When CNET profiled Inflo Health in its recent feature Closing Gaps in Health Care: How Inflo Health Is Using AI, the story didn’t just highlight a promising technology. It exposed one of the most overlooked risks in modern medicine: the gap between what radiologists see and what systems do about it.
In an era when imaging detects more than ever, the lack of follow-up coordination is more than a minor workflow problem; it can be the difference between early treatment and a preventable tragedy. As the article describes, a radiologist identified a suspicious breast lesion during a scan for abdominal pain — the kind of incidental finding that saves lives. But no one acted on it. No one followed up. Ten months later, the patient was diagnosed with metastatic cancer. She passed away a year and a half later.
That loss inspired the founding of Inflo Health. And it reflects a broader truth that our CEO, registered nurse Angela Adams, often emphasizes:
“AI is not meant to replace clinicians. It is meant to replace the broken parts of the system that humans should never have to shoulder alone.
The Root Problem: Detection Without Action
The CNET article underscores a national trend: imaging is getting better, but patient communication and care navigation are not. Researchers estimate that about 50% of radiology follow-up recommendations (excluding mammograms) never happen. The increase in incidental findings — sometimes 40% more due to more sensitive imaging — is pushing an already strained system past its breaking point.
These failures don’t result from lack of clinical expertise. They result from outdated workflows, unclear delegation, disconnected communication, and the false belief that the solution is always to add more humans to a broken process.
The Inflo Shift: “Never Miss a Follow-Up”
Inflo Health was created to ensure that radiologist recommendations never fall into that void. Our platform uses natural language processing, large language models, and workflow automation to:
✔️ Scan imaging reports (CT, MRI, ultrasound, X-ray)
✔️ Identify recommended follow-up actions
✔️ Prioritize urgent or high-risk findings
✔️ Notify and escalate tasks across patients and providers
✔️ Track outcomes transparently until completion
The result is a high-reliability workflow where automation handles 60–70% of routine follow-up scenarios end-to-end. The remainder — complex cases, oncology pathways, multiple findings — are escalated to humans, where they belong. This “human-in-the-loop” model supports clinicians instead of replacing them.
Or as Angela told CNET:
“AI isn’t replacing radiologists. It’s empowering them to deliver more reliable patient care.”
Impact That Matters
This isn’t theoretical. The data is measurable:
- East Alabama Medical Center improved its follow-up closure by 74%, according to the American College of Radiology.
- Inflo impacted 125,000+ lives in just the last year. Every improvement in follow-up adherence represents another person who doesn’t slip through the cracks.
That is the outcome of AI built to serve, not supplant, clinical teams. Angela summarized it best:
“Technology’s highest calling is to give humans back the two most important things in life that you cannot buy, which are health and time.”
A Vision for the Future
As digital imaging continues to advance, the real question isn’t how we detect more — it’s how we ensure every discovery leads to action. The future of radiology isn’t defined by scanners alone, but by what happens after the scan.
At Inflo Health, we’re building an ecosystem where every follow-up is visible, communicated, and completed. Where frontline clinicians don’t have to hope the system works — they can trust it. Where radiologists aren’t left wondering if their recommendations reach the right hands. Where patients never experience preventable delays.
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