Djulbegovic Benjamin, Hozo Iztok, Dale William
Department of Supportive Care Medicine, City of Hope, Duarte, California, USA.
Department of Mathematics, Indiana University NW, Gary, Indiana, USA.
J Eval Clin Pract. 2018 Oct;24(5):1247-1254. doi: 10.1111/jep.12895. Epub 2018 Feb 27.
Contemporary delivery of health care is inappropriate in many ways, largely due to suboptimal Q5 decision-making. A typical approach to improve practitioners' decision-making is to develop evidence-based clinical practice guidelines (CPG) by guidelines panels, who are instructed to use their judgments to derive practice recommendations. However, mechanisms for the formulation of guideline judgments remains a "black-box" operation-a process with defined inputs and outputs but without sufficient knowledge of its internal workings.
Increased explicitness and transparency in the process can be achieved by implementing CPG as clinical pathways (CPs) (also known as clinical algorithms or flow-charts). However, clinical recommendations thus derived are typically ad hoc and developed by experts in a theory-free environment. As any recommendation can be right (true positive or negative), or wrong (false positive or negative), the lack of theoretical structure precludes the quantitative assessment of the management strategies recommended by CPGs/CPs.
To realize the full potential of CPGs/CPs, they need to be placed on more solid theoretical grounds. We believe this potential can be best realized by converting CPGs/CPs within the heuristic theory of decision-making, often implemented as fast-and-frugal (FFT) decision trees. This is possible because FFT heuristic strategy of decision-making can be linked to signal detection theory, evidence accumulation theory, and a threshold model of decision-making, which, in turn, allows quantitative analysis of the accuracy of clinical management strategies.
Fast-and-frugal provides a simple and transparent, yet solid and robust, methodological framework connecting decision science to clinical care, a sorely needed missing link between CPGs/CPs and patient outcomes. We therefore advocate that all guidelines panels express their recommendations as CPs, which in turn should be converted into FFTs to guide clinical care.
当代医疗服务在很多方面并不恰当，这主要归因于欠佳的决策。改善从业者决策的一种典型方法是由指南制定小组制定基于证据的临床实践指南（CPG），这些小组被要求运用他们的判断力来得出实践建议。然而，指南判断的形成机制仍然是一个“黑箱”操作——一个有明确输入和输出但对其内部运作缺乏足够了解的过程。
通过将CPG实施为临床路径（CP）（也称为临床算法或流程图），可以提高过程的明确性和透明度。然而，这样得出的临床建议通常是临时的，并且是在无理论环境中由专家制定的。由于任何建议都可能是正确的（真阳性或真阴性），或者是错误的（假阳性或假阴性），缺乏理论结构使得无法对CPG/CP推荐的管理策略进行定量评估。
为了充分发挥CPG/CP的潜力，需要将它们置于更坚实的理论基础之上。我们认为，通过在决策启发式理论（通常以快速节俭（FFT）决策树的形式实施）中转换CPG/CP，可以最好地实现这一潜力。这是可行的，因为FFT决策启发式策略可以与信号检测理论、证据积累理论以及决策阈值模型联系起来，这反过来又允许对临床管理策略的准确性进行定量分析。
快速节俭提供了一个简单、透明但坚实且稳健的方法框架，将决策科学与临床护理联系起来，这是CPG/CP与患者预后之间急需的缺失环节。因此，我们主张所有指南制定小组将其建议表述为CP，而CP又应转换为FFT以指导临床护理。
