Study of AI-Assisted Fall Prevention in Hospital Care Evaluating Implementation, Patient Safety, and Healthcare Workflows

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 Vstra Gtaland 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.

AI-assisted Fall Prevention Through Evidence