A Pipeline for the Usage of the Core Data Set of the Medical Informatics Initiative for Process Mining - A Technical Case Report.
Introduction: Process Mining (PM) has emerged as a transformative tool in healthcare, facilitating the enhancement of process models and predicting potential anomalies. However, the widespread application of PM in healthcare is hindered by the lack of structured event logs and specific data privacy...
| Publicado en: | Studies in Health Technology & Informatics Vol. 317; pp. 30 - 40 |
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| Autores principales: | , , , , , , , , , |
| Formato: | proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2024
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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=179603596&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179603596 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2024 vid: 317 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 179603596 179603596 179603596 10.3233/SHTI240835 179603596 ppf: 30 ppct: 10 formats: tig: atl: A Pipeline for the Usage of the Core Data Set of the Medical Informatics Initiative for Process Mining - A Technical Case Report. aug: au: HEIDEMEYER, Hauke AUHAGEN, Leo MAJEED, Raphael W. PEGORARO, Marco BIENZEISLER, Jonas PEEVA, Viki BEYEL, Harry RÖHRIG, Rainer VAN DER AALST, Wil M. P. PULADI, Behrus affil: Institute of Medical Informatics, University Hospital RWTH Aachen, Aachen, Germany sug: subj: Data Mining Methods Health Information Systems Systems Integration Quality of Health Care Quality Assurance Medical Informatics Patient Record Systems Human Funding Source Case Studies Electronic Health Records Academic Medical Centers Germany Germany Data Security Legislation and Jurisprudence Data Quality ab: Introduction: Process Mining (PM) has emerged as a transformative tool in healthcare, facilitating the enhancement of process models and predicting potential anomalies. However, the widespread application of PM in healthcare is hindered by the lack of structured event logs and specific data privacy regulations. Concept: This paper introduces a pipeline that converts routine healthcare data into PM-compatible event logs, leveraging the newly available permissions under the Health Data Utilization Act to use healthcare data. Implementation: Our system exploits the Core Data Sets (CDS) provided by Data Integration Centers (DICs). It involves converting routine data into Fast Healthcare Interoperable Resources (FHIR), storing it locally, and subsequently transforming it into standardized PM event logs through FHIR queries applicable on any DIC. This facilitates the extraction of detailed, actionable insights across various healthcare settings without altering existing DIC infrastructures. Lessons Learned: Challenges encountered include handling the variability and quality of data, and overcoming network and computational constraints. Our pipeline demonstrates how PM can be applied even in complex systems like healthcare, by allowing for a standardized yet flexible analysis pipeline which is widely applicable.The successful application emphasize the critical role of tailored event log generation and data querying capabilities in enabling effective PM applications, thus enabling evidence-based improvements in healthcare processes. pubtype: Academic Journal doctype: proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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