BoneView helps Poitiers emergency doctors read fracture X-rays

At Poitiers University Hospital's emergency department, the X-ray discrepancy rate fell by 17% and mean stay by 9 minutes after Gleamer BoneView arrived (3,720 patients).

21
Benefit status
Reported
Evidence
Claimed by the parties
Observed
Sources
1 publication
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Benefits

Benefit

The rate of discrepancies between emergency physicians' and radiologists' readings fell by 17%

Awaiting review

Outcome identifiers

Unresolved

Not reviewedUnresolved

Category

Improved Task Accuracy

Awaiting review

Status

Reported benefit

Awaiting review

Beneficiary groups

Organizations. People.

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

BoneView

Awaiting review

Model

This is an explicit unresolved assignment: the sources on record do not settle this question.

Not reviewedUnresolved

Reported configuration

V1

Awaiting review

Provider

Unresolved

Not reviewedUnresolved

Role

Unresolved

Not reviewedUnresolved

Configuration

Unresolved

Not reviewedUnresolved

Inputs and outputs

Unresolved

Not reviewedUnresolved

Autonomy

Unresolved

Not reviewedUnresolved

Workflow

Emergency physicians had the AI marks on limb radiographs at the point of care. Radiologists read every study as the reference.

Awaiting review

Human oversight

Unresolved

Not reviewedUnresolved

Relation to AI

The study compares two periods a year apart, with no concurrent control, so other changes between 2020 and 2021 may explain part of the difference.

Awaiting review

AI contribution

Unresolved

Not reviewedUnresolved

Measurement

Studies

Before/after. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Study design

Before/after. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Measurement

Retrospective comparison of emergency physician and radiologist readings, length of stay and consultations from records. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Setting and sample

3,720 adult trauma patients with limb radiographs (1,780 in 2020, 1,940 in 2021) at one level I trauma center. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Measures

Discrepancy rate; length of stay. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Comparison

Same six months of the previous year. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Results

Discrepancy rate down 17%; mean stay down 9 minutes. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Additional value from AI

17% relative fall in discrepancies. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Limitations

Retrospective, single center, no concurrent control; clinically relevant discrepancies did not change significantly. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Denominators

All eligible patients in the 2021 period. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Materials for replication

Not stated. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

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. Operator: Poitiers University Hospital (CHU de Poitiers).

Awaiting review

Jurisdictions

Benefit: Emergency department, Poitiers University Hospital, Poitiers, France. Developer: France. Operator: France.

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 must check the AI marks before discharge decisions. The tool must keep its accuracy on the local case mix.

Awaiting review

Replication attempts

Unresolved

Not reviewedUnresolved

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-0638-source-0001

Awaiting review

Citations

Numbered references below.

Awaiting review

Language

Unresolved

Not reviewedUnresolved

Source relationships

Operator

Awaiting review

Original evidence

Unresolved

Not reviewedUnresolved

Access and versions

Unresolved

Not reviewedUnresolved

Supported findings

Unresolved

Not reviewedUnresolved

Evidence strength

The deployer's account. Sources: the deployer's peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Missing evidence

Unresolved

Not reviewedUnresolved

Grades

Assessed benefits

Organizations. People.

Awaiting review

Depth

Organizations: 2. People: 1.

Awaiting review

Reasons

Organizations: The discrepancy rate between emergency and radiology readings fell by 17% after the tool began. People: Mean length of stay in the emergency department fell by 9 minutes.

Awaiting review

Observed or intended

Unresolved

Not reviewedUnresolved

Rubric

Unresolved

Not reviewedUnresolved

Assessor and date

Unresolved

Not reviewedUnresolved

Alternative assessments

Unresolved

Not reviewedUnresolved

Fill

The deployer's account

Awaiting review

Entry details

Kind

The case describes a deployment. A hospital deployment evaluated before and after. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Field

Healthcare.

Awaiting review

Purpose

BoneView was built to help clinicians detect fractures on radiographs. Fewer reading discrepancies were that purpose; the shorter stay was a related workflow gain.

Awaiting review

Dates

Observed: 1 January 2021. Updated: 29 October 2026.

Awaiting review

Stage

The system was in routine use. The commercial tool was available to emergency clinicians in daily work. [1]

Fully reviewed

Review date: 29 October 2026.

Sources: [1]

Version

SHA-256: b847fecfd455…

Awaiting review

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

  1. Peer-reviewed study Deployer

    Herpe G, Nelken H, Vendeuvre T, et al. Effectiveness of an Artificial Intelligence Software for Limb Radiographic Fracture Recognition in an Emergency Department. J Clin Med. 2024;13(18):5575.

Cite this case

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Version b847fecfd455, archived in the edition of 29 October 2026

Benefit marks

Depth

The number and color show the depth of a benefit.

  1. A convenience, or time or money saved.
  2. A measurable improvement in a result or ability.
  3. A lasting change, an ability restored, or a risk removed.
  4. A serious harm averted or a serious condition resolved in time.
  5. A life or livelihood preserved, or a change documented across a population.

Beneficiary

  • Circle: a person
  • Square: an organization
  • Triangle: society

Evidence

  • Solid. A court or regulator found a benefit, or researchers independently studied it.

  • Hatched. Independent reporting.

  • Outline. Claimed by the parties. Only the people or organizations involved, or sources whose independence has not been assessed, support the benefit.

The fill changes with the evidence. The depth color stays the same.

How benefits are assessed