Intelligent Model of Nursing Shift in Tehran University of Medical Sciences, Tehran, Iran - Mashallah Torabi; Maryam Goodarzi; Maryam Ahmadi; Hamideh Hamidi; Samira Elmi; Fatemeh Golmah; Samira Mortezaie; Parisa Nezari (Tehran University of Medical Sciences, 2022)
Background: Nurses play a key role in increasing the efficiency of healthcare systems. Given the 24-hour performance of hospitals and the small number of nurses in the field of treatment, it is quintessential to re-shift them in the hospital. This study set out to achieve coherence in nursing shift planning and justice in the order of shifts in hospital. Methods: This applied and a developmental study was performed from 2019 to 2020. We used genetic algorithm to provide operational solutions and define flexible shifts and plan nurses' working hours in Yas Hospital, Tehran University of Medical Sciences Hospital, Tehran, Iran. Results: Based on the selection of each nurse and determining the approved shifts of each ward, the possibility of appropriate planning was provided to determine the required shifts per month and to estimate the needs of each department. Conclusion: Using genetic algorithm and nursing shift in office automation console provides useful tools for managers at all organizational levels, according to which a good balance between the hospital's need for nurse and nurses' demands in different time periods.