Lussier Y A, Kukafka R, Patel V L, Cimino J J
Department of Medical Informatics, Columbia University, New York, New York, USA.
Proc AMIA Symp. 2000:522-6.
This paper addresses a process in which we combined educational guidelines (EG) from heterogeneous sources in one set of coherent computable statements to support dynamically generated and precisely tailored patient education material. The Guideline Interchange Format (GLIF), predicate logic and decision tables were assessed. An extended formalism of GLIF was applied to break up composite sentences of the educational material in atomic sentences. The differentiation of atomic sentences and combinations of atomic sentences from heterogeneous sources lead to a simplified overall content and model, and a significant reduction of conditional sentences in the EG. The resulting streamlined and personalized guidelines are expected to provide an improved user experience.
本文探讨了一个过程,在这个过程中,我们将来自不同来源的教育指南(EG)整合为一组连贯的可计算语句,以支持动态生成且精准定制的患者教育材料。我们评估了指南交换格式(GLIF)、谓词逻辑和决策表。应用了GLIF的扩展形式来将教育材料的复合句分解为原子句。对来自不同来源的原子句及其组合进行区分,可简化整体内容和模型,并显著减少EG中的条件句。由此产生的精简且个性化的指南有望提供更好的用户体验。