VitalCare Diagnostics lifted radiologist throughput 32% with an AI clinical decision-support platform
A diagnostic imaging network was losing radiologists to burnout and turning away referrals it couldn't read in time. An AI knowledge platform that surfaces and prioritizes findings cut turnaround time and unlocked $2.1M in new referral capacity.
This is an illustrative case study. Company names, identifying details, and testimonials have been changed to protect client confidentiality. The technical solution and target outcomes are representative of the work we do. We extend the same confidentiality to every client.
Where they started
VitalCare's 9 imaging centers were running 24/7 but radiologists couldn't keep up. Average turnaround time for non-urgent studies hit 11 hours, referring physicians were pulling contracts, and two senior radiologists quit citing burnout. An estimated 6% of critical findings were going unread for over 24 hours — a patient-safety and liability risk the board could no longer ignore.
What we built
We built a clinical decision-support platform on our Cortex knowledge engine that ingests imaging study metadata, runs AI triage to flag and rank likely critical findings, and queues them to the right radiologist with citation-backed context. Worklists now self-prioritize, and the AI surfaces prior reports and relevant history so reads start faster.
Target outcomes
More from this project
We were about to lose two more hospital contracts over turnaround time. The AI triage didn't replace our radiologists — it made them faster and made sure nothing critical sat unread. We took on $2.1M in new referrals without hiring.
Representative testimonial — name and role changed to protect client identity.