ArticleAnnals of operations research2023
Development of a new personalized staff-scheduling method with a work-life balance perspective: case of a hospital.
Article in Annals of operations research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 23 citations in OpenAlex.
- Deep learning-based physiological risk stratification in night-shift hospital workers.Scientific reports · 2026Article
- Shift nurses' work quality and job satisfaction after implementing the Inha University hospital nursing AI scheduling system (IH-NASS).BMC nursing · 2025Article
- Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study.JMIR formative research · 2025Article
- Article
- Factors Affecting Patients' Atttendance for Periodontal Follow-up Visits after Crown Lengthening Surgery.Oral health & preventive dentistry · 2024Article
- Precision Workforce Management for Radiographers: Monitoring and Managing Competences with an Automatic Tool.Journal of personalized medicine · 2024Article
- Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Burnout rates and dissatisfaction among healthcare workers remain high due to long working hours. One possible solution to this problem is to let them choose their weekly working hours and starting times in order to achieve a work-life balance. Moreover, a scheduling process that responds to changing healthcare demands at different times of the day should increase work efficiency in hospitals. In this study, a methodology and software were developed to schedule hospital personnel, taking into account their preferences regarding working hours and starting time. The software also allows the hospital management to determine the number of staff needed at different times of the day. Three methods and five working-time scenarios characterized by different divisions of working time are proposed to solve the scheduling problem. The Seniority score Priority assignment Method appoints personnel prioritizing seniority, whereas the newly developed Balanced and Fair assignment Method and Genetic Algorithm Method aim for a more nuanced distribution. The methods proposed were applied to physicians in the internal diseases department in a specific hospital. Weekly/monthly scheduling of all employees was carried out with the software. The results of scheduling factoring in work-life balance, and the performances of algorithms are shown for the hospital where the application was trialled.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.