Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
Department of Veterans Affairs Knowledge Based Systems, Salt Lake City, UT.
AMIA Annu Symp Proc. 2021 Jan 25;2020:687-696. eCollection 2020.
Clinical Practice Guidelines (CPG), meant to express best practices in healthcare, are commonly presented as narrative documents communicating care processes, decision making, and clinical case knowledge. However, these narratives in and of themselves lack the specificity and conciseness in their use of language to unambiguously express quality clinical recommendations. This impacts the confidence of clinicians, uptake, and implementation of the guidance. As important as the quality of the clinical knowledge articulated, is the quality of the language(s) and methods used to express the recommendations. In this paper, we propose the BPM+ family of modeling languages as a potential solution to this challenge. We present a formalized process and framework for translating CPGs into a standardized BPM+ model. Further, we discuss the features and characteristics of modeling languages that underpin the quality in expressing clinical recommendations. Using an existing CPG, we defined a systematic series of steps to deconstruct the CPG into knowledge constituents, assign CPG knowledge constituents to BPM+ elements, and re-assemble the parts into a clear, precise, and executable model. Limitations of both the CPG and the current BPM+ languages are discussed.
临床实践指南 (CPG) 旨在表达医疗保健方面的最佳实践,通常以叙述性文件的形式呈现,传达护理流程、决策和临床病例知识。然而,这些叙述本身在语言使用的准确性和简洁性方面缺乏明确表达质量临床建议的能力。这会影响临床医生的信心、指导的采用和实施。与表达的临床知识的质量一样重要的是,用于表达建议的语言和方法的质量。在本文中,我们提出了 BPM+ 系列建模语言作为解决这一挑战的潜在方法。我们提出了一个将 CPG 转换为标准化 BPM+模型的正式流程和框架。此外,我们讨论了支持表达临床建议的质量的建模语言的特征和特点。使用现有的 CPG,我们定义了一系列系统的步骤,将 CPG 分解为知识要素,将 CPG 知识要素分配给 BPM+ 元素,并将各个部分重新组合成一个清晰、精确和可执行的模型。讨论了 CPG 和当前 BPM+语言的局限性。