Teleradiology Case Studies: Real Results at Real Scale
How government institutions, PPP networks, and large-volume providers solved their radiology operations with 5C Network — from 30,000 scans per month to 60,000-case backlog clearance.
In brief: Three case studies. Three operating models. 30,000 scans/month unified across 20+ PPP hospitals. 50+ medical camps/year with zero PACS infrastructure. 60,000 cases triaged by AI in weeks instead of months. One common outcome: radiology operations that scale without breaking — with 30-minute average turnaround and no additional radiologist recruitment.
Why Large-Volume Radiology Is a Different Problem
Most teleradiology providers are built for steady-state volume: a few hundred studies a day, predictable modality mix, one or two sites. Large-volume providers face a structurally different problem.
Thousands of pending cases. Multiple sites with different equipment, formats, and workflows. Government compliance requirements. Camp-based imaging with no PACS infrastructure. Variable connectivity. Modality mixes that shift from week to week. These problems do not yield to "more radiologists." They require a different operating model — one where AI, workflow automation, and a distributed radiologist pool work together as a system.
The three case studies below illustrate how that system works in practice across fundamentally different operating contexts.
Bulk Offloads
Hospitals transferring thousands of pending cases for rapid clearance.
Massive Backlogs
Weeks or months of unreported studies that need systematic clearance.
Multi-Site Coordination
PPP networks with 10-50 hospitals needing unified reporting workflows.
Government Tenders
NHM, Ayushman Bharat, and state-level programmes requiring audit-ready compliance.
3
Operating models covered
60,000+
Cases triaged in one engagement
20+
Hospitals unified in one network
50+
Medical camps scaled per year
30,000+ Scans Per Month Across 20+ Hospitals
Multi-Site PPP Network
The Challenge
A state-level Public-Private Partnership programme connected 20+ district and sub-district hospitals under one radiology contract. Each hospital had different equipment, different PACS configurations (some had none), and different referral patterns. Volume exceeded 30,000 scans per month across all sites.
The existing approach — hiring radiologists at each hospital — was failing. Smaller district hospitals could not attract qualified radiologists. Reports were delayed by 24-48 hours. There was no standardisation in report quality or format across the network, making programme-level analytics impossible.
The programme administrators needed a single reporting partner who could unify the entire network: accept studies from every site regardless of equipment or format, deliver reports within a predictable turnaround window, and provide real-time visibility into volume and quality across the programme.
The Solution
Unified Workflow
All 20+ hospitals feeding into one central reporting pipeline.
Intelligent Routing
Studies routed by modality, subspecialty, and urgency to the right radiologist.
Real-Time Visibility
Programme administrators could track TAT, volume, and quality across every site.
Quality at Scale
Standardised report templates and AI-assisted quality checks on every study.
Results
30%
Faster turnaround
18%
Lower cost per scan
Zero
Additional radiologists needed
20+
Hospitals unified
"Reports that used to take 48 hours were now completed in 12-18 hours. The programme finally had consistent, auditable radiology across every district hospital."
End-to-End Radiology for Distributed, Mobile Imaging
Medical Camp Network
The Challenge
A large-scale screening programme ran medical camps in rural and semi-urban locations. Mobile X-ray units captured images as JPEGs — not DICOM — because the portable CR equipment had no PACS integration. There was no radiologist on-site, no reliable internet at most camp locations, and no digital infrastructure to receive or store reports.
The programme needed a workflow that started with a USB drive and ended with government-compliant radiology reports accessible in real time — without requiring any infrastructure at the camp site itself.
Traditional teleradiology was not an option. There was no PACS to push studies from, no DICOM gateway, and often no stable internet connection at the point of imaging. The workflow had to be designed around these constraints, not in spite of them.
The Solution
On-site Capture
Portable CR units capture X-ray images as JPEGs at camp locations.
Drive Upload
Camp coordinator uploads images from USB drive at nearest internet-connected point.
Backend Processing
5C backend validates, de-duplicates, and queues incoming images.
JPEG-to-DICOM Conversion
Images converted to DICOM with proper metadata tagging for archive compliance.
Secure Cloud Storage
DICOM studies stored in cloud PACS, accessible without local infrastructure.
Radiologist Reporting
Studies assigned to radiologists based on modality and volume. AI triage flags abnormals.
Government Validation
Reports formatted to meet state and central government audit requirements.
Real-Time Access
Referring physicians and programme administrators access reports via web portal.
Results
Zero
Infrastructure overhead
24-48h
Report turnaround
50+
Camps/year scaled
Full
Government compliance
"Just plug in a drive and go. The camp team captures images, uploads when connectivity is available, and reports appear in the portal within a day. No PACS, no viewer, no radiologist on-site."
Clearing 60,000 Cases with Intelligent Triage
International Teleradiology Provider
The Challenge
An international teleradiology provider had accumulated a backlog of 60,000 unreported cases. Their radiologists were spending roughly 70% of their time on studies that turned out to be normal — leaving abnormal and critical cases waiting in the same queue. Adding more radiologists was not economically viable, and the backlog was growing faster than the team could clear it.
The provider needed a way to triage at scale: separate normals from abnormals, reorder the worklist by clinical priority, and let their radiologists focus on the cases that actually required expert interpretation.
The core insight was that the bottleneck was not radiologist availability — it was radiologist allocation. Most of their expert time was being spent confirming normals, while abnormals sat in the same undifferentiated queue.
The Solution
Normal/Abnormal Classification
AI screening across hundreds of pathologies classified every study before it reached a radiologist. Normals were flagged for expedited sign-off; abnormals were prioritised.
Worklist Reordering
The reporting queue was dynamically reordered so critical and abnormal cases surfaced first. Radiologists no longer had to manually search for urgent studies in a sea of normals.
Efficiency Unlock
With AI handling the initial screening pass, radiologists could sign off on pre-screened normals faster and spend their interpretation time on cases that required it. The same team produced significantly more output.
Results
6,000
Cases cleared in 48 hours
40%
Productivity increase
Faster
Critical findings caught
Lower
Cost per case
"Backlogs that would take months to clear got done in weeks. The radiologists were doing less volume-work and more actual interpretation — and output went up, not down."
What These Case Studies Have in Common
The bottleneck was never just "radiologists"
In every case, the constraint was not a shortage of radiologists per se, but a workflow problem: studies were not being routed to the right people, normals were consuming expert time, or the intake infrastructure could not handle the format and volume. Solving the workflow solved the throughput.
AI was force-multiplying, not replacing
In every deployment, AI served as a screening and routing layer. It classified normals, flagged abnormals, and reordered worklists. Radiologists still interpreted every study. The combination produced more output with fewer errors than either could achieve alone.
Time-to-value was measured in days, not months
The PPP network went live across 20+ hospitals. The medical camp workflow ran without any on-site PACS. The backlog engagement cleared 6,000 cases in 48 hours. In none of these cases was the deployment timeline measured in quarters.
Quality did not degrade at scale
Standardised templates, AI-assisted quality checks, and subspecialty-matched routing ensured that a report from the 30,000th scan met the same standard as the first. This is a structural property of the system, not a function of individual radiologist effort.
Why Large-Volume Providers Choose 5C
Across all three case studies, the same structural advantages applied.
Operational Efficiency at Scale
2-3x more scans processed with the same team. AI triage handles the screening pass; radiologists handle the interpretation. Volume increases do not require proportional headcount increases.
Financial Advantage
Cost per scan decreases with volume. No fixed radiologist salaries, no infrastructure investment, no recruitment overhead. The economics improve as you scale, not the other way around.
Clinical Consistency
Unified report templates, AI-assisted quality checks, and standardised workflows across every site in the network.
Flexibility
From camps with USB drives to multi-site DICOM integrations. The same platform adapts to the infrastructure available — fixed installations, mobile units, or a mix of both.
AI Amplifies Human Expertise
AI handles screening and triage. Radiologists handle interpretation. Neither replaces the other — together, they produce more and miss less.
Regulatory Compliance by Default
HL7, DICOM, and audit-ready reporting built into every workflow. Government and institutional compliance requirements are met structurally, not as an afterthought.
How Engagements Typically Work
From initial pilot to full-scale operations in under a month.
Pilot
Within 72 hours
- Scope the engagement and sign MOU
- Configure intake pipeline (DICOM, Drive, or JPEG batch)
- Process 500-1,000 studies to validate quality, TAT, and workflow
Scale
Within a week
- Expand to full production volume
- Onboard additional sites if multi-location
- Enable AI triage, automated routing, and real-time dashboards
Optimise
Within a month
- Measure operational metrics: TAT, cost per scan, quality scores
- Adjust routing rules, expand modalities, add new sites
- Ongoing performance reviews with the institution
Frequently Asked Questions
Explore how 5C Network can scale your radiology operations
Whether you are managing a PPP network, running medical camps, or clearing a reporting backlog, we can scope an engagement in a single conversation.
Pilot in 72 hours. Full production within a week. No long-term commitments required to start.
Contact Us
