Towards standards based health data extraction facilitating process mining

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

As an evidence based business process analysis method, process mining can be used to investigate variations in clinical practice and delivery of care. However, to enable cross-organizational comparative analysis, healthcare institutions need a common ground for the description and representation of health data. In this work, we analyze different approaches, to describe clinical and patient pathways. The Healthcare Reference Model represents a bottom-up approach, the HL7 v3 RIM as a generic health information model represents a top-down approach and HL7 FHIR, the newest standard of the HL7 family stands in-between. We highlight similarities and differences according to interoperability and process mining tasks. We conclude that a standards (RIM) based top-down approach, and the derived FHIR approach respectively, is able to provide similar insights and, on top of that, operational support for the ETL process on all interoperability levels.

Original languageEnglish
Title of host publication6th International Workshop on Innovative Simulation for Health Care, IWISH 2017, Held at the International Multidisciplinary Modeling and Simulation Multiconference, I3M 2017
EditorsMarco Frascio, Agostino Bruzzone, Francesco Longo, Vera Novak
PublisherCAL-TEK S.r.l.
Pages20-25
Number of pages6
ISBN (Electronic)9781510847699
Publication statusPublished - 2017
Event6th International Workshop on Innovative Simulation for Health Care, IWISH 2017 - Barcelona, Spain
Duration: 18 Sep 201720 Sep 2017

Publication series

Name6th International Workshop on Innovative Simulation for Health Care, IWISH 2017, Held at the International Multidisciplinary Modeling and Simulation Multiconference, I3M 2017

Conference

Conference6th International Workshop on Innovative Simulation for Health Care, IWISH 2017
CountrySpain
CityBarcelona
Period18.09.201720.09.2017

Keywords

  • Data Extraction
  • Evidence Based Medicine
  • Process Mining
  • Semantic Interoperability

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