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TRUVACE RECORD VERSION
record: TRV-2026-0855
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-23T06:03:11.867005Z
status: published
lens: p_space
sector: health
headline: Systematic assessment of the medical utility of radiology and diagnostic Artificial Intelligence in fracture detection (SAMURAI-fracture): a protocol for a multicentre cluster-randomised controlled trial
dek: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient outcomes, unnecessary treatments and significant healthcare costs. Artificial intelligence (AI)-assisted fracture detection tools are now available for use in radiology workflows; however, the impact of these technologies on patient outcomes, experiences and overall care pathways in the real-world clinical setting is limited. We will conduct a prospective cluster randomised cro…
gain_title: (none)
problem_title: Systematic assessment of the medical utility of radiology and diagnostic Artificial Intelligence in fracture detection (SAMURAI-fracture): a protocol for a multicentre cluster-randomised controlled trial: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient outcomes, unnecessary treatments and significant healthcare costs.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Systematic assessment of the medical utility of radiology and diagnostic Artificial Intelligence in fracture detection (SAMURAI-fracture): a protocol for a multicentre cluster-randomised controlled trial: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient outcomes, unnecessary treatments and significant healthcare costs.
problem_evidence: (none)
quick_read: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient outcomes, unnecessary treatments and significant healthcare costs. Artificial intelligence (AI)-assisted fracture detection tools are now available for use in radiology workflows; however, the impact of these technologies on patient outcomes, experiences and overall care pathways in the real-world clinical setting is limited.

We will conduct a prospective cluster randomised cross-over trial over a 6-month period, assessing the impact of an AI-assisted fracture detection tool in EDs and MIUs across 4 healthcare Trusts in the UK. The trial will deploy Radiobotics' RBfracture, a CE-approved AI-assisted medical device software for fracture detection at each site for 6 months.
limitation: 
tag: Evidence-backed problem
key_points: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient outcomes, unnecessary treatments and significant healthcare costs. | Artificial intelligence (AI)-assisted fracture detection tools are now available for use in radiology workflows; however, the impact of these technologies on patient outcomes, experiences and overall care pathways in the real-world clinical setting is limited. | We will conduct a prospective cluster randomised cross-over trial over a 6-month period, assessing the impact of an AI-assisted fracture detection tool in EDs and MIUs across 4 healthcare Trusts in the UK.
rundown: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient outcomes, unnecessary treatments and significant healthcare costs. Artificial intelligence (AI)-assisted fracture detection tools are now available for use in radiology workflows; however, the impact of these technologies on patient outcomes, experiences and overall care pathways in the real-world clinical setting is limited.

We will conduct a prospective cluster randomised cross-over trial over a 6-month period, assessing the impact of an AI-assisted fracture detection tool in EDs and MIUs across 4 healthcare Trusts in the UK. Patients aged over 2 years old undergoing a plain film radiography for a suspected fracture as part of routine clinical care will be eligible for study enrolment.
sources:
- peer_reviewed | BMJ Open | https://doi.org/10.1136/bmjopen-2026-120631 | 2026-08-21
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