Actively Recruiting
Safe AI-assisted Fall Prevention Through Evidence in Swedish Hospitals A Multi-Method Observational Study Evaluating AI Impact on Patient Safety and Care Workflows
Led by Halmstad University · Updated on 2026-03-31
23425
Participants Needed
1
Research Sites
N/A
Total Duration
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AI-Summary
What this Trial Is About
This research aims to explore how AI-assisted fall prevention systems are integrated into everyday hospital care and what effects they have. It focuses on understanding their impact on patient safety, healthcare workers' roles, and the use of healthcare resources. The project is a large, multi-method observational study conducted across multiple hospitals in the Västra Götaland Region of Sweden from 2026 to 2028, involving collaboration between Halmstad University and local hospitals. The study observes the implementation of AI-based fall prevention technologies that use real-time sensors and alerts to help reduce in-hospital falls. It includes surveys, interviews, observations, and retrospective data analysis to evaluate how these systems work in practice. Additionally, the project involves learning labs that bring together patients, relatives, and healthcare staff to co-create strategies for sustaining the use of AI-assisted fall prevention in hospital settings. Participants will be involved through interviews, surveys, and observations, including patients, family members, healthcare staff, and managers at participating hospitals. The study collects data such as fall rates from medical records and gathers feedback on system use and integration. The main outcome measured is the fall rate from January 2025 to December 2028. The research also monitors how well the AI system supports patient safety and healthcare workflows over time.
CONDITIONS
Brief Title
AI-assisted Fall Prevention Through Evidence
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Be employed at one of the participating hospitals
- Hold a role as a key stakeholder in the implementation work
- Have experience with the implementation of the AI-assisted fall prevention
- Have the ability to understand and communicate in Swedish
- Be employed as a manager at one of the participating hospitals with experience of the AI system
- Be employed as staff on a ward where the AI-assisted fall prevention is implemented
- Be a patient on a ward where the AI-assisted fall prevention has been implemented, or a family member involved in such care
- Be 18 years of age or older
- Have the ability to provide informed consent
- Be a patient representative or involved in a patient group where falls are an issue
- Have the ability to access and respond to web-based surveys in Swedish
- Patients cared for up to 24 months after or 12 months before AI system implementation
You will not qualify if you...
- Insufficient proficiency in Swedish to participate or understand the study
- Lack the ability to provide informed consent
- Patients who received care outside the defined time periods relative to AI implementation
- Not employed on wards where AI-assisted fall prevention is implemented
- Lack the ability to access or respond to surveys in Swedish
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person or remote) for eligibility confirmation
Duration - Up to 4 years
Participants who undergo routine care are observed to evaluate the implementation and impact of the AI-assisted fall prevention system in hospital settings.
Surveys, interviews, and observations conducted periodically during routine care
Duration - Up to 24 months after AI system implementation for patients
Participants are followed up to assess long-term effects on patient safety, healthcare workflows, and resource use after implementation of the AI-assisted fall prevention system.
Periodic assessments via web-based surveys and interviews
Trial Site Locations
Total: 1 location
1
Sahlgrenska Hospital
Gothenburg, Sweden
Actively Recruiting
Research Team
P
Project leader
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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