■将叙述性临床指南转化为可计算知识是一个长期的挑战,已经看到了各种各样的方法。英国国家健康与护理卓越研究所(NICE)内容咨询委员会(CAB)的最终目标是(1)指导临床决策支持和其他软件开发人员提高可追溯性,支持NICE建议的临床使用的保真度和一致性,(2)指导地方执业审计和干预,减少不必要的变异,(3)向NICE提供有关如何制定未来建议的反馈。
■工作的第一阶段是探索一系列技术方法,以将NICE过渡到本地数字内容的生产。
■在2022年11月首次“合作马拉松”之后,建立了NICE可计算实施指导项目(NCIG)。我们大约每两周举行一次工作流电话会议,专注于(1)用户故事和触发事件,(2)信息模型和定义,(3)水平扫描和输出格式。2023年3月举行了第二次合作马拉松,以巩固整个工作流的进展,并同意完成剩余行动。
■虽然我们最初专注于技术实施标准,我们认为,在从叙事到完全可计算表示的旅程中,中间逻辑模型是更可实现的第一步。NCIG采用了世卫组织数字适应工具包(DAK)作为一种与技术无关的方法来对用户场景进行建模,人物,流程和工作流,核心数据元素和决策支持逻辑。进一步的工作将涉及指标,例如规定合规性,并在初级保健患者记录系统的文档模板中实施。
■该项目表明,世卫组织DAK,经过一些修改,是构建NICE建议的技术中立逻辑规范的有前途的方法。在指南开发过程中,多学科团队实施并发可计算建模会带来方法和文化问题,这些问题很复杂,但在适当的意愿和领导能力下易于处理。
UNASSIGNED: Translating narrative clinical guidelines to computable knowledge is a long-standing challenge that has seen a diverse range of approaches. The UK National Institute for Health and Care Excellence (NICE) Content Advisory Board (CAB) aims ultimately to (1) guide clinical decision support and other software developers to increase traceability, fidelity and consistency in supporting clinical use of NICE recommendations, (2) guide local practice audit and intervention to reduce unwarranted variation, (3) provide feedback to NICE on how future recommendations should be developed.
UNASSIGNED: The first phase of work was to explore a range of technical approaches to transition NICE toward the production of natively digital content.
UNASSIGNED: Following an initial \'collaborathon\' in November 2022, the NICE Computable Implementation Guidance project (NCIG) was established. We held a series of workstream calls approximately fortnightly, focusing on (1) user stories and trigger events, (2) information model and definitions, (3) horizon-scanning and output format. A second collaborathon was held in March 2023 to consolidate progress across the workstreams and agree residual actions to complete.
UNASSIGNED: While we initially focussed on technical implementation standards, we decided that an intermediate logical model was a more achievable first step in the journey from narrative to fully computable representation. NCIG adopted the WHO Digital Adaptation Kit (DAK) as a technology-agnostic method to model user scenarios, personae, processes and workflow, core data elements and decision-support logic. Further work will address indicators, such as prescribing compliance, and implementation in document templates for primary care patient record systems.
UNASSIGNED: The project has shown that the WHO DAK, with some modification, is a promising approach to build technology-neutral logical specifications of NICE recommendations. Implementation of concurrent computable modelling by multidisciplinary teams during guideline development poses methodological and cultural questions that are complex but tractable given suitable will and leadership.