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Analyzing Healthcare Processes with Incremental Process Discovery: Practical Insights from a Real-World Application.

Daniel Schuster1,2, Elisabetta Benevento3,4, Davide Aloini3

  • 1Data Science & Artificial Intelligence, Fraunhofer Institute for Applied Information Technology FIT, Schloss Birlinghoven, 53757 Sankt Augustin, Germany.

Journal of Healthcare Informatics Research
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Summary
This summary is machine-generated.

Interactive process mining enhances healthcare analysis by integrating domain knowledge. This hybrid intelligence approach overcomes challenges like data variability and quality issues in process discovery.

Keywords:
Business process managementDomain knowledgeInteractive process discoveryProcess miningProcess modeling

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Area of Science:

  • Computer Science
  • Information Systems
  • Healthcare Informatics

Background:

  • Traditional process mining tools operate as "black boxes" with limited analyst interaction.
  • Recent advancements focus on hybrid intelligence, incorporating domain knowledge into process mining.
  • Interactive process discovery techniques are emerging but lack practical application studies.

Purpose of the Study:

  • To investigate the practical application of incremental and interactive process discovery in the healthcare domain.
  • To evaluate the effectiveness of hybrid intelligence in addressing healthcare-specific process mining challenges.

Main Methods:

  • A case study was conducted in the healthcare sector.
  • Employed incremental and interactive process discovery techniques.
  • Focused on integrating domain knowledge for process analysis.

Main Results:

  • The interactive process mining approach effectively addressed challenges in healthcare data.
  • Demonstrated successful application of hybrid intelligence in a complex domain.
  • Showcased the ability to handle high process execution variability and poor data quality.

Conclusions:

  • Interactive process discovery is a viable and effective approach for healthcare process mining.
  • Hybrid intelligence can significantly improve process analysis in complex, real-world settings.
  • Further research into interactive techniques in specialized domains is warranted.