development and validation of predictive models for clinical practice is only the initial step in the journey toward mainstream implementation of real-time point-of-care predictions. Integrating electronic health care predictive analytics (e-HPA) into the clinical work flow, testing e-HPA in a patient population, and subsequently disseminating e-HPA across US health care systems on a broad scale require thoughtful planning. Input is needed from policy makers, health care executives, researchers, and practitioners as the field evolves. This article describes some of the considerations and challenges of implementing e-HPA, including the need to ensure patients' privacy, establish a health system monitoring team to oversee implementation, incorporate predictive analytics into medical education, and make sure that electronic systems do not replace or crowd out decision making by physicians and patients.