Process mining-driven analysis of COVID-19's impact on vaccination patterns.
Process mining is a discipline sitting between data mining and process science, whose goal is to provide theoretical methods and software tools to analyse process execution data, known as event logs. Although process mining was originally conceived to facilitate business process management activitie...
| Published in: | Journal of Biomedical Informatics Vol. 130 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Published: |
Academic Press Inc.
Jun2022
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157222201&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157222201 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15320464 OMB jtl: Journal of Biomedical Informatics issn: 15320464 maglogo: N pubinfo: dt: Jun2022 vid: 130 pid: 735 pub: Academic Press Inc. place: Burlington, Massachusetts artinfo: ui: 157222201 157222201 NLM35525400 10.1016/j.jbi.2022.104081 NLM35525400 157222201 ppct: 1 formats: tig: atl: Process mining-driven analysis of COVID-19's impact on vaccination patterns. aug: au: Augusto, Adriano Deitz, Timothy Faux, Noel Manski-Nankervis, Jo-Anne Capurro, Daniel affil: The University of Melbourne, Australia sug: ab: Process mining is a discipline sitting between data mining and process science, whose goal is to provide theoretical methods and software tools to analyse process execution data, known as event logs. Although process mining was originally conceived to facilitate business process management activities, research studies have shown the benefit of leveraging process mining in healthcare contexts. However, applying process mining tools to analyse healthcare process execution data is not straightforward. In this paper, we show a methodology to: i) prepare general practice healthcare process data for conducting a process mining analysis; ii) select and apply suitable process mining solutions for successfully executing the analysis; and iii) extract valuable insights from the obtained results, alongside leads for traditional data mining analysis. By doing so, we identified two major challenges when using process mining solutions for analysing healthcare process data, and highlighted benefits and limitations of the state-of-the-art process mining techniques when dealing with highly variable processes and large data-sets. While we provide solutions to the identified challenges, the overarching goal of this study was to detect differences between the patients' health services utilization pattern observed in 2020-during the COVID-19 pandemic and mandatory lock-downs -and the one observed in the prior four years, 2016 to 2019. By using a combination of process mining techniques and traditional data mining, we were able to demonstrate that vaccinations in Victoria did not drop drastically-as other interactions did. On the contrary, we observed a surge of influenza and pneumococcus vaccinations in 2020, as opposed to other research findings of similar studies conducted in different geographical areas. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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