Artificial intelligence approach to optimise safety for hospitalised patients with dementia
ML techniques can provide insights into situational factors and active failures that drive dementia-related safety events. These insights can inform targeted interventions such as specialised staff training for behavioural symptoms management and pharmacist-led medication optimisation, to enhance care and safety for hospitalised people living with dementia.
Authors
- Nicole E. Werner (ORCID: https://orcid.org/0000-0003-2363-9491)
- Yijung K. Kim (ORCID: https://orcid.org/0000-0001-9450-8208)
- Raj M. Ratwani (ORCID: https://orcid.org/0000-0002-8623-6123)
- Karl Eric De Jonge
- Azade Tabaie (ORCID: https://orcid.org/0000-0003-1869-5923)
- Lauren R. Bangerter (ORCID: https://orcid.org/0000-0001-8452-2495)
- Allan Fong (ORCID: https://orcid.org/0000-0002-7550-1569)
- Garrett Zabala
Institutions
- MedStar Washington Hospital Center (US)
- Vanderbilt University (US)
- MedStar Health (US)
Publication Details
- Journal
- BMJ Open Quality
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1136/bmjoq-2024-003270
- Primary Topic
- Clinical Reasoning and Diagnostic Skills
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agency for Healthcare Research and Quality