See what our clients say about working with Bonami Software across 200+ projects for 18+ industries. EXPLORE NOW!
We don't just build software. We deliver results. EXPLORE NOW!
See why businesses choose Bonami Software for reliable, scalable solutions. EXPLORE NOW!
We turn ideas into scalable products with proven delivery across 18+ industries. EXPLORE NOW!
See what our clients say about working with Bonami Software across 200+ projects for 18+ industries. EXPLORE NOW!
We don't just build software. We deliver results. EXPLORE NOW!
See why businesses choose Bonami Software for reliable, scalable solutions. EXPLORE NOW!
We turn ideas into scalable products with proven delivery across 18+ industries. EXPLORE NOW!

AI Diagnostic Tool: 3-Hospital Rollout for Chest X-Ray AI

How a regional hospital network deployed an FDA-cleared chest X-ray AI across three facilities in production — what the clinical workflow integration required, and what radiologists and clinicians actually experienced.

Get Started

About the Project

Running an FDA-cleared AI diagnostic in production is nothing like a vendor demo: results must reach the radiologist for every eligible study and hold up across thousands a month. This case study covers the deployment across three hospitals — integration architecture, clinical change management, and six-month outcomes.

Industry

Healthcare / Radiology

Hospital radiology departments reading ~85,000 chest X-ray studies a year.

  • Radiology
  • Diagnostic Imaging
  • Clinical AI
Business Type

Regional 3-Hospital Network

Three facilities carrying unfilled radiologist positions and rising workload.

  • 3 Hospitals
  • ED & Inpatient
  • Outpatient Imaging
Core Offering

FDA-Cleared Chest X-Ray AI in Production

AI output reaches the radiologist workflow on every eligible study, not a pilot subset.

  • FDA 510(k) Cleared
  • Pneumothorax Detection
  • Consolidation
  • Pulmonary Nodules
Integration Architecture

PACS to AI engine and back to the worklist

Studies auto-route at acquisition and findings return as a DICOM Structured Report.

  • DICOM Routing
  • Structured Reports
  • Acuity Worklist
  • EHR Surfacing
Clinical Governance

Monthly QA and Threshold Tuning

Dismissed findings are reviewed monthly and confidence thresholds tuned from real reads.

  • Monthly QA Review
  • Documented Dismissals
  • Threshold Tuning
Build your idea

Talk to our experts

Scope your own clinical AI deployment with our healthcare engineering team.

  • Free Consultation

The Clinical Problem

A high-volume network needed faster, safer chest X-ray reads.

85,000
The network processed ~85,000 chest X-ray studies annually, with unfilled radiologist positions creating workload pressure. Time from acquisition to report was 4.2 hours for routine studies and 47 minutes for flagged urgent ones.
Throughput
Leadership wanted to improve routine throughput, reliably surface critical findings such as pneumothorax, consolidation, and suspicious nodules promptly, and give radiologists a quality-check tool for high-volume reads.
510(k)
The selected tool had FDA 510(k) clearance for pneumothorax, consolidation, pleural effusion, pulmonary nodules, and other chest pathologies, with particular attention to pneumothorax and consolidation detection.

Surface critical findings faster.
Support your radiologists.
Deploy AI that clinicians trust.

Talk to Our Team

The Integration Architecture

  • DICOM Routing from PACS to AI Engine

    DICOM Routing from PACS to AI Engine

    DICOM Routing from PACS to AI Engine

    • Each PACS auto-sent chest studies to the AI endpoint at acquisition
    • Targeted PA & lateral views from ED, inpatient & outpatient settings
    • Excluded portable ICU ventilator-management views
  • AI Results Back into the Radiologist Workflow

    AI Results Back into the Radiologist Workflow

    AI Results Back into the Radiologist Workflow

    • Findings returned to PACS as a DICOM Structured Report by the image
    • High-confidence pneumothorax studies elevated to the top of the worklist
    • Acuity, not acquisition time, drove reading priority
  • EHR Result Documentation

    EHR Result Documentation

    EHR Result Documentation

    • Preliminary AI findings surfaced in clinician's EHR view before report
    • Let ED physicians & hospitalists see findings awaiting the read
    • Framed as preliminary — extra information, not a report substitute
  • Feedback Loop & Threshold Tuning

    Feedback Loop & Threshold Tuning

    Feedback Loop & Threshold Tuning

    • Consistently dismissed AI findings reviewed in monthly QA meetings
    • Judged whether dismissals reflected judgment, AI, or thresholds
    • Confidence thresholds tuned from real clinical experience
  • Governance & Clinical Oversight

    Governance & Clinical Oversight

    Governance & Clinical Oversight

    • Radiology, IT, and compliance signed off on scope before go-live
    • AI findings logged as decision support, never as the final read
    • Performance reviewed against local case mix, not vendor benchmarks

The Clinical Change Management Challenge

Hover a row to see what changed.

What Made the Deployment Clinically Valuable

Over the first 90 days, the share of radiologists who preferred the AI overlay visible from the start of the read grew as the team built confidence in the tool — the deployment design earned trust rather than demanding it.

The Results

Every number below was measured in production after launch — not projected in a pitch deck.

31 min

Urgent ED Report Time — Down from 47 minutes

78%

Radiologists Report Positive Impact — At the six-month survey

85,000

Studies Processed Annually — Across all three facilities

3

Hospitals Live in Production — Network-wide rollout

Global presence

Three offices. One team.

Hi, I'm ARIA. Ask me anything about Bonami's AI agents.