University of Pavia, Pavia, Italy.
Department of Information Systems, University of Haifa, Haifa, Israel.
AMIA Annu Symp Proc. 2022 Feb 21;2021:1186-1195. eCollection 2021.
Developing effective digital interventions to help patients form healthy habits is a challenging goal. IDEAS is a step-by-step framework that allows developers to draw ideas from intended users and behavioral theories, and ideate implementation strategies for them, followed by rapid prototype development. Based on our long experience with developing knowledge-based clinical decision support systems (CDSS) and integrating them with electronic health records (EHR) to deliver patient-specific advice, we observed a challenge that IDEAS is not addressing: the semantic detailing of the clinical knowledge behind the digital intervention and relevant patient data that could be used to personalize the digital intervention. To close the gap, we augmented two steps of IDEAS with an ontology that structures the target behavior as classes, derived from HL7 Fast Healthcare Interoperability Resources standard. We exemplify the augmented IDEAS with a case study taken from the Horizon 2020 CAPABLE project, that uses Fogg's Tiny Habits behavioral model to improve the sleep of cancer patients via Tai Chi.
开发有效的数字干预措施来帮助患者养成健康的习惯是一个具有挑战性的目标。IDEAS 是一个逐步框架,允许开发人员从预期用户和行为理论中汲取创意,并为他们构思实施策略,然后快速开发原型。基于我们在开发基于知识的临床决策支持系统 (CDSS) 并将其与电子健康记录 (EHR) 集成以提供患者特定建议方面的长期经验,我们观察到 IDEAS 没有解决的一个挑战:数字干预背后的临床知识和可用于个性化数字干预的相关患者数据的语义细节。为了缩小差距,我们使用本体论扩展了 IDEAS 的两个步骤,该本体论将目标行为构建为类,这些类源自 HL7 Fast Healthcare Interoperability Resources 标准。我们使用来自 Horizon 2020 CAPABLE 项目的一个案例研究来说明增强的 IDEAS,该研究使用 Fogg 的微小习惯行为模型通过太极拳来改善癌症患者的睡眠。