Modeling clinical activities based on multi-perspective declarative process mining with openEHR's characteristic.
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...
| Publicado en: | BMC Medical Informatics & Decision Making Vol. 20; pp. 1 - 12 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
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BioMed Central
12/15/2020 Supplement 10
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=147623649&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 147623649 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14726947 1CI0 jtl: BMC Medical Informatics & Decision Making issn: 14726947 maglogo: N pubinfo: dt: 12/15/2020 Supplement 10 vid: 20 pid: 24147 pub: BioMed Central artinfo: ui: 147623649 147623649 NLM33323101 147623649 10.1186/s12911-020-01323-7 NLM33323101 147623649 ppf: 1 ppct: 11 formats: tig: atl: Modeling clinical activities based on multi-perspective declarative process mining with openEHR's characteristic. aug: au: Xu, Haifeng Pang, Jianfei Yang, Xi Yu, Jinghui Li, Xuemeng Zhao, Dongsheng affil: Information Center, Academy of Military Medical Sciences, Beijing, China sug: subj: Stroke Retrospective Design Health Care Delivery China Human Comparative Studies Multicenter Studies Evaluation Research Validation Studies Scales Ferrans and Powers Quality of Life Index Questionnaires ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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