Computer-based Decision Support for Management of Comorbid Diseases

临床实践指南(CPG)是一种基于知识的工具，用于特定疾病的患者管理，其中概括了在可能的诊断和开出最合适的治疗计划方面的最佳实践。然而，由于指南中与药物-药物或药物-疾病的不良相互作用相关的不一致，不加缓和地同时应用针对共病患者的特定疾病指南往往会产生不希望看到的后果。尽管管理合并疾病的患者具有临床和社会重要性，但关于自动缓解同时使用的CPG中可能存在的不良相互作用的研究很少。拟议的研究计划旨在填补这一空白。拟议研究的主要目标是开发方法，通过支持护理点的循证决策，帮助改善对合并疾病患者的护理质量。这转化为对创建可计算的CPG模型的研究，该模型：-允许对患有并存疾病的患者的指南的同时应用进行建模，-被自动缓解以解决不良交互作用，-在护理点以不引人注目的方式执行。提出的研究具有应用性和方法论轴心。应用轴是关于支持对合并疾病患者的循证管理，而方法学轴是关于自动检测和缓解不良相互作用的方法。研究的具体目标被定义为：-根据CPG形式自动构建可计算的逻辑指南模型，-为多个CPG构建约束逻辑编程(CLP)模型，-识别不利交互作用，-减轻不利交互作用，-使用临床案例研究验证概念决策支持。

A clinical practice guideline (CPG) is a knowledge-based tool for disease-specific patient management that encapsulates best practices in deriving at possible diagnoses, and prescribing the most appropriate treatment plan. However, the unmitigated concurrent application of disease-specific guidelines for comorbid patients often has undesired consequences due to the inconsistencies in the guidelines associated with adverse drug-drug or drug-disease interactions. Despite the clinical and social importance of managing patients with comorbid diseases, there is little research on the automatic mitigation of adverse interactions that might be present in concurrently used CPGs. The proposed research program is designed to fill the void. The main goal of the proposed research is to develop methodologies that help to improve the quality of care for patients with comorbid diseases by supporting evidence-based decision-making at the point of care. This translates into research on creating a computable CPG model that: - allows for modeling concurrent application of the guidelines for a patient with comorbid diseases, - is automatically mitigated to address adverse interactions, - is executed at the point of care in an unobtrusive manner. Proposed research has applied and methodological axis. The applied axis is about supporting evidence-based management of patients with comorbid diseases, while the methodological axis is about the methodologies for automatic detection and mitigation of the adverse interactions. Specific aims of the research are defined as:- Automatic construction of computable logical guideline models from the CPG formalisms, - Building constraint logic programming (CLP) model for the multiple CPGs, - Identification of adverse interactions, - Mitigating the adverse interactions,- Proof of concept decision support using clinical case studies.