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A new approach to solve operations planning problems of the outpatient chemotherapy process

Increasing number of cancer survivors besides efficient medications render demand for cancer service care dramatically increasing. Hence, stakeholders have to investigate new ways in order to enhance cancer treatment operational performance. Outpatient chemotherapy management is a complex problem due to large variability in treatment times as a result of the different cancer types and thus different chemotherapy protocols, and scarce resources. In this paper, we address the operations planning problem of the outpatient chemotherapy process, namely; the assignment of the optimum first day of treatment for a set of new patients in tandem with the presence of existing patients. We propose a mixed-integer programming model that assigns new patients to their starting days of treatment fulfilling two objectives; minimizing the treatment delay of the new patients and the total completion times under resources availability constraints. For the first time in outpatient chemotherapy planning problems, we consider the drug availability constraint and pharmacists working times constraint. We solve the model using CPLEX solver for parameters retrieved from a real case study from the literature, and the results give a global optimum solution. Furthermore, we modify the model to include solving the capacity planning problem, namely, setting the number of nurses and pharmacists as decision variables other than pre-specify them as an input. The results of the modified model provide the optimum number of nurses and pharmacists required each day in a certain planning horizon. Finally, we propose an empirical rule calculating the required nurse treatment time which is dedicated to each patient as a proportion of the infusion time. This rule anticipates the actual working times for nurses, which is useful in balancing the workload for nurses who are working in outpatient chemotherapy units.