基于过程挖掘的临床路径Petri网建模  

Clinical Pathway Modeling by Petri Net Based on Process Mining

作　　者：余建波[1] 郑小云 李传锋 董晨阳 YU Jianbo;ZHENG Xiaoyun;LI Chuanfeng;DONG Chenyang(School of Mechanical Engineering, Tongji University, Shanghai 201804, China)

机构地区：[1]同济大学机械与能源工程学院,上海201804

出　　处：《同济大学学报（自然科学版）》2018年第4期524-534,549,共12页Journal of Tongji University:Natural Science

基　　金：国家自然科学基金(51375290;71777173;中央高校基本科研业务费专项基金;上海市科技创新行动计划(17511109204);上海市航天科技创新基金(SAST2015054)

摘　　要：提出基于统计α算法的临床路径Petri网模型,将Petri网和基于统计α算法的过程挖掘算法集成,从事件日志中挖掘重要信息,获得完善的诊疗流程,并在此基础上建立Petri网模型,有效实现诊疗流程的优化和改进.通过仿真数据试验,验证了本文提出的统计α算法相较于经典α算法在准确度和运行时间上有着较大的优势.并将模型运用到临床路径真实数据上,证明了模型的有效性和准确性.This paper proposed a clinical pathway Petri net model based on statistical a-algorithm, which integrate the basic Petri net with process mining algorithm based on statistical a-algorithm. This model can obtain medical procedure from event log and build clinical pathway Petri net model on the procedure. The medical procedure could be optimized and improved by analysis of the Petri net model. Simulation results shows that the statistical a-algorithm performs better in accuracy and efficiency than classic α- algorithm. The proposed model is verified on the real data of clinical pathway.

关 键 词：临床路径 统计α算法 PETRI网建模 过程挖掘算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]