FallSAFENCT07503665
AI-assisted Fall Prevention Through Evidence
An observational study of Fall, run by Halmstad University at 1 site in Sweden.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Fall
- What is being tested?
- Not applicable- observational study
- How many people
- 23,425 participants
- Where
- 1 siteSweden
- Study dates
- 1 Jan 2026to Dec 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Key actors in the implementation, managers, staff, patients and patient representatives
Who may be able to join
- 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
- Have experience with the implementation or use of the AI-assisted fall prevention
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- Have the ability to understand and communicate in Swedish
- 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
- Have experience with the implementation or use of the AI-assisted fall prevention
- Have the ability to understand and communicate in Swedish
- 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
- Have experience with the implementation or use of the AI-assisted fall prevention
- Have the ability to understand and communicate in Swedish
- Be employed as staff on a ward at one of the participating hospitals where the AI-assisted fall prevention is decided to be implemented.
- 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.
- (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
- Have the ability to understand and communicate in Swedish
Who cannot join
- 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
- 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
- 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
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- 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):
- 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
- Have experience with the AI-assisted fall prevention as part of their care
- Have the ability to understand and communicate in Swedish
- Be 18 years of age or older
- 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.
- Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study
- Lack the ability to provide informed consent
- Web-based surveys with staff:
- Not being employed on a ward at one of the participating hospitals where the AI-assisted fall prevention is decided to be implemented
- Lack the ability to access information and respond to the survey in Swedish
- Retrospective medical record data:
- 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:
- Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study
- Lack the ability to provide informed consent
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Sweden1 site, 1 recruiting
- Recruiting
Sahlgrenska Hospital
Gothenburg
Project leader, +46706924613, elin.siira@hh.se
About this study
Official title: Safe AI-assisted Fall Prevention Through Evidence
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.
Read the detailed 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.
- Conditions
- Fall
- Being tested
- Not applicable- observational study
- Keywords
- fall prevention, artificial intelligence, hospital, work, patient safety, resource use, implementation, effects
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Not applicable- observational studyOther
Not applicable- observational study
What is being measured
The primary outcome is the main question the study is designed to answer.
Fall rate
Measured: From earliest January 2025 to latest December 2028
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Mar 2026
- Study start1 Jan 2026
- Primary completionDec 2028 (estimated)
- Study completionDec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for FallStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 23,425 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Halmstad University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Elin Siira, Halmstad University
- Investigators
- Elin Siira, PhD, Principal investigator, Halmstad University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07503665
- Sponsor's protocol ID
- 2025-03701-01
- Other IDs
- 2025
- Acronym
- SAFE
- Status last verified
- Mar 2026
- First submitted
- 13 Mar 2026
- Last updated
- 31 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Siira E, Gyberg A, Larsson I, Rosenburg M, Svedberg P, Ulin K, Wijk H, Brezicka T, Hansson M, Hallgren J, Nygren J. Investigating the Implementation and Impact of AI-Assisted Fall Prevention in Hospitals: Protocol for a Multicenter, Multimethod Observational Study in Sweden (SAFE). JMIR Res Protoc. 2026 May 4;15:e84294. doi: 10.2196/84294.
PubMed 42081738
Study at a glance
From the registry record, last updated by the sponsor on 31 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Safe AI-assisted Fall Prevention Through Evidence
- ClinicalTrials.gov ID
- NCT07503665
- Acronym / sponsor ID
- SAFE / 2025-03701-01
- Conditions
- Fall
- Keywords
- fall prevention, artificial intelligence, hospital, work, patient safety, resource use, implementation, effects
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 23,425 participants (estimated)
- Lead sponsor
- Halmstad UniversityUniversity, hospital or other
- Study start
- 1 Jan 2026 (actual)
- Primary completion
- Dec 2028 (estimated)
- Study completion
- Dec 2028 (estimated)
- First posted
- 31 Mar 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Observational model
- Other
- Time perspective
- Other
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Key actors in the implementation, managers, staff, patients and patient representatives
Key inclusion criteria (17 listed)
- 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
Key exclusion criteria (24 listed)
- 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
- 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
- 1. Have insufficient proficiency in Swedish to participate in an interview or observation and to understand the purpose and content of the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Not applicable- observational studyNot applicable- observational study | Other | – |
Primary outcome
Fall rate
Time frame: From earliest January 2025 to latest December 2028
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 Mar 2026.
- Derived from this study: PubMed 42081738Siira E, Gyberg A, Larsson I, Rosenburg M, Svedberg P, Ulin K, Wijk H, Brezicka T, Hansson M, Hallgren J, Nygren J. Investigating the Implementation and Impact of AI-Assisted Fall Prevention in Hospitals: Protocol for a Multicenter, Multimethod Observational Study in Sweden (SAFE). JMIR Res Protoc. 2026 May 4;15:e84294. doi: 10.2196/84294.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Elin Siira, PhD principal investigator
Halmstad University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Fall, run by Halmstad University at 1 site in Sweden.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 17 inclusion and 24 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 31 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Sweden. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Project leader (+46706924613, elin.siira@hh.se), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Fall rate (time frame: From earliest January 2025 to latest December 2028). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07503665, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 31 Mar 2026.