Paper Info
Title
Modeling Clinical Activities Based On Multi-Perspective Declarative Process Mining With Openehr'S Characteristic
Abstract
Background It is significant to model clinical activities for process mining, which assists in improving medical service quality. However, current process mining studies in healthcare pay more attention to the control flow of events, while the data properties and the time perspective are generally ignored. Moreover, classifying event attributes from the view of computers usually are difficult for medical experts. There are also problems of model sharing and reusing after it is generated. Methods In this paper, we presented a constraint-based method using multi-perspective declarative process mining, supporting healthcare personnel to model clinical processes by themselves. Inspired by openEHR, we classified event attributes into seven types, and each relationship between these types is represented in a Constrained Relationship Matrix. Finally, a conformance checking algorithm is designed. Results The method was verified in a retrospective observational case study, which consists of Electronic Medical Record (EMR) of 358 patients from a large general hospital in China. We take the ischemic stroke treatment process as an example to check compliance with clinical guidelines. Conformance checking results are analyzed and confirmed by medical experts. Conclusions This representation approach was applicable with the characteristic of easily understandable and expandable for modeling clinical activities, supporting to share the models created across different medical facilities.
Year
DOI
Venue
2020
10.1186/s12911-020-01323-7
BMC MEDICAL INFORMATICS AND DECISION MAKING
Keywords
DocType
Volume
Clinical events, Declarative modeling, Multi-perspective, openEHR, Process mining
Journal
20
Issue
ISSN
Citations 
14
1472-6947
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Haifeng Xu104.06
Jianfei Pang203.04
Xi Yang301.69
Jinghui Yu401.69
Xuemeng Li502.37
Zhao Dongsheng606.42