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Song, Minseok
Business Process Intelligence(BPI) Lab
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  • Process mining

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Discovery of outpatient care process of a tertiary university hospital using process mining

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dc.contributor.author Kim, Eunhye ko
dc.contributor.author Kim, Seok ko
dc.contributor.author Song, Minseok ko
dc.contributor.author Kim, Seongjoo ko
dc.contributor.author Yoo, Donghyun ko
dc.contributor.author Hwang, Hee ko
dc.contributor.author Yoo, Sooyoung ko
dc.date.available 2014-04-10T00:25:57Z -
dc.date.created 2013-07-03 ko
dc.date.issued 2013-03 -
dc.identifier.citation HEALTHCARE INFORMATICS RESEARCH, v.19, no.1, pp.42 - 49 ko
dc.identifier.issn 2093-3681 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/2849 -
dc.identifier.uri http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84878721444 ko
dc.description.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. ko
dc.description.statementofresponsibility open -
dc.language ENG ko
dc.publisher 대한의료정보학회 ko
dc.subject Hospital information systems ko
dc.subject Outpatients ko
dc.subject Process mining ko
dc.subject Workflow analysis ko
dc.title Discovery of outpatient care process of a tertiary university hospital using process mining ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84878721444 ko
dc.type.rims ART ko
dc.description.scopustc 1 *
dc.date.scptcdate 2014-07-12 *
dc.identifier.doi 10.4258/hir.2013.19.1.42 ko
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