MRI-Linac Economics II: Rationalizing Schedules

Area of Science:

• Medical Physics
• Radiation Oncology
• Health Economics

Background:

• MR-guided radiotherapy (MRgRT) offers advanced capabilities like real-time tracking and daily plan adaptation.
• However, MRgRT treatments, especially adaptive ones, are time-intensive, potentially limiting daily patient capacity and impacting financial returns.
• Previous work highlighted the need for efficient scheduling in proton therapy facilities for debt management.

Purpose of the Study:

• To determine the optimal scheduling of different MRgRT treatment plans to maximize capital cost recovery.
• To analyze the financial implications of varying patient caseloads and treatment complexities in an MR-linac (MRL) setting.

Main Methods:

• Modeled MRL scheduling over workdays of varying durations, assuming full patient occupancy.
• Extrapolated treatment times and reimbursement data for adaptive and non-adaptive MRgRT cases.
• Utilized Health Outcomes Plan Payment Survey (HOPPS) data to model reimbursement and derive optimal patient mixes.

Main Results:

• A single MRL treating only non-adaptive IMRT patients would take approximately 4.8 years to cover acquisition costs.
• Including four adaptive MRgRT cases daily reduced the cost recovery period to 2.4 years.
• Non-adaptive treatments are more efficiently handled by conventional linear accelerators, while MRgRT is uniquely suited for adaptive cases.

Conclusions:

• Unlike proton therapy, MR-guided radiotherapy's financial case is strengthened by a clinically optimal caseload of adaptive patients.
• Achieving optimal financial performance requires a substantial and consistent patient volume for MRgRT.
• Future improvements in MRgRT treatment times will enhance cost recovery but necessitate an even larger, appropriate patient pool.