Benefits
- Benefit
-
From 61% to 74%
Awaiting review
- Outcome identifiers
-
Unresolved
Not reviewedUnresolved
- Category
-
Improved Task Accuracy
Awaiting review
- Status
-
Reported benefit
Awaiting review
- Beneficiary groups
-
Organizations.
Awaiting review
- Beneficiaries
-
Unresolved
Not reviewedUnresolved
- Reach
-
Unresolved
Not reviewedUnresolved
- Distribution and access
-
Unresolved
Not reviewedUnresolved
- Duration
-
Unresolved
Not reviewedUnresolved
- Expected?
-
Yes
Awaiting review
- Costs and harms
-
Unresolved
Not reviewedUnresolved
AI system
- System
-
AI fracture detection software: BoneView, RBfracture, Rayvolve and TechCare Alert
Awaiting review
- Model
-
This is an explicit unresolved assignment: the sources on record do not settle this question.
Not reviewedUnresolved
- Release
-
Unresolved
Not reviewedUnresolved
- Provider
-
Unresolved
Not reviewedUnresolved
- Role
-
Unresolved
Not reviewedUnresolved
- Configuration
-
Unresolved
Not reviewedUnresolved
- Inputs and outputs
-
Unresolved
Not reviewedUnresolved
- Autonomy
-
Unresolved
Not reviewedUnresolved
- Workflow
-
The software marked suspected fractures on the X-ray for the reader. A trained clinician made the final interpretation.
Awaiting review
- Human oversight
-
Unresolved
Not reviewedUnresolved
- Relation to AI
-
The reader studies compared the same clinicians reading X-rays with and without the software.
Awaiting review
- AI contribution
-
The reader studies compared the same clinicians reading X-rays with and without the software.
Awaiting review
Measurement
- Studies
-
Controlled observational. [2]
Fully reviewed: supporting details for Studies
Review date: 29 October 2026.
Sources: [2]
- Study design
-
Controlled observational. [2]
Fully reviewed: supporting details for Study design
Review date: 29 October 2026.
Sources: [2]
- Measurement
-
Sensitivity and specificity of clinicians reading with and without the software against a reference standard. [2]
Fully reviewed: supporting details for Measurement
Review date: 29 October 2026.
Sources: [2]
- Setting and sample
-
16 studies, mostly on BoneView (8) and RBfracture (5). [2]
Fully reviewed: supporting details for Setting and sample
Review date: 29 October 2026.
Sources: [2]
- Measures
-
Sensitivity and specificity for fractures. [2]
Fully reviewed: supporting details for Measures
Review date: 29 October 2026.
Sources: [2]
- Comparison
-
Unassisted reading by the same clinicians. [2]
Fully reviewed: supporting details for Comparison
Review date: 29 October 2026.
Sources: [2]
- Results
-
Sensitivity 61% to 74% (BoneView), 74% to 83% (RBfracture), 79% to 94% (Rayvolve); no loss of specificity. [2]
Fully reviewed: supporting details for Results
Review date: 29 October 2026.
Sources: [2]
- Additional value from AI
-
Higher sensitivity by 9 to 15 percentage points. [2]
Fully reviewed: supporting details for Additional value from AI
Review date: 29 October 2026.
Sources: [2]
- Limitations
-
Mostly retrospective case-control designs; no UK urgent care studies; readers saw X-rays without patient history. Unassisted readers were less accurate than expected. [2]
Fully reviewed: supporting details for Limitations
Review date: 29 October 2026.
Sources: [2]
Money
- Kind of value
-
The kind of monetary value is unclear.
Not reviewedUnresolved
- Amount
-
The monetary value is not established.
Not reviewedUnresolved
- Currency and prices
-
The currency and price basis are unclear.
Not reviewedUnresolved
- Period and unit
-
The period and unit of the monetary estimate are unclear.
Not reviewedUnresolved
- Realization
-
Whether the monetary value was realized is unclear.
Not reviewedUnresolved
- Recipients and payers
-
The recipients and payers are unclear.
Not reviewedUnresolved
- Gross or net
-
Whether the monetary figure includes costs is unclear.
Not reviewedUnresolved
- Included costs
-
The costs included in the estimate are unclear.
Not reviewedUnresolved
- Comparison
-
The financial comparison is not established.
Not reviewedUnresolved
- Method
-
The method used to calculate monetary value is unclear.
Not reviewedUnresolved
- Return and payback
-
The return on investment or payback period is not established.
Not reviewedUnresolved
People and places
- Participants
-
Developer: Gleamer (BoneView), Radiobotics (RBfracture), AZmed (Rayvolve) and Milvue (TechCare Alert). Operator: Hospitals in the reader studies reviewed by NICE; NHS urgent care services in England during the evidence generation period.
Awaiting review
- Jurisdictions
-
Benefit: Multiple countries (studies); England,
United Kingdom (guidance). Developer: Multiple: 
France, 
Denmark. Operator: Multiple.Awaiting review
- Ownership and control
-
Unresolved
Not reviewedUnresolved
- Dependencies
-
Unresolved
Not reviewedUnresolved
- Cross-border connections
-
Unresolved
Not reviewedUnresolved
- Geopolitical implications
-
The geopolitical implications are unclear.
Not reviewedUnresolved
Follow-up
- Conditions for replication
-
Clinicians in urgent care read with the software as they did in the studies. The software performs on local X-ray equipment as it did in testing.
Awaiting review
- Replication attempts
-
1 follow-up entry. Benefit recurred: 1.
Awaiting review
- Later findings
-
Unresolved
Not reviewedUnresolved
- Availability
-
Unresolved
Not reviewedUnresolved
- Institutional decision
-
A relevant institutional decision has not been established.
Not reviewedUnresolved
- Grounds
-
The grounds for an institutional decision are unclear.
Not reviewedUnresolved
- Action and result
-
The result of an institutional decision is not established.
Not reviewedUnresolved
- Success criterion
-
The criterion for a successful institutional decision is unclear.
Not reviewedUnresolved
Evidence
- Source numbers
-
AIBD-0655-source-0001–0003
Awaiting review
- Citations
-
Numbered references below.
Awaiting review
- Language
-
Unresolved
Not reviewedUnresolved
- Source relationships
-
Independent, Developer
Awaiting review
- Original evidence
-
Unresolved
Not reviewedUnresolved
- Access and versions
-
Unresolved
Not reviewedUnresolved
- Supported findings
-
Unresolved
Not reviewedUnresolved
- Evidence links
-
Unresolved
Not reviewedUnresolved
- Evidence strength
-
Found by a regulator. Sources: two independent regulatory documents and the makers' peer-reviewed study. The cited evidence includes no independent study or report. [1] [2] [3]
- Missing evidence
-
Unresolved
Not reviewedUnresolved
Grades
- Assessed benefits
-
Organizations.
Awaiting review
- Depth
-
Organizations: 2.
Awaiting review
- Reasons
-
Organizations: Clinicians' sensitivity for fractures rose from 61% to 74% with BoneView, from 74% to 83% with RBfracture and from 79% to 94% with Rayvolve, without lower specificity.
Awaiting review
- Observed or intended
-
Unresolved
Not reviewedUnresolved
- Rubric
-
Unresolved
Not reviewedUnresolved
- Assessor and date
-
Unresolved
Not reviewedUnresolved
- Alternative assessments
-
Unresolved
Not reviewedUnresolved
- Fill
-
Found by a regulator
Awaiting review
Entry details
- Kind
-
The case describes an evaluation or a study. A health technology assessment of reader studies. [2]
Fully reviewed: supporting details for Kind
Review date: 29 October 2026.
Sources: [2]
- Related entries
-
No incident in the AI Incident Database snapshot of 26 October 2026 concerns the same kind of system harming the same kind of stakeholder.
Partly reviewedUnresolved: supporting details for Related entries
Compared with the incidents in the AI Incident Database snapshot of 26 October 2026.
- Field
-
Healthcare.
Awaiting review
- Purpose
-
The systems were built to help clinicians detect fractures on X-rays. Higher detection is that purpose.
Awaiting review
- Dates
-
Source published: 14 January 2025. Updated: 29 October 2026.
Awaiting review
- Stage
-
The system was tested in a laboratory. Most evidence came from retrospective reader studies on archived X-rays. [2]
Fully reviewed: supporting details for Stage
Review date: 29 October 2026.
Sources: [2]
- Version
-
SHA-256: 9b5065c33b38…
Awaiting review: supporting details for Version
SHA-256 of the public case, its assessments, and its displayed answers and notes, excluding its own identifier and the derived coverage summary.
References
- Other identifiers
-
Unresolved
Not reviewedUnresolved
- Category mappings
-
Unresolved
Not reviewedUnresolved
- Citable summary
-
Unresolved
Not reviewedUnresolved
- Revisions
-
1 revision. Latest: 29 October 2026.
Awaiting review
Sources
-
Peer-reviewed study Developer
Duron L, Ducarouge A, Gillibert A, et al. Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study. Radiology. 2021;300(1):120-129.
The AI aid improved the sensitivity of physicians by 8.7% (95% CI: 3.1, 14.2; P = .003 for superiority)
-
Regulatory document Independent author
Diagnostic accuracy studies typically found improved sensitivity of fracture detection, without reduced specificity, by healthcare professionals assisted by AI software compared with unassisted interpretation.
-
Regulatory document Independent author
Four artificial intelligence (AI) technologies can be used in the NHS during the evidence generation period as options to help healthcare professionals detect fractures on X-rays in urgent care.