An analytical solution to patient prioritisation in radiotherapy based on utilitarian optimisation

Area of Science:

• Radiation Oncology
• Medical Physics
• Operations Research

Background:

• Radiotherapy waiting lists can negatively impact patient outcomes.
• Effective patient prioritization strategies are needed to optimize treatment delivery.

Purpose of the Study:

• To develop and evaluate an analytical solution for radiotherapy patient prioritization to maximize local control probability.
• To compare the analytical solution with simulation-based approaches for managing radiotherapy waiting lists.

Main Methods:

• Formulated patient prioritization as an optimization problem to maximize overall population local control probability.
• Derived a simple analytical solution for optimal patient ordering.
• Compared the analytical solution with a simulation model incorporating a numerical optimization routine for daily patient ordering.

Main Results:

• The analytical solution effectively determines an optimal patient ordering for radiotherapy.
• Simulation results using both analytical and numerical methods yielded highly similar outcomes.
• The analytical approach significantly reduced computation time compared to the numerical solution.

Conclusions:

• Incorporating treatment delays and waiting lists into radiotherapy optimization is crucial.
• The derived analytical solution offers an efficient mechanism for optimizing patient prioritization on waiting lists.
• This approach can help mitigate the detrimental effects of radiotherapy waiting lists on patient outcomes.