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Decision support for comorbid conditions via execution-time integration of clinical guidelines using transaction-based semantics and temporal planning
Artificial Intelligence in Medicine ( IF 6.1 ) Pub Date : 2021-06-25 , DOI: 10.1016/j.artmed.2021.102127
William Van Woensel 1 , Syed Sibte Raza Abidi 1 , Samina Raza Abidi 2
Affiliation  

In case of comorbidity, i.e., multiple medical conditions, Clinical Decision Support Systems (CDSS) should issue recommendations based on all relevant disease-related Clinical Practice Guidelines (CPG). However, treatments from multiple comorbid CPG often interact adversely (e.g., drug-drug interactions) or introduce operational inefficiencies (e.g., redundant scans). A common solution is the a-priori integration of computerized CPG, which involves integration decisions such as discarding, replacing or delaying clinical tasks (e.g., treatments) to avoid adverse interactions or inefficiencies. We argue this insufficiently deals with execution-time events: as the patient's health profile evolves, acute conditions occur, and real-time delays take place, new CPG integration decisions will often be needed, and prior ones may need to be reverted or undone. Any realistic CPG integration effort needs to further consider temporal aspects of clinical tasks—these are not only restricted by temporal constraints from CPGs (e.g., sequential relations, task durations) but also by CPG integration efforts (e.g., avoid treatment overlap). This poses a complex execution-time challenge and makes it difficult to determine an up-to-date, optimal comorbid care plan. We present a solution for dynamic integration of CPG in response to evolving health profiles and execution-time events. CPG integration policies are formulated by clinical experts for coping with comorbidity at execution-time, with clearly defined integration semantics that build on Description and Transaction Logics. A dynamic planning approach reconciles temporal constraints of CPG tasks at execution-time based on their importance, and continuously updates an optimal task schedule.



中文翻译:

通过使用基于事务的语义和时间规划的临床指南的执行时间集成对合并症的决策支持

在合并症的情况下,即多种疾病,临床决策支持系统 (CDSS) 应根据所有相关疾病相关的临床实践指南 (CPG) 发布建议。然而,来自多种合并症 CPG 的治疗通常会产生不利的相互作用(例如药物相互作用)或导致操作效率低下(例如冗余扫描)。一个常见的解决方案是计算机化 CPG 的先验整合,这涉及整合决策,例如放弃、替换或延迟临床任务(例如,治疗)以避免不利的相互作用或低效率。我们认为这不足以处理执行时间事件:随着患者健康状况的发展、急性情况的发生和实时延迟的发生,通常需要新的 CPG 集成决策,之前的可能需要恢复或撤消。任何现实的 CPG 集成工作都需要进一步考虑临床任务的时间方面——这些不仅受到 CPG 的时间限制(例如,顺序关系、任务持续时间)而且还受到 CPG 集成工作(例如,避免治疗重叠)的限制。这带来了复杂的执行时间挑战,并且难以确定最新的、最佳的合并症护理计划。我们提出了一种动态集成 CPG 的解决方案,以响应不断变化的健康状况和执行时间事件。CPG 集成策略由临床专家制定,用于在执行时处理合并症,并具有基于描述和事务逻辑的明确定义的集成语义。

更新日期:2021-07-06
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