Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations
Open accessAbstract
BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every 15 minutes, to ascertain that they are safe and breathing. However, while this practice ensures patient safety, it can also disturb patients' sleep, which in turn can impact negatively on their recovery. OBJECTIVE: This article describes the process of introducing artificial intelligence ('digitally assisted nursing observations') in an acute mental health inpatient ward, to enable staff to carry out the hourly and the 15 minutes observations, minimising disruption of patients' sleep while maintaining their safety. FINDINGS: The preliminary data obtained indicate that the digitally assisted nursing observations agreed with the observations without sensors when both were carried out in parallel and that over an estimated 755 patient nights, the new system has not been associated with any untoward incidents. Preliminary qualitative data suggest that the new technology improves patients' and staff's experience at night. DISCUSSION: This project suggests that the digitally assisted nursing observations could maintain patients' safety while potentially improving patients' and staff's experience in an acute psychiatric ward. The limitations of this study, namely, its narrative character and the fact that patients were not randomised to the new technology, suggest taking the reported findings as qualitative and preliminary. CLINICAL IMPLICATIONS: These results suggest that the care provided at night in acute inpatient psychiatric units could be substantially improved with this technology. This warrants a more thorough and stringent evaluation.
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The shared perspective of preparedness and optimism resonates with prior research underlining nurses' enthusiasm in exploring AI contributions to nursing practice.
“This shared perspective resonates with prior research, underlining nurses' enthusiasm in exploring the potential contributions of AI to nursing practice [14,54].”
From Artificial intelligence in future nursing care: exploring perspectives of nursing professionals - a descriptive qualitative study (2024) · cites this paper as [14]
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- Authors
- Barrera, A., Gee, C., Wood, A., Gibson, O., Bayley, D., & Geddes, J.
- Affiliations
- University of Oxford, Oxford, UK
- Oxford Health NHS Foundation Trust (GB)
- LIO (GB)
- Venue
- Evidence-Based Mental Health
- Publisher
- BMJ
- Published
- 2020-02
- Volume
- 23
- Issue
- 1
- Pages
- 34-38
- ISSN
- 1362-0347 (ISSN-L)
- 1468-960X
- PMC
- PMC7034347
- OpenAlex
- W3006635320
- Cited by
- 79
- References
- 17
- Citations by year
- 2026: 12 · 2025: 12 · 2024: 16 · 2023: 16 · 2022: 10 · 2021: 11 · 2020: 1
- FWCI
- 8.68
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Evidence-Based Mental Health (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Oxford Health Biomedical Research Centre (Part-time nursing research role (AW))
- NIHR Oxford Collaboration for Leadership in Applied Health Research and Care (Part-time nursing research role (AW))
- Topics
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Psychology › Clinical Psychology › Psychiatric care and mental health services
- Keywords
- artificial intelligence, nursing observation, acute psychiatric inpatient care, sleep disruption, digital health technologies, patient experience, employee experience, technology implementation
- MeSH terms
- Acute Disease, Adult, Artificial Intelligence, Humans, Monitoring, Physiologic, Psychiatric Department, Hospital, Psychiatric Nursing, Observation, Qualitative Research, Patient Safety
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