Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare

Eduardo González-López de Murillas; Emmanuel Helm; Hajo A. Reijers; Josef Küng

doi:10.1007/978-3-319-64265-9_7

Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare

Eduardo González-López de Murillas, Emmanuel Helm, Hajo A. Reijers, Josef Küng

Research Center Hagenberg

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

The analysis of organizational and medical treatment processes is crucial for the future development of the healthcare domain. Recent approaches to enable process mining on healthcare data make use of the hospital information systems’ Audit Trails. In this work, methods are proposed to integrate Audit Trail data into the generic OpenSLEX meta model to allow for an analysis of healthcare data from different perspectives (e.g. patients, doctors, resources). Instead of flattening the event data in a single log file the proposed methodology preserves as much information as possible in the first stages of data extraction and preparation. By building on established standardized data and message specifications for auditing in healthcare, we increase the range of analysis opportunities in the healthcare domain.

Original language	English
Title of host publication	Information Technology in Bio- and Medical Informatics - 8th International Conference, ITBAM 2017, Proceedings
Editors	M. Elena Renda, Andreas Holzinger, Sami Khuri, Miroslav Bursa
Publisher	Springer
Pages	82-91
Number of pages	10
ISBN (Print)	9783319642642
DOIs	https://doi.org/10.1007/978-3-319-64265-9_7
Publication status	Published - 2017
Event	28th DEXA Conferences and Workshops - Lyon, France, France Duration: 28 Aug 2017 → 31 Aug 2017 http://www.dexa.org/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10443 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	28th DEXA Conferences and Workshops
Country/Territory	France
City	Lyon, France
Period	28.08.2017 → 31.08.2017
Internet address	http://www.dexa.org/

Keywords

Audit trails
Healthcare
Meta model
Process mining

Access to Document

10.1007/978-3-319-64265-9_7

Cite this

de Murillas, E. G.-L., Helm, E., Reijers, H. A., & Küng, J. (2017). Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare. In M. E. Renda, A. Holzinger, S. Khuri, & M. Bursa (Eds.), Information Technology in Bio- and Medical Informatics - 8th International Conference, ITBAM 2017, Proceedings (pp. 82-91). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10443 LNCS). Springer. https://doi.org/10.1007/978-3-319-64265-9_7

de Murillas, Eduardo González-López ; Helm, Emmanuel ; Reijers, Hajo A. et al. / Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare. Information Technology in Bio- and Medical Informatics - 8th International Conference, ITBAM 2017, Proceedings. editor / M. Elena Renda ; Andreas Holzinger ; Sami Khuri ; Miroslav Bursa. Springer, 2017. pp. 82-91 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The analysis of organizational and medical treatment processes is crucial for the future development of the healthcare domain. Recent approaches to enable process mining on healthcare data make use of the hospital information systems{\textquoteright} Audit Trails. In this work, methods are proposed to integrate Audit Trail data into the generic OpenSLEX meta model to allow for an analysis of healthcare data from different perspectives (e.g. patients, doctors, resources). Instead of flattening the event data in a single log file the proposed methodology preserves as much information as possible in the first stages of data extraction and preparation. By building on established standardized data and message specifications for auditing in healthcare, we increase the range of analysis opportunities in the healthcare domain.",

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de Murillas, EG-L, Helm, E, Reijers, HA & Küng, J 2017, Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare. in ME Renda, A Holzinger, S Khuri & M Bursa (eds), Information Technology in Bio- and Medical Informatics - 8th International Conference, ITBAM 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10443 LNCS, Springer, pp. 82-91, 28th DEXA Conferences and Workshops, Lyon, France, France, 28.08.2017. https://doi.org/10.1007/978-3-319-64265-9_7

Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare. / de Murillas, Eduardo González-López; Helm, Emmanuel; Reijers, Hajo A. et al.
Information Technology in Bio- and Medical Informatics - 8th International Conference, ITBAM 2017, Proceedings. ed. / M. Elena Renda; Andreas Holzinger; Sami Khuri; Miroslav Bursa. Springer, 2017. p. 82-91 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10443 LNCS).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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AB - The analysis of organizational and medical treatment processes is crucial for the future development of the healthcare domain. Recent approaches to enable process mining on healthcare data make use of the hospital information systems’ Audit Trails. In this work, methods are proposed to integrate Audit Trail data into the generic OpenSLEX meta model to allow for an analysis of healthcare data from different perspectives (e.g. patients, doctors, resources). Instead of flattening the event data in a single log file the proposed methodology preserves as much information as possible in the first stages of data extraction and preparation. By building on established standardized data and message specifications for auditing in healthcare, we increase the range of analysis opportunities in the healthcare domain.

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de Murillas EGL, Helm E, Reijers HA, Küng J. Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare. In Renda ME, Holzinger A, Khuri S, Bursa M, editors, Information Technology in Bio- and Medical Informatics - 8th International Conference, ITBAM 2017, Proceedings. Springer. 2017. p. 82-91. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-64265-9_7

Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare

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