Toward Value-Based Healthcare through Interactive Process Mining in Emergency Rooms: The Stroke Case

Area of Science:

• Health Informatics
• Data Science in Healthcare
• Process Management

Background:

• Value-Based Healthcare (VBHC) implementation requires understanding clinical processes and patient value chains.
• Classical Data Mining techniques lack transparency, hindering trust and adoption in the medical domain.
• Process Mining offers interpretable Data Science solutions for healthcare.

Purpose of the Study:

• To analyze how Process Mining techniques can support healthcare professionals in applying Value-Based Healthcare.
• To demonstrate the utility of Process Mining in characterizing emergency care processes.

Main Methods:

• Exploration of Process Mining techniques applied to emergency care.
• Analysis of critical timing in Stroke treatment using a Question-Driven methodology.
• Utilized a real-world dataset of 9046 emergency episodes from 2145 stroke patients (Jan 2010 - Jun 2017).

Main Results:

• Process Mining effectively differentiates the patient flow of stroke cases from other emergency cases.
• The study highlights the potential of Process Mining to reveal process variations and inefficiencies.
• Demonstrated enhanced understanding of emergency processes for health professionals.

Conclusions:

• Process Mining is a valuable, human-understandable tool for advancing Value-Based Healthcare.
• Improved understanding of clinical processes through Process Mining can lead to enhanced quality of care.
• Process Mining facilitates the transparent application of Data Science in healthcare decision-making.