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首页> 外文期刊>BMC Medical Informatics and Decision Making >Creation of clinical algorithms for decision-making in oncology: an example with dose prescription in radiation oncology
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Creation of clinical algorithms for decision-making in oncology: an example with dose prescription in radiation oncology

机译：肿瘤决策临床算法的创建：辐射肿瘤学剂量处方的一个例子

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In oncology, decision-making in individual situations is often very complex. To deal with such complexity, people tend to reduce it by relying on their initial intuition. The downside of this intuitive, subjective way of decision-making is that it is prone to cognitive and emotional biases such as overestimating the quality of its judgements or being influenced by one’s current mood. Hence, clinical predictions based on intuition often turn out to be wrong and to be outperformed by statistical predictions. Structuring and objectivizing oncological decision-making may thus overcome some of these issues and have advantages such as avoidance of unwarranted clinical practice variance or error-prevention. Even for uncertain situations with limited medical evidence available or controversies about the best treatment option, structured decision-making approaches like clinical algorithms could outperform intuitive decision-making. However, the idea of such algorithms is not to prescribe the clinician which decision to make nor to abolish medical judgement, but to support physicians in making decisions in a systematic and structured manner. An example for a use-case scenario where such an approach may be feasible is the selection of treatment dose in radiation oncology. In this paper, we will describe how a clinical algorithm for selection of a fractionation scheme for palliative irradiation of bone metastases can be created. We explain which steps in the creation process of a clinical algorithm for supporting decision-making need to be performed and which challenges and limitations have to be considered.
机译：在肿瘤学中，各个情况的决策往往非常复杂。为了应对这种复杂性，人们倾向于通过依赖他们的初始直觉来减少它。这种直观的主观决策方式的缺点是它易于认知和情感偏见，例如过度估计其判断的质量或受到目前情绪的影响。因此，基于直觉的临床预测经常变成错误，并且通过统计预测表现出优越。因此，构建和目标肿瘤决策可以克服这些问题中的一些并具有诸如避免无标记的临床实践方差或防止错误的优势。即使对于有限的医学证据可用或关于最佳治疗选项的争议的不确定情况，临床算法等结构化决策方法可能会优于直观的决策。然而，这种算法的想法不是规定决定做出的临床医生，也不规定消除医疗判决，而是支持医生以系统和结构化的方式做出决策。用于这种方法可能是可行的用例场景的示例是辐射肿瘤学中的治疗剂量选择。在本文中，我们将描述如何选择用于选择用于选择骨转移的姑息辐射的分馏方案的临床算法。我们解释了需要执行支持决策的临床算法的创建过程中的哪些步骤，并且必须考虑哪些挑战和限制。

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