Sordo Margarita, Tokachichu Priyaranjan, Vitale Christopher J, Maviglia Saverio M, Rocha Roberto A
Clinical Informatics, Partners eCare, Partners Healthcare System.
Brigham and Women's Hospital.
AMIA Annu Symp Proc. 2018 Apr 16;2017:1617-1624. eCollection 2017.
In theory, the logic of decision rules should be atomic. In practice, this is not always possible; initially simple logic statements tend to be overloaded with additional conditions restricting the scope of such rules. By doing so, the original logic soon becomes encumbered with contextual knowledge. Contextual knowledge is re-usable on its own and could be modeled separately from the logic of a rule without losing the intended functionality. We model constraints to explicitly define the context where knowledge of decision rules is actionable. We borrowed concepts from Semantic Web, Complex Adaptive Systems, and Contextual Reasoning. The proposed approach provides the means for identifying and modeling contextual knowledge in a simple, sound manner. The methodology presented herein facilitates rule authoring, fosters consistency in rules implementation and maintenance; facilitates developing authoritative knowledge repositories to promote quality, safety and efficacy of healthcare; and paves the road for future work in knowledge discovery.
理论上，决策规则的逻辑应该是原子性的。在实践中，这并不总是可行的；最初简单的逻辑语句往往会因附加条件而负担过重，这些条件限制了此类规则的范围。这样一来，原始逻辑很快就会被上下文知识所拖累。上下文知识本身是可重复使用的，并且可以与规则逻辑分开建模，而不会失去预期的功能。我们对约束进行建模，以明确界定决策规则知识可起作用的上下文。我们借鉴了语义网、复杂自适应系统和上下文推理的概念。所提出的方法提供了以简单、合理的方式识别和建模上下文知识的手段。本文介绍的方法有助于规则编写，促进规则实施和维护的一致性；有助于开发权威性知识库以提高医疗保健的质量、安全性和有效性；并为知识发现的未来工作铺平道路。
