Industrial Management Studies

Scheduling Shifts of Nurses with Considering Job Satisfaction (The Case: Imam Khomeini Hospital in Noor City)

Document Type : Research Paper

Authors

Somayeh Kavianpour 1
Gavad Rezaeian 2

1 M.Sc. in Industrial Engineering, Mazandaran University of Science and Technology, Mazandaran

2 Associate professor, Department of Industrial Engineering, Mazandaran University of Science and Technology, Mazandaran

https://doi.org/10.22054/jims.2017.16659.1592
Abstract
Appropriate scheduling of shifts for nurses, is a critical issue in hospital management. This study improves the scheduling of shifts for nurses in health services organizations to provide lower cost and also to reduce the computational complexity and finally to realize the outcome of these actions on job satisfaction and quality of received services. A linear mathematical model is proposed and since this problem is NP-hard, Genetic Algorithm is provided for solving the problem and finally Implemented in Imam Khomeini hospital of Noor city as a real sample. Computational results and performance of the proposed algorithm in terms of solution quality and computational time were analyzed. Accreditation standards for hospitals as well as the Productivity laws are used in the proposed model. Production of timetables by the proposed model, resulting in improved satisfaction levels of nurses and their job performance.

Keywords

Nurse Scheduling
Meta-Heuristic Genetic Algorithm
Productivity
Job Satisfaction

  1.  

    1. Biviano M, Fritz MS, Spencer W, Dall TM., What is behind HRSA’s projected supply, demand, and shortage of registered nurses? , 2008.
    2. Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. Journal of the American Medical Association 2002; 288(16):1987–93.
    3. P. Daniel Wright, Stephen Mahar, Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction, Omega 41 (2013) 1042–1052.
    4. Bahadori M, Teimourzadeh E, Masteri Farahani H. Factors Affecting Human Resources’ Productivity in a Military Health Organization. Journal of Military Medicine. 2013.
    5. Isken MW, Hancock WM. A heuristic approach to nurse scheduling in hospital units with nonstationary, urgent demand, and a fixed staff size. J Soc Health Syst. 1991; 2(2): 24-41.
    6. Rosenbloom ES, Goertzen NF. Nurse scheduling using mathematical programming. Operations Research 1976; 31: 857–70.
    7. Jaumard B, Semet F, Vovor T. A generalized linear programming model for nurse scheduling. European Journal of Operational Research 1998; 107(1): 1–18.
    8. Alvani M, Ahmadi P. Designing a model for human resources productivity by using management productivity approach. J Res Sci. 2001; 5: 19-27.
    9. Hong Tao, PhD, RN, Carol H. Ellenbecker, PhD RN, Yuefeng Wang, MSN, RN, Ying Li, PhD, RN, Examining Perceptions of Job Satisfaction and Intentions to Leave among ICU Nurses in China, International Journal of Nursing Sciences, 2015.07.04.
    10. Mihyun Park, PhD, RN, Ji Yun Lee, PhD, RN, Sung-Hyun Cho, PhD, RN, Newly Graduated Nurses’ Job Satisfaction: Comparison with Allied Hospital Professionals, Social Workers, and Elementary School Teachers, Asian Nursing Research 6 (2012) 85- 90
    11. Sailaxmi Gandhi, G. Sangeetha, Nurnahar Ahmed, S.K. Chaturvedi, Somatic symptoms, perceived stress and perceived job satisfaction among nurses working in an Indian psychiatric hospital, Asian Journal of Psychiatry, 2014.
    12. Vladica M. Veličković, MD Aleksandar Višnjić, PhD Slađana Jović, PhD Olivera Radulović, PhD Čedomir Šargić, MD Jovan Mihajlović, MPharm Jelena Mladenović, Organizational Commitment and Job Satisfaction Among Nurses in Serbia: A Factor Analysis, Nursing Outlook, 2014.
    13. T.C. Wong, M. Xu, K.S. Chin, A two-stage heuristic approach for nurse scheduling problem: A case study in an emergency department, Computers & Operations Research, 2014.
    14. Rym M’Hallah, Amina Alkhabbaz, Scheduling of nurses: A case study of a Kuwaiti health care unit, Operations Research for Health Care 2 (2013) 1–19.
    15. Mojisola Otegbeye, PhD, Roslyn Scriber, RN, BSN, Donna Ducoin, RN, and Amy Glasofer, DrNP, RN, Marlton, NJ, Designing a data-driven decision support tool for nurse scheduling in the emergency department: A case study of a southern New Jersey emergency department, Emergency Nurses Association, 2015.

     

Industrial Management Studies
Volume 18, Issue 59
Winter 2021
Pages 181-218

meni

Editorial Boards

Submit Manuscript

Contact Us