Reducing Patient Waiting Times for Radiation Therapy and Improving the Treatment Planning Process: a Discrete-event...

Area of Science:

• Oncology
• Health Services Research
• Operations Research

Background:

• Radiotherapy planning is a critical step in cancer treatment.
• Identifying and addressing bottlenecks in the planning process is essential for timely patient care.
• Resource allocation significantly impacts patient throughput and waiting times.

Purpose of the Study:

• To analyze the radiotherapy planning process at the London Regional Cancer Program.
• To identify bottlenecks and quantify the impact of resource levels on waiting times.
• To optimize resource allocation for reduced patient waiting times.

Main Methods:

• Developed a discrete-event simulation model of the patient journey through radiotherapy planning.
• Modeled sequential steps and resource utilization from referral to treatment start.
• Measured the effect of resource changes on ready-to-treat to treatment (RTTT) waiting time and adherence to the 14-day target.

Main Results:

• Increasing dosimetrists by one reduced mean RTTT by 6.55%, achieving 84.92% of patients treated within 14 days.
• Adding one oncologist decreased mean RTTT slightly (10.83 to 10.55 days).
• A 15% increase in patient arrivals increased waiting time by 22.53%; other resource changes had less impact.

Conclusions:

• The simulation model identified key sensitive and non-sensitive system parameters in radiotherapy planning.
• This modeling approach can be adapted by other cancer programs to optimize resource use.
• Effective resource management is crucial for improving efficiency in cancer treatment delivery.