Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study
AI-supported scheduling systems can significantly enhance fairness, transparency, and efficiency in nurse scheduling. However, concerns regarding AI reliability, adaptability to individual needs, and human oversight must be addressed. A hybrid approach integrating AI recommendations with human decision-making may be optimal. Future research should explore the broader implementation of AI-driven scheduling models and assess their impact on nurse satisfaction and patient outcomes over time.
Authors
- Maisa Gerlach (ORCID: https://orcid.org/0009-0001-4203-9152)
- Christoph Golz (ORCID: https://orcid.org/0000-0003-1711-5106)
- Jannic Stefan Bieri (ORCID: https://orcid.org/0009-0000-8325-1398)
- Murat Sariyar (ORCID: https://orcid.org/0000-0003-3432-2860)
- Fabienne Josefine Renggli
Institutions
- Bern University of Applied Sciences (CH)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2025-03-07
- DOI
- https://doi.org/10.2196/67747
- Citations
- 8
- Primary Topic
- Scheduling and Timetabling Solutions
- Type
- article
- Field-Weighted Citation Impact
- 16.85