Exploring needs and challenges for AI in nursing care-results of an explorative sequential mixed methods study
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Abstract Background and aim While artificial intelligence (AI) is being adapted for various life domains and applications related to medicine and healthcare, the use of AI in nursing practice is still scarce. The German Ministry for Education and Research funded a study in order to explore needs, application scenarios, requirements, facilitators and barriers for research and development projects in the context of AI in nursing care. Method A sequential explorative mixed methods study including a stakeholder and expert workshop ( N = 21), expert interviews ( N = 14), an online survey ( N = 53) and a Datathon ( N = 80) was conducted with an emphasis on qualitative data. Results Needs and application scenarios encompassed the micro- and meso-level of care and derived from typical phenomena inherent to nursing care as well as from skill- and staff mix and consequences arising from staff shortages, from the extend of informal care and an associated need for information and education of informal caregivers and nursing assistants. Requirements for and characteristics of successful research and development projects included regulatory, processual, technological, ethical and legal aspects and supportive eco-systems. Conclusion A key element in the design of research projects remains participatory and demand-driven development that aims to bring AI solutions out of the lab and into practice. However, influencing factors remain that are outside the sphere of influence of individual projects, in particular the creation of resilient legal foundations for data use and the use of AI in practice, standardization of data structures and the establishment of infrastructures for data exchange across institutions and projects.
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Seibert et al. (48) highlight barriers such as limited data digitization, privacy and security concerns, and the complexity of nursing tasks that restrict AI to simpler functions.
“Seibert et al. (48) highlight barriers such as limited data digitization, privacy and security concerns, and the complexity of nursing tasks that restrict AI to simpler functions.”
From Artificial intelligence in nursing: an integrative review of clinical and operational impacts (2025) · cites this paper as [48]
Seibert et al. (48) highlight the potential of AI to optimize staff scheduling and skill mix, improve route planning for home care services, and aid in institutional workflow management.
“Seibert et al. (48) highlight the potential of AI to optimize staff scheduling and skill mix, improve route planning for home care services, and aid in institutional workflow management.”
From Artificial intelligence in nursing: an integrative review of clinical and operational impacts (2025) · cites this paper as [48]
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Artificial intelligence in nursing: an integrative review of clinical and operational impacts
Hassanein, S., El Arab, R. A., Abdrbo, A., Abu-Mahfouz, M. S., Gaballah, M. K. F., Seweid, M. M., Almari, M., & Alzghoul, H. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1552372 · Cited by 134 · see citing works
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- Authors
- Seibert, K., Domhoff, D., Fürstenau, D., Biessmann, F., Schulte-Althoff, M., & Wolf-Ostermann, K.
- Affiliations
- University of Bremen (DE)
- IT University of Copenhagen (DK)
- Berliner Hochschule für Technik (DE)
- Corresponding author
- Seibert, Kathrin
- ORCID
- Venue
- BMC Digital Health
- Published
- 2023-05-04
- Volume
- 1
- Issue
- 1
- ISSN
- 2731-684X (ISSN-L)
- OpenAlex
- W4367856437
- Cited by
- 38
- References
- 47
- Citations by year
- 2026: 12 · 2025: 15 · 2024: 9 · 2023: 2
- FWCI
- 1.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Digital Health (publishedVersion, cc-by)
- IT University Of Copenhagen (IT University of Copenhagen) (submittedVersion, other-oa)
- Funders
- German Ministry for Education and Research (16SV8508)
- Universität Bremen
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › General Health Professions › Social Policies and Healthcare Reform
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Keywords
- artificial intelligence in nursing, nursing care, needs assessment, application scenarios, barriers and facilitators, staff shortage, informal care, nursing assistants, regulatory considerations, legal and ethical issues, data utilization, data standardization, participatory research
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