Nurses are one of the essential resources in the U.S. healthcare system. They account for approximately 25% of the total hospital operating budget and 44 % of direct care costs [1]. However, healthcare managers face several challenges in managing this vital resource efficiently. These challenges negatively affect the profitability of hospitals and the quality of nurses’ work. Moreover, they can substantially impact the failure of patients’ treatment and its associated costs for the healthcare system. In what follows, we will first elaborate on these challenges. Then we will discuss how Nurse Scheduling Optimization can alleviate them.
Unsatisfactory nurse scheduling is a significant reason for nurse resignation, cited by 30.4% as the main reason behind their resignation [2]. On the one hand, nurses spend much time recording documents through electronic medical records to improve care coordination while their primary responsibility is to care for patients [3, 4]. On the other hand, the shortage of 400,000 registered nurses in the U.S. leads to over-scheduling and inadequate rest periods in hospitals [2, 5]. As a result, more than 50% of full-time nurses work an average of seven hours of overtime each week [3, 4], which has caused only 25% nurse satisfaction in this country [6, 7]. Therefore, offering flexible optimal nurse schedules encourages the stability of the workforce and makes the profession more attractive in a context where there are chronic staff shortages [1]. Moreover, inappropriate nurse schedules can increase the risk of healthcare-associated infections by unnecessarily increasing the number and duration of contacts. These infections substantially impact morbidity and associated costs for the healthcare system, potentially leading to failure of treatment, more prolonged illnesses and hospitalizations, and deaths [2].
Nurse scheduling optimization assigns an optimal number of skilled nurses to each shift to satisfy the demand of a hospital. Nurse scheduling optimization aims to minimize the overall hospital cost and maximize nurses’ preferences while considering the governmental regulations, labor laws, hospital policy, and the status of nurses [8]. Nurse scheduling optimization can improve nurses’ satisfaction up to 34% by creating a fair schedule system that takes care of nurses’ preferences and decreases the overall cost up to 11% [6, 9] and overtime cost by 36% [3]. Moreover, it can lead to up to a 30% reduction in overtime schedule, elimination of an average of 4 hours of manual scheduling, an increase in scheduling fairness with fewer nurses working excessive numbers of shifts or minimum/maximum number of hours per week [3]. Last but not least, nurse scheduling optimization can reorganize nurse schedules to reduce the risk of healthcare-associated infections in hospitals up to 27%. Indeed, it can break potential chains of transmission while ensuring timeliness, the quality of healthcare services, and the minimum number and duration of contacts [2].
References
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[2] Valdano, E., Poletto, C., Boëlle, P. Y., & Colizza, V. (2021). Reorganization of nurse scheduling reduces the risk of healthcare associated infections. Scientific reports, 11(1), 1-12.Â
[3] El Adoly, A. A., Gheith, M., & Fors, M. N. (2018). A new formulation and solution for the nurse scheduling problem: A case study in Egypt. Alexandria engineering journal, 57(4), 2289- 2298.Â
[4] Stimpfel, A. W., Sloane, D. M., & Aiken, L. H. (2012). The longer the shifts for hospital nurses, the higher the levels of burnout and patient dissatisfaction. Health affairs, 31(11), 2501- 2509.Â
[5] Jafari, H., & Salmasi, N. (2015). Maximizing the nurses’ preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm. Journal of Industrial Engineering International, 11(3), 439-458.Â
[6] Rizany, I., Hariyati, R. T. S., Afifah, E., & Rusdiyansyah. (2019). The impact of nurse scheduling management on nurses’ job satisfaction in Army Hospital: a cross-sectional research. Sage Open, 9(2), 2158244019856189.Â
[7] Aiken, L. H., Sermeus, W., Van den Heede, K., Sloane, D. M., Busse, R., McKee, M., … & Kutney-Lee, A. (2012). Patient safety, satisfaction, and quality of hospital care: cross sectional surveys of nurses and patients in 12 countries in Europe and the United States. Bmj, 344.
 [8] Omar, E. R., Garaix, T., Augusto, V., & Xie, X. (2015). A stochastic optimization model for shift scheduling in emergency departments. Health care management science, 18(3), 289-302.
 [9] Wright, P. D., & Mahar, S. (2013). Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction. Omega, 41(6), 1042-1052.
