A mental workload based patient scheduling model for a Cancer Clinic

This study focused on increasing productivity and efficiency in a Cancer Clinic (CC) taking into consideration mental workload. The demand of the clinic has increased and the clinic recognized the importance of improving the distribution of the resources. Addressing these objectives have a positive impact in operations, however, it also requires managing the human elements of the system in an efficient way. Previous studies have considered human resources as a number representing a fix quantity of available entities without considering their mental capabilities. This research measured mental workload using a perceptual tool, NASA-TLX, as well as physiological responses. The purpose was to balance patient appointments and increase resource utilization while taking into consideration the balance of human workload as a constraint in the mathematical model. Mental workload was included to assure a balance in the capacity of the human resources without overloading them. The mathematical model was able to successfully build a patient scheduling model considering nurses’ workload. It was shown that the model balanced patient appointments throughout the day by leveling the workload of nurses. Sensitivity analysis showed that the patient demand of the center could be increased by up to 50% without negatively impacting patient service.