Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
Department of Information Systems and Operations Management, Business School, The University of Auckland, Auckland, New Zealand.
J Healthc Eng. 2021 Mar 31;2021:5563651. doi: 10.1155/2021/5563651. eCollection 2021.
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.
如今,由于 COVID-19 大流行,世界各地的护士都在以最高的压力无私地工作。这种紧急情况可能会使那些负责照顾 COVID-19 患者的护士更加疲劳,他们需要 24 小时不间断地工作。因此,护士排班应该根据这种新情况进行修改。本研究的目的是提出一种新的考虑疲劳因素的护士排班问题(NSP)数学模型。为了解决所提出的模型,开发了一种混合遗传算法(GA),为一天的三个班次提供护士排班。为了验证所提出的方法,解决了一个随机生成的问题。此外,为了展示所提出的方法在实际情况下的适用性,该模型已经针对伊朗伊斯法罕的一家医院的一个部门的实际案例进行了求解,该部门收治了 COVID-19 患者。因此,应用所提出的模型为 5 月提供了护士排班,结果表明其优于该部门目前使用的手动排班。据我们所知,这是首次将护士的疲劳因素考虑在内并根据疲劳因素提供排班的研究。