Peleg M, Boxwala A A, Bernstam E, Tu S, Greenes R A, Shortliffe E H
Stanford Medical Informatics, Stanford University School of Medicine, Stanford, California 94305-5479, USA.
J Biomed Inform. 2001 Jun;34(3):170-81. doi: 10.1006/jbin.2001.1016.
Clinical guidelines are intended to improve the quality and cost effectiveness of patient care. Integration of guidelines into electronic medical records and order-entry systems, in a way that enables delivery of patient-specific advice at the point of care, is likely to encourage guidelines acceptance and effectiveness. Among the methodologies for modeling guidelines and medical decision rules, the Arden Syntax for Medical Logic Modules and the GuideLine Interchange Format version 3 (GLIF3) emphasize the importance of sharing encoded logic across different medical institutions and implementation platforms. These two methodologies have similarities and differences; in this paper we clarify their roles. Both methods can be used to support sharing of medical knowledge, but they do so in complementary situations. The Arden Syntax is suitable for representing individual decision rules in self-contained units called Medical Logic Modules (MLMs), which are usually implemented as event-driven alerts or reminders. In contrast, GLIF3 is designed for encoding complex multistep guidelines that unfold over time. As a consequence, GLIF3 has several mechanisms for complexity management and additional constructs that may require overhead unnecessary for expressing simple alerts and reminders. Unlike the Arden Syntax, GLIF3 encourages a top-down process of guideline modeling consisting of three levels that are created in order: Level 1 comprises a human-readable flowchart of clinical decisions and actions. Level 2 comprises a computable specification that can be verified for logical consistency and completeness; and Level 3 comprises an implementable specification that includes information required for local adaptation of guideline logic as well as for mapping guideline variables onto institutional medical records. A major emphasis of the current GLIF3 development process has been to create the computable specification that formally represents medical decision and eligibility criteria. We based GLIF3's formal expression language on the Arden Syntax's logic grammar, making the necessary extensions to the Arden Syntax's data structures and operators to support GLIF3's object-oriented data model. We discuss why the process of generating a set of MLMs from a GLIF-encoded guideline cannot be automated, why it can result in information loss, and why simple medical rules are best represented as individual MLMs. We thus show that the Arden Syntax and GLIF3 play complementary roles in representing medical knowledge for clinical decision support.
临床指南旨在提高患者护理的质量和成本效益。以能够在护理点提供针对患者的建议的方式，将指南整合到电子病历和医嘱录入系统中，可能会促进指南的接受度和有效性。在对指南和医疗决策规则进行建模的方法中，医学逻辑模块的Arden语法和指南交换格式第3版（GLIF3）强调了在不同医疗机构和实施平台之间共享编码逻辑的重要性。这两种方法既有相似之处，也有不同之处；在本文中，我们阐明了它们的作用。两种方法都可用于支持医学知识的共享，但它们是在互补的情况下这样做的。Arden语法适用于在称为医学逻辑模块（MLM）的独立单元中表示单个决策规则，这些模块通常作为事件驱动的警报或提醒来实施。相比之下，GLIF3是为编码随时间展开的复杂多步骤指南而设计的。因此，GLIF3有几种复杂性管理机制和额外的结构，这些结构对于表达简单的警报和提醒可能需要不必要的开销。与Arden语法不同，GLIF3鼓励一种自上而下的指南建模过程，该过程由三个依次创建的级别组成：第1级包括临床决策和行动的人类可读流程图。第2级包括一个可计算规范，可对其进行逻辑一致性和完整性验证；第3级包括一个可实施规范，其中包括指南逻辑的本地适应性所需的信息以及将指南变量映射到机构病历上所需的信息。当前GLIF3开发过程的一个主要重点是创建正式表示医疗决策和资格标准的可计算规范。我们基于Arden语法的逻辑语法构建了GLIF3的形式表达语言，对Arden语法的数据结构和运算符进行了必要的扩展，以支持GLIF3的面向对象数据模型。我们讨论了为什么从GLIF编码的指南生成一组MLM的过程不能自动化，为什么它会导致信息丢失，以及为什么简单的医学规则最好表示为单个MLM。因此，我们表明Arden语法和GLIF3在为临床决策支持表示医学知识方面发挥着互补作用。
