Process mining applications in healthcare: a systematic literature review

Area of Science:

• Health Informatics
• Data Science
• Operations Research

Background:

• Digitalization and abundant clinical data fuel process mining in healthcare.
• Process mining enhances workflow optimization, cost reduction, and asset management.
• It identifies inefficiencies, standardizes practices, and supports evidence-based decisions for better care quality.

Purpose of the Study:

• To systematically review the research landscape of process mining applications in healthcare.
• To provide an in-depth understanding of how process mining is applied within healthcare settings.
• To identify key research topics, algorithms, data types, and challenges in healthcare process mining.

Main Methods:

• Systematic literature review of selected articles.
• Analysis of research focusing on process mining algorithms and data employed.
• Categorization of studies based on research topics, algorithm usage, and data characteristics.

Main Results:

• Identified specific research topics within healthcare process mining.
• Assessed the utilization and effectiveness of various process mining algorithms across different healthcare applications.
• Highlighted the types of data used and associated challenges in healthcare process mining.

Conclusions:

• The study provides a comprehensive overview of the current state of process mining in healthcare.
• It offers insights for researchers to identify valuable future research directions.
• Identified critical issues and vulnerabilities in existing healthcare process mining applications.