Semantic Web Based System for Stroke Clinical Pathways Automation

根据世界卫生组织，中风被认为是全球第二大死亡原因，也是导致严重和长期残疾的主要原因，包括瘫痪、感觉障碍、记忆和思维问题以及情绪障碍。值得一提的是，在所有其他类型的中风中，颈动脉疾病（CAD）导致的中风往往是最多的残疾。加拿大中风大会的一项研究表明，中风管理对加拿大健康护理的财务成本总计约为每年25亿加元的加拿大税收。鉴于这些事实，Qwantech正在投资软件技术，允许CAD临床路径的计算机化。临床路径（CP）是医疗保健计划或图表，详细说明了患有特定疾病的患者护理的基本步骤，描述了患者的预期进展，并减少了医疗实践中任何不期望的变化的发生。目前，大多数CP都是基于纸张的，需要解决自动化的挑战，以提高医疗效率和质量。特别是，Qwantech正在开发软件技术，可以帮助联合收割机CAD临床路径与工作场所使用的医疗信息系统相结合。在这项研究中，我们将协助Qwantech应用最先进的语义网技术，在现有的电子病历（EMR）系统上部署临床路径。本体将用于建模CAD CP领域的术语，语义Web规则语言将用于建模CAD领域的推理规则。在该模型中，CP可以对收集到的规则和知识进行推理，并在CAD的诊断和管理过程中提供自动化的医疗指导和错误检查。在这项研究中开发的算法将允许Qwantech开发软件，使护理团队成员之间能够更好地协作和临床知识共享。这种技术还将确保提高生产率并降低成本。

Stroke is considered the second leading cause of death worldwide according to the World Health Organization.It is also a leading cause of severe and long-term disabilities, including paralysis, sensory disturbances,problems with memory and thinking, and emotional disturbances. It is worth mentioning that strokes due toCarotid Artery Disease (CAD) tend to cause the most disability among all other types of strokes. A study bythe Canadian Stroke Congress showed that the financial cost of stroke management on Canada's health caresystem amounts to a total of about $2.5 billion per year of Canadian's tax dollar. Given these facts, Qwantech isinvesting in software technology that allows computerization of CAD clinical pathways. Clinical Pathways(CPs) are health care plans or charts that detail the essential steps in the care of patients with a specific disease,describe the expected progress of the patient, and decrease the occurrence of any undesired variability ofmedical practice. At present, most CPs are paper-based and there is a need to address the challenge ofautomating them in order to enhance healthcare efficiency and quality. In particular, Qwantech is investigatingsoftware technology that can help combine CAD clinical pathways with medical information systems used inthe workplace.In this research, we will assist Qwantech to apply state of the art Semantic Web technology to deploy clinicalpathways on existing Electronic Medical Records (EMR) systems. Ontology will be used to model CAD CPdomain terms, and Semantic Web Rule language will be used to model CAD domain inference rules. In thismodel, the CP could reason over the collected rules and knowledge, and provide automated medical guidanceand error checking during the diagnosis and management of CAD. The algorithms to be developed in thisresearch will allow Qwantech develop software that enable better collaboration and clinical knowledge sharingamongst members of caregiver team. Such technology will also ensure better productivity and reduce costs.