Abstract
Nowadays and due to the pandemic of COVID-19, nurses are working under the highest pressure benevolently all over the world. This urgent situation can cause more fatigue for nurses who are responsible for taking care of COVID-19 patients 24 hours a day. Therefore, nurse scheduling should be modified with respect to this new situation. The purpose of the present research is to propose a new mathematical model for Nurse Scheduling Problem (NSP) considering the fatigue factor. To solve the proposed model, a hybrid Genetic Algorithm (GA) has been developed to provide a nurse schedule for all three shifts of a day. To validate the proposed approach, a randomly generated problem has been solved. In addition, to show the applicability of the proposed approach in real situations, the model has been solved for a real case study, a department in one of the hospitals in Esfahan, Iran, where COVID-19 patients are hospitalized. Consequently, a nurse schedule for May has been provided applying the proposed model, and the results approve its superiority in comparison with the manual schedule that is currently used in the department. To the best of our knowledge, it is the first study in which the proposed model takes the fatigue of nurses into account and provides a schedule based on it.
Highlights
In working places such as hospitals where the services must be provided continuously, distribution of workforces within different shifts is required
Different studies could be found within the literature which formulated the problem of scheduling nurses, known as the Nurse Scheduling Problem (NSP), from different aspects to provide a timetable for nurses in a hospital [1,2,3]
Motivated by the aforementioned issues, and since, to the best of our knowledge, formulating an NSP considering fatigue factor has not studied yet, in this study, we have suggested a framework to distribute nurses in work shifts with the least fatigue alongside an attention to the additional pressure due to COVID-19 pandemic
Summary
In working places such as hospitals where the services must be provided continuously, distribution of workforces within different shifts is required. Hospital work shifts could impose negative effects on involved nurses such as understaffing, heavy workload, and irregular workscheduling conditions It adversely affects the service quality of healthcare operations and leads to less patient-nurse interaction and patient safety issues. Other negative impacts of shift works on nurses are important such as fatigue, obesity, sleep disorder, and a wide range of chronic diseases [5,6,7,8] It seems that human factors should be combined with NSP if a more productive hospital is needed. Motivated by the aforementioned issues, and since, to the best of our knowledge, formulating an NSP considering fatigue factor has not studied yet, in this study, we have suggested a framework to distribute nurses in work shifts with the least fatigue alongside an attention to the additional pressure due to COVID-19 pandemic. The most important results along with suggestions for future research are presented in the conclusion section
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