Process mining to optimize palliative patient flow in a high-volume radiotherapy department

Area of Science:

• Radiotherapy
• Palliative Care
• Process Mining

Background:

• Palliative patients in radiotherapy often face suboptimal management and long waiting times.
• Event-log analysis of palliative patient data can inform shared guidelines for improved patient flow.
• Optimizing patient flow is crucial for effective palliative care delivery.

Purpose of the Study:

• To analyze palliative patient flow in a radiotherapy department using process mining.
• To identify opportunities for optimizing patient flow and decision-making.
• To evaluate the effectiveness of existing palliative care guidelines.

Main Methods:

• Process mining methodology applied to palliative patient flow data.
• Analysis of event-logs from 500 palliative radiation treatment plans (290 patients).
• Process discovery and conformance checking against a theoretical model.

Main Results:

• Dose prescriptions varied: 8 Gy (10%), 20 Gy (49.8%), 30 Gy (31.8%), and others (7.8%).
• Conformance checking indicated that event-logs align with the theoretical process model.
• The study provides data-driven insights into current palliative patient pathways.

Conclusions:

• Results partially validate the implemented palliative patient care guideline.
• Process mining offers valuable insights for improving palliative patient care flows.
• The study supports the use of process mining for enhancing radiotherapy patient management.