Around 40% of cured cancer patients in the European Union are treated with radiotherapy . Delays in cancer treatment are associated with psychological distress and decreased cancer control. To this end, in the Netherlands standards for the access time for radiation treatment are set, which are currently not met in many Dutch oncological centers. The radiotherapy care process (i.e., preparation and treatment) consists of several consecutive stages, possibly related via time constraints. Inadequate capacity allocation may cause large delays, for example due to the capacity allocation of different stages not being aligned, or due to inadequate time division of single resources over different activities. The objective of this study is to increase compliance to access time standards without extending resource capacities, by developing a methodology for optimizing resource capacity allocation in the radiotherapy care process. For radiotherapy, time division of resources over different activities particularly applies to the doctors, who carry out consultations and scan contouring. Time slots for these activities are typically set for each doctor in a cyclic weekly scheme. We develop an integer linear programming (ILP) model to design a weekly doctors’ scheme that minimizes the expected access times of all patient types in the care process and that matches the number of consultation time slots with demand. In several experiments, the quality of the resulting doctors’ schemes is studied via a discrete event simulation model by evaluating the consequences of the schemes in a stochastic environment. Results from a case study in the Academic Medical Center (AMC) in Amsterdam show that the implementation of these schemes may result in a considerable access time reduction. The designed doctor’s schemes are being evaluated for implementation in the AMC.
- Linear Programming
- Capacity allocation