Healthc Inform Res.  2013 Mar;19(1):42-49. 10.4258/hir.2013.19.1.42.

Discovery of Outpatient Care Process of a Tertiary University Hospital Using Process Mining

Affiliations
  • 1Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea. yoosoo0@snu.ac.kr
  • 2School of Technology Management, Ulsan National Institute of Science and Technology, Ulsan, Korea.
  • 3Cyberdigm Co., Seoul, Korea.
  • 4Patient's Affairs, Seoul National University Bundang Hospital, Seongnam, Korea.

Abstract


OBJECTIVES
There is a need for effective processes in healthcare clinics, especially in tertiary hospitals, that consist of a set of complex steps for outpatient care, in order to provide high quality care and reduce the time cost. This study aimed to discover the potential of a process mining technique to determine an outpatient care process that can be utilized for further improvements.
METHODS
The outpatient event log was defined, and the log data for a month was extracted from the hospital information system of a tertiary university hospital. That data was used in process mining to discover an outpatient care process model, and then the machine-driven model was compared with a domain expert-driven process model in terms of the accuracy of the matching rate.
RESULTS
From a total of 698,158 event logs, the most frequent pattern was found to be "Consultation registration > Consultation > Consultation scheduling > Payment > Outside-hospital prescription printing" (11.05% from a total cases). The matching rate between the expert-driven process model and the machine-driven model was found to be approximately 89.01%, and most of the processes occurred with relative accuracy in accordance with the expert-driven process model.
CONCLUSIONS
Knowledge regarding the process that occurs most frequently in the pattern is expected to be useful for hospital resource assignments. Through this research, we confirmed that process mining techniques can be applied in the healthcare area, and through detailed and customized analysis in the future, it can be expected to be used to improve actual outpatient care processes.

Keyword

Process Mining; Hospital Information Systems; Outpatients; Workflow Analysis

MeSH Terms

Ambulatory Care
Delivery of Health Care
Hospital Information Systems
Humans
Mining
Outpatients
Prescriptions
Tertiary Care Centers

Figure

  • Figure 1 Outpatient care mega-process model derived from domain experts.

  • Figure 2 Various process mining algorithms: (A) heuristic miner, (B) fuzzy miner, and (C) comp miner.

  • Figure 3 A major workflow (bold line) discovered by the process mining algorithm.

  • Figure 4 Number of cases and ratio per number of outpatient events.


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