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一个用于在医疗现场使用患者汇总数据的“绿色按钮”。

A 'green button' for using aggregate patient data at the point of care.

作者信息

Longhurst Christopher A, Harrington Robert A, Shah Nigam H

机构信息

Christopher A. Longhurst (

Robert A. Harrington is a professor of medicine at Stanford University School of Medicine.

出版信息

Health Aff (Millwood). 2014 Jul;33(7):1229-35. doi: 10.1377/hlthaff.2014.0099.

Abstract

Randomized controlled trials have traditionally been the gold standard against which all other sources of clinical evidence are measured. However, the cost of conducting these trials can be prohibitive. In addition, evidence from the trials frequently rests on narrow patient-inclusion criteria and thus may not generalize well to real clinical situations. Given the increasing availability of comprehensive clinical data in electronic health records (EHRs), some health system leaders are now advocating for a shift away from traditional trials and toward large-scale retrospective studies, which can use practice-based evidence that is generated as a by-product of clinical processes. Other thought leaders in clinical research suggest that EHRs should be used to lower the cost of trials by integrating point-of-care randomization and data capture into clinical processes. We believe that a successful learning health care system will require both approaches, and we suggest a model that resolves this escalating tension: a "green button" function within EHRs to help clinicians leverage aggregate patient data for decision making at the point of care. Giving clinicians such a tool would support patient care decisions in the absence of gold-standard evidence and would help prioritize clinical questions for which EHR-enabled randomization should be carried out. The privacy rule in the Health Insurance Portability and Accountability Act (HIPAA) of 1996 may require revision to support this novel use of patient data.

摘要

传统上,随机对照试验一直是衡量所有其他临床证据来源的金标准。然而,开展这些试验的成本可能高得令人望而却步。此外,试验证据往往基于狭窄的患者纳入标准,因此可能无法很好地推广到实际临床情况中。鉴于电子健康记录(EHR)中综合临床数据的可用性不断提高,一些卫生系统领导者现在主张从传统试验转向大规模回顾性研究,后者可以利用作为临床过程副产品产生的基于实践的证据。临床研究领域的其他思想领袖建议,应通过将即时随机化和数据采集整合到临床过程中,利用电子健康记录来降低试验成本。我们认为,一个成功的学习型医疗保健系统将需要这两种方法,我们提出了一个解决这种不断升级的紧张关系的模型:在电子健康记录中设置一个“绿色按钮”功能,以帮助临床医生在护理点利用汇总的患者数据进行决策。在缺乏金标准证据的情况下,为临床医生提供这样一个工具将有助于支持患者护理决策,并有助于确定应开展基于电子健康记录的随机化的临床问题的优先级。1996年《健康保险流通与责任法案》(HIPAA)中的隐私规则可能需要修订,以支持这种对患者数据的新用途。

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