Audit trails in OpenSLEX : paving the road for process mining in healthcare

E. González López De Murillas, E. Helm, H.A. Reijers, J. Küng

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)
1 Downloads (Pure)

Abstract

The analysis of organizational and medical treatment pro-cesses 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 languageEnglish
Title of host publicationInformation Technology in Bio- and Medical Informatics - 8th International Conference, ITBAM 2017, Proceedings
Subtitle of host publication8th International Conference, ITBAM 2017, Lyon, France, August 28–31, 2017, Proceedings
EditorsM. Elena Renda, Andreas Holzinger, Sami Khuri, Miroslav Bursa
Place of PublicationDordrecht
PublisherSpringer
Pages82-91
Number of pages10
ISBN (Electronic)978-3-319-64265-9
ISBN (Print)978-3-319-64264-2
DOIs
Publication statusPublished - 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10443 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Audit trails
  • Healthcare
  • Meta model
  • Process mining

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