Federer Andrew E, Taylor Dean C, Mather Richard C
Rush University Medical College, Chicago, IL, USA.
Sports Med Arthrosc Rev. 2013 Sep;21(3):155-65. doi: 10.1097/JSA.0b013e31829f608c.
Decision making in health care has evolved substantially over the last century. Up until the late 1970s, medical decision making was predominantly intuitive and anecdotal. It was based on trial and error and involved high levels of problem solving. The 1980s gave way to empirical medicine, which was evidence based probabilistic, and involved pattern recognition and less problem solving. Although this represented a major advance in the quality of medical decision making, limitations existed. The advantages of the gold standard of the randomized controlled clinical trial (RCT) are well-known and this technique is irreplaceable in its ability to answer critical clinical questions. However, the RCT does have drawbacks. RCTs are expensive and can only capture a snapshot in time. As treatments change and new technologies emerge, new expensive clinical trials must be undertaken to reevaluate them. Furthermore, in order to best evaluate a single intervention, other factors must be controlled. In addition, the study population may not match that of another organization or provider. Although evidence-based medicine has provided powerful data for clinicians, effectively and efficiently tailoring it to the individual has not yet evolved. We are now in a period of transition from this evidence-based era to one dominated by the personalization and customization of care. It will be fueled by policy decisions to shift financial responsibility to the patient, creating a powerful and sophisticated consumer, unlike any patient we have known before. The challenge will be to apply medical evidence and personal preferences to medical decisions and deliver it efficiently in the increasingly busy clinical setting. In this article, we provide a robust review of the concepts of customized care and some of techniques to deliver it. We will illustrate this through a personalized decision model for the treatment decision after a first-time anterior shoulder dislocation.
在过去的一个世纪里，医疗保健领域的决策方式发生了巨大的演变。直到20世纪70年代末，医学决策主要是凭直觉和经验。它基于反复试验，需要高水平的问题解决能力。20世纪80年代，经验医学应运而生，它基于证据的概率性，涉及模式识别且问题解决能力要求较低。尽管这代表了医学决策质量的一大进步，但仍存在局限性。随机对照临床试验（RCT）这一黄金标准的优势众所周知，并且这项技术在回答关键临床问题的能力方面是不可替代的。然而，RCT确实存在缺点。RCT成本高昂，且只能捕捉某一时刻的情况。随着治疗方法的改变和新技术的出现，必须开展新的昂贵临床试验来重新评估它们。此外，为了最好地评估单一干预措施，其他因素必须得到控制。另外，研究人群可能与其他机构或医疗服务提供者的人群不匹配。尽管循证医学为临床医生提供了有力的数据，但有效地将其针对个体进行定制尚未实现。我们现在正处于从这个循证时代向以个性化和定制化医疗为主导的时代过渡的时期。这将由政策决策推动，将经济责任转移给患者，从而造就一个强大而精明的消费者，这与我们以往所知的任何患者都不同。挑战将是把医学证据和个人偏好应用于医疗决策，并在日益繁忙的临床环境中高效地提供这种决策。在本文中，我们对定制化医疗的概念以及一些实现它的技术进行了全面的综述。我们将通过一个针对首次前肩脱位后治疗决策的个性化决策模型来说明这一点。
