Journal of nursing management · 2026
Data-Driven Scheduling Strategies to Minimize Fatigue in Rotating Night-Shift Nurses.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
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Kim Su Hyun, Jang Geunsoo, Lee Yeonsu, Lee Sijin, Hwang Huiyoung, Shin Seunghwa, Jeon Bomin, Youn Sol, Lee Hyojung
Аннотация
BACKGROUND: Shift work is essential for continuous patient care but disrupts circadian rhythms, leading to increased fatigue, burnout, and the risk of errors. Existing guidelines for managing nurse fatigue remain broad and often lack actionable strategies for roster design and staffing.
AIM: This study aimed to identify optimal shift patterns and sleep-wake schedules that minimize fatigue among rotating night-shift nurses, using mathematical modeling to provide actionable recommendations for nursing management.
METHODS: A quantitative observational study was conducted with 273 nurses working 8-h rotating three-shift systems in three Korean hospitals. Sleep was monitored over 14 days using wearable devices, supplemented with survey data. Fatigue was estimated using a validated mathematical model based on the two-process model of sleep regulation, and simulations were applied to evaluate alternative shift sequences and sleep-wake strategies.
RESULTS: Night shifts resulted in the shortest sleep (mean 5.0 h) and the highest fatigue, with over half of work hours predicted to be spent in a fatigued state. Three consecutive day or evening shifts yielded the most favorable outcomes, with cumulative sleep exceeding 26 h and fatigue limited to less than 1 hour. Conversely, three consecutive night shifts resulted in the poorest outcomes, with fatigue affecting 34.7% of work hours. Quick return patterns (< 11 h between shifts) significantly increased fatigue despite comparable sleep durations. Model-derived recommendations-such as immediate postshift sleep following night duty-improved recovery and reduced cumulative fatigue.
CONCLUSIONS: Limiting consecutive night duties, avoiding quick returns, and supporting tailored sleep routines may reduce fatigue among rotating night-shift nurses.
IMPLICATIONS FOR NURSING MANAGEMENT: These findings provide managers with practical, evidence-based guidance for roster design, policy development, and staff education. Incorporating fatigue modeling into workforce planning can enhance nurse well-being, reduce error risks, and promote sustainable healthcare delivery.
AIM: This study aimed to identify optimal shift patterns and sleep-wake schedules that minimize fatigue among rotating night-shift nurses, using mathematical modeling to provide actionable recommendations for nursing management.
METHODS: A quantitative observational study was conducted with 273 nurses working 8-h rotating three-shift systems in three Korean hospitals. Sleep was monitored over 14 days using wearable devices, supplemented with survey data. Fatigue was estimated using a validated mathematical model based on the two-process model of sleep regulation, and simulations were applied to evaluate alternative shift sequences and sleep-wake strategies.
RESULTS: Night shifts resulted in the shortest sleep (mean 5.0 h) and the highest fatigue, with over half of work hours predicted to be spent in a fatigued state. Three consecutive day or evening shifts yielded the most favorable outcomes, with cumulative sleep exceeding 26 h and fatigue limited to less than 1 hour. Conversely, three consecutive night shifts resulted in the poorest outcomes, with fatigue affecting 34.7% of work hours. Quick return patterns (< 11 h between shifts) significantly increased fatigue despite comparable sleep durations. Model-derived recommendations-such as immediate postshift sleep following night duty-improved recovery and reduced cumulative fatigue.
CONCLUSIONS: Limiting consecutive night duties, avoiding quick returns, and supporting tailored sleep routines may reduce fatigue among rotating night-shift nurses.
IMPLICATIONS FOR NURSING MANAGEMENT: These findings provide managers with practical, evidence-based guidance for roster design, policy development, and staff education. Incorporating fatigue modeling into workforce planning can enhance nurse well-being, reduce error risks, and promote sustainable healthcare delivery.