Process Mining in Standards-based Healthcare Information Systems

Emmanuel Helm

Research output: Types of ThesesDoctoral Thesis

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Healthcare organizations are bureaucracies where groups of trained professionals coordinate their work within functional units or departments. This coordination is based more on the standardization of skills and knowledge rather than on the standardization of work processes. However, by operating the user interfaces of their information systems and medical devices, healthcare personnel triggers a sequence of functions and procedures. From the point of view of the systems and their recorded event logs and databases, these actions constitute a process that is emerging over time. The research discipline of 'process mining' aims to facilitate understanding and improvement of these processes.

This thesis addresses challenges that emanate from the application of process mining techniques to data of healthcare information systems - especially data collection, data integration, and data quality. To this end, a review of existing work in the field process mining in healthcare is conducted and the characteristics of healthcare data are described. Based on the assumption that healthcare information systems strive for interoperability, methods are developed and tested to utilize the (process) data recorded in standardized 'audit trails'. The contributions include an interface to access this data based on Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR). This thesis also presents a case study on guideline compliance checking for melanoma surveillance procedures based on process mining.

The conclusion is that different initiatives and standardization efforts gradually converge towards a better, more interoperable, health IT environment. Syntactic and semantic interoperability pave the road for 'process interoperability' and the standardization of data plays a key role in achieving a better understanding of the complex interactions in healthcare workflows.
Original languageEnglish
QualificationDr. techn.
Awarding Institution
  • Johannes Kepler University Linz
  • Küng, Josef, Supervisor, External person
Award date22 Apr 2021
Publication statusPublished - Mar 2021


  • Process Mining
  • HL7
  • Healthcare
  • Standards


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