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AI-assisted Fall Prevention Through Evidence

AI-assisted Fall Prevention Through Evidence

Recruiting
18 years and older
All
Phase N/A

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Overview

The goal of this multi-method study is to investigate how AI-assisted fall-prevention are implemented in routine hospital care what their effects are. The main questions it aims to answer are how these AI systems influence patient safety outcomes, how they affect healthcare professionals work and healthcare resource use, and what factors support or hinder their sustainable integration into hospital environments.

Description

Artificial intelligence (AI) offers new opportunities to strengthen patient safety, particularly in preventing in-hospital falls through real-time, sensor-based monitoring and alerts. As hospitals across Europe begin adopting these proactive fall-prevention technologies, evidence on their routine implementation and impact remains limited. The Safe AI assisted Fall Prevention through Evidence (SAFE) project aims to address this gap by examining the large-scale introduction of an AI-assisted fall prevention system in hospitals within the Västra Götaland Region (VGR), Sweden. Conducted between 2026 and 2028, the multicentre, multimethod project involves collaboration between Halmstad University and VGR hospitals, encompassing up to 2,400 patient beds. Using a multi-method design including surveys, interviews, observations, and a retrospective study, the project will follow the implementation process and evaluate effects on patient safety, healthcare workflows, and resource use multiple sites. Additionally, two learning labs will engage patients, relatives, and healthcare professionals to co-develop strategies that support sustainable system integration. The project will generate evidence-based insights and practical guidance for implementing AI-assisted fall prevention, with relevance for healthcare professionals, patients, hospital managers, and policymakers. While centred on VGR, the findings will offer valuable lessons for future initiatives in Sweden and internationally, contributing to the broader evidence base needed for responsible and scalable use of AI in healthcare fall prevention.

Eligibility

Individual interviews with key actors in the implementation

Inclusion criteria:

  1. Be employed at one of the participating hospitals
  2. Hold a role as a key stakeholder in the implementation work
  3. Have experience with the implementation of the AI-assisted fall prevention
  4. Have the ability to understand and communicate in Swedish

Exclusion criteria:

1\. Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study

Individual interviews with managers

Inclusion criteria:

  1. Be employed as a manager at one of the participating hospitals
  2. Have experience with the implementation or use of the AI-assisted fall prevention
  3. Have the ability to understand and communicate in Swedish

Exclusion criteria:

1\. Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study

Individual interviews with staff

Inclusion criteria:

  1. Be employed as staff on a ward at one of the participating hospitals where the AI-assisted fall prevention has been decided to be implemented
  2. Have experience with the implementation or use of the AI-assisted fall prevention
  3. Have the ability to understand and communicate in Swedish

Exclusion criteria:

1\. Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study

Observations of staff work

Inclusion criteria:

  1. Be employed as staff on a ward at one of the participating hospitals where the AI-assisted fall prevention has been decided to be implemented
  2. Have experience with the implementation or use of the AI-assisted fall prevention
  3. Have the ability to understand and communicate in Swedish

Exclusion criteria:

1\. Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study

Individual interviews with patients and family members:

Inclusion criteria (for family members, only inclusion criterion 1b applies):

  1. Either (a) have been a patient on a ward at one of the participating hospitals where the AI-assisted fall prevention has been implemented, or (b) be a family member involved in the care of a patient who meets the inclusion criteria but lacks the ability to provide informed consent. The family member must be able to understand and communicate in Swedish
  2. Have experience with the AI-assisted fall prevention as part of their care
  3. Have the ability to understand and communicate in Swedish
  4. Be 18 years of age or older
  5. Have the ability to provide informed consent. If there is any uncertainty regarding a patient's ability to provide informed consent, the research team will refrain from conducting the interview.

Exclusion criteria:

  1. Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study
  2. Lack the ability to provide informed consent

Web-based surveys with staff:

Inclusion criteria:

  1. Be employed as staff on a ward at one of the participating hospitals where the AI-assisted fall prevention is decided to be implemented.

Exclusion criteria:

  1. Not being employed on a ward at one of the participating hospitals where the AI-assisted fall prevention is decided to be implemented
  2. Lack the ability to access information and respond to the survey in Swedish

Retrospective medical record data:

Inclusion criteria:

1\. Patients who have been cared for on a ward at one of the participating hospitals where the AI-assisted fall prevention has been implemented, either (a) up to 24 months after implementation or (b) up to 12 months before implementation.

Exclusion criteria:

1\. Patients who have only received care outside the defined time period, meaning not within 24 months after or 12 months before the implementation of the AI-assisted fall prevention

Learning labs:

Inclusion criteria:

  1. (a) Be employed at one of the participating hospitals and hold a role as a key stakeholder in the implementation work, or be staff or a manager with experience of the implementation or use of the AI-assisted fall prevention; or (b1) have been a patient cared for on a ward at one of the participating hospitals where the AI-assisted fall prevention has been implemented and have experience with the AI-assisted fall prevention as part of their care; or (b2) be a family member of a patient with such experience; or (c) be a patient representative for a patient group, patient organization, or user organization where falls are an identified issue
  2. Have the ability to understand and communicate in Swedish

Exclusion criteria:

  1. Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study
  2. Lack the ability to provide informed consent

Study details
    Fall

NCT07503665

Halmstad University

13 May 2026

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