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Using process mining for automatic support of clinical pathways design.

Carlos Fernandez-Llatas1, Bernardo Valdivieso, Vicente Traver

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Summary
This summary is machine-generated.

This study introduces the PALIA algorithm for automating healthcare process standardization and control. Activity-Based process mining helps infer real processes from logs, reducing variability and improving care quality.

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Area of Science:

  • Health Informatics
  • Process Mining
  • Healthcare Management

Background:

  • Healthcare processes often exhibit variability, impacting care quality and efficiency.
  • Existing technologies for standardization and control require significant resources and knowledge, hindering widespread adoption.
  • Computer-assisted guidance systems can improve professional practice but depend on standardized clinical pathways.

Purpose of the Study:

  • To propose a novel algorithm, PALIA, for automating the standardization and continuous control of healthcare processes.
  • To leverage Activity-Based process mining to infer actual healthcare processes from execution logs.
  • To reduce complexity in designing and deploying standard Clinical Pathways for better quality assurance.

Main Methods:

  • Utilizing the PALIA algorithm, which is based on Activity-Based process mining techniques.
  • Inferring actual healthcare processes by analyzing real execution logs.
  • Applying process mining to design and quality control of healthcare processes.

Main Results:

  • The PALIA algorithm offers a new technological approach to healthcare process standardization.
  • Activity-Based process mining can effectively infer real-world processes from execution data.
  • The proposed method aims to reduce the complexity and resource requirements for creating practical healthcare protocols.

Conclusions:

  • The PALIA algorithm, using Activity-Based process mining, presents a disruptive solution for healthcare process standardization.
  • This approach can significantly aid clinical experts and healthcare systems in reducing practice variability.
  • Effective usage of computer-assisted guidance and assured care quality are enhanced through simplified pathway design and deployment.