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Development and Evaluation of Research Methods, Instruments and Tools (1348) Organizational Issues (271) Design of Processes and Workflows (293) Focus Groups and Qualitative Research for Human Factors Research (1565) Machine Learning (3229) Nursing in a Hospital Setting (238) Artificial Intelligence (4844)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67747, first published .
AI scheduling in healthcare: doctor, hospital, and AI interface

Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study

Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study

Authors of this article:

Fabienne Josefine Renggli1 Author Orcid Image ;   Maisa Gerlach1 Author Orcid Image ;   Jannic Stefan Bieri1 Author Orcid Image ;   Christoph Golz1 Author Orcid Image ;   Murat Sariyar2 Author Orcid Image
Article Authors Cited by (16) Tweetations Metrics

Journals

  1. Sitters S, O'Callahan K, O'Callahan M, Petersen M, Clasper T, Sicely L. Evaluating the impact of artificial intelligence-driven self-rostering: A dual-site pilot in medical imaging. Radiography 2025;31(6):103150 View
  2. S. M, JR S, S. S, Abirami . AI-Driven Dynamic Scheduling and Real-Time Notification System for Staff Optimization and Conflict Resolution. Journal of Ubiquitous Computing and Communication Technologies 2025;7(3):313 View
  3. Abbas A, Taha Yassen E. Crew Scheduling Problems: A Systematic Literature Review. IEEE Access 2025;13:190196 View
  4. Zhou X, Jomhari N, Farid N, Xing Y. Physicians’ perceptions and attitudes on artificial intelligence in hospital management: a qualitative study. BMC Health Services Research 2025;26(1) View
  5. Biot C, Tabbuso T, Marechal Y. Artificial Intelligence for Hospital Scheduling: A Simple, Reproducible, and Effective Model. Cureus 2026 View
  6. Virgillito D, Ledda C. AI-Mediated Participation and People Sustainability: A Socio-Technical Case Study in Healthcare Shift Scheduling. Systems 2026;14(2):168 View
  7. Jung S, Seo H, Hong S, Doo E. Development of a nurse scheduling program using robotic process automation in Korea. Health Informatics Journal 2026;32(1) View
  8. Li X, Zhu J, Park J, Hong Y. Association between full-scope practice, schedule balance, and burnout among nurses in health professional shortage areas: A cross-sectional study. International Journal of Nursing Studies 2026;179:105516 View
  9. Chorfi H, Ouazene Y, Alaouchiche Y, Yalaoui F. An analytics-driven optimization framework for nurse scheduling under uncertainty. Healthcare Analytics 2026;9:100462 View
  10. Shia B, Peng S, Zhang Q, Lo C, Wang S. Explainable AI for Equitable Nurse Scheduling: Pragmatic Pre-Post Implementation Study. JMIR Nursing 2026;9:e94450 View
  11. Llada Suarez R, del Fresno Marqués L, Antuna-Casal M. Leading Safe Float Pool Mobility. Nurse Leader 2026:102774 View
  12. Min A, Kim I, Lee M, Lee J, Kim S. Artificial intelligence-based nurse scheduling in healthcare: A scoping review of functional features and empirical outcomes. International Journal of Nursing Studies 2026;183:105656 View
  13. Ewing J. How to implement AI-based rostering to ease the administrative burden on nurse managers. Nursing Management 2026 View
  14. Morales L, Perez D, Soto V, Alvarez M, Diaz F. Federated Reinforcement Learning for Coordinated Bed Allocation and Nurse Staffing During Pandemic Surges. Journal of Artificial Intelligence for Healthcare Systems 2025;4(2) View

Books/Policy Documents

  1. Alsufi M, Alsayed S, Alsufi M, Qtaishat F. Breakthroughs in Smart Nursing With Generative AI. View
  2. Assayed S, Atout M, Alsufi M. Breakthroughs in Smart Nursing With Generative AI. View