基于状态机的急性加重慢性阻塞性肺疾病临床路径优化

摘要

本文提出了基于状态机工作流模型的急性加重慢性阻塞性肺疾病（AECOPD）临床路径。通过响应临床事件，降低AECOPD临床路径的执行难度和增加变异的适应性。与传统的顺序工作流临床路径管理进行对比表明，本文所提出的临床路径建模方法在住院时间、住院平均花费及变异率等临床路径评价指标均较优，能更好地处理AECOPD临床路径执行过程中出现的变异。%We propose a clinical pathway of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) based on state machine. Clinical event-driven response was utilized to control workflow execution of the AECOPD clinical pathway. By comparison with the traditional clinical pathway management, clinical numerical results showed that the proposed method was better in hospitalization days, average hospitalization expense and aberration rate, and better handled the variability in the AECOPD clinical pathway execution.