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Supporting capacity management decisions in healthcare using data-driven process simulation.

Gerhardus van Hulzen1, Niels Martin2, Benoît Depaire1

  • 1Hasselt University, Research group Business Informatics, Martelarenlaan 42, 3500 Hasselt, Belgium.

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Summary
This summary is machine-generated.

Data-Driven Process Simulation (DDPS) aids healthcare capacity management by combining event data with expert knowledge. This approach addresses data quality issues for better resource allocation decisions in hospitals.

Keywords:
Capacity managementData-driven process simulationDomain knowledgeHealthcare processesProcess mining

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Area of Science:

  • Healthcare Management
  • Process Mining
  • Data Science

Background:

  • Healthcare managers face critical capacity management decisions impacting resource allocation (staff, equipment).
  • Hospital Information Systems (HIS) generate extensive process execution data (event logs).
  • Data-Driven Process Simulation (DDPS) is an emerging field leveraging this data for decision support.

Purpose of the Study:

  • To apply DDPS in a real-life healthcare setting for capacity management.
  • To investigate the interplay between process execution data and domain expertise in DDPS.
  • To address challenges in data quality for accurate simulation model discovery.

Main Methods:

  • Case study at a hospital's radiology department.
  • Application of Data-Driven Process Simulation (DDPS) techniques.
  • Analysis of event logs and integration of domain expert knowledge.

Main Results:

  • DDPS, integrating domain expertise, can overcome data quality limitations in HIS event logs.
  • Successful application of DDPS provided decision support for radiology management.
  • Identified key challenges and formulated recommendations for future DDPS research in healthcare.

Conclusions:

  • Combining process execution data with domain expertise is crucial for reliable DDPS in healthcare.
  • Addressing data quality is paramount for accurate simulation models and effective decision-making.
  • Further research is needed to advance DDPS methodologies within the healthcare context.