CASE STUDY VIGNETTE
49X is an enviable ROI, no matter what industry you are in.
When a large integrated health system needed to scale radiology follow-up across more than 100 care facilities without scaling staff, it partnered with Inflo. The result was one of the strongest documented ROI outcomes in health system AI deployment.
How did this health system scale radiology follow-up without adding staff?
Radiology follow-up becomes especially difficult at large integrated health systems, where recommendations are generated across inpatient, outpatient, and emergency department settings every day. The volume is high, the workflows are fragmented, and manual tracking models break down quickly.
This health system knew the problem was significant. Follow-up recommendations were embedded in radiology reports, routed to referring providers, and too often lost between handoffs. Without a systematic way to identify, prioritize, and close those loops, the organization was carrying both clinical risk and revenue leakage.
It needed infrastructure built for enterprise-scale execution, not another manual workaround.
What value did Inflo deliver?
Inflo is an AI-powered radiology follow-up platform that identifies, prioritizes, and closes open follow-up loops, turning a historically manual process into an automated, measurable workflow.
For this health system, Inflo delivered:
- $9.5 million in attributed revenue from closed follow-up loops
- 49X return on investment
- 62,812 recommendations surfaced, triaged, and tracked
- 88% attribution rate, meaning 88 cents of every dollar of follow-up revenue captured was directly attributable to Inflo
- Sustained platform growth through site activations and modality expansion during 2025
These results reflect both financial and clinical value. Tens of thousands of patients who might otherwise have been lost to follow-up received the care their radiologists recommended.
Why did Inflo matter in this environment?
Inflo is built for health systems operating at scale, especially those with large facility footprints, complex care pathways, and lean teams. This customer serves patients across inpatient, outpatient, and emergency department settings at more than 100 facilities. Its imaging program spans multiple modalities and generates follow-up recommendations at a volume no manual process could manage reliably.
That is what made this deployment notable. The organization did not need more effort layered onto an already strained process. It needed a best-of-breed platform that could support enterprise-scale follow-up without requiring enterprise-scale staffing to sustain it.
What was unique about the Ferrum Health partnership?
This deployment was implemented in partnership with Ferrum Health, whose model helps health systems identify and deploy AI solutions with measurable clinical and operational value. That partnership mattered because it accelerated selection and implementation while ensuring a strong fit with existing infrastructure. It also strengthened accountability. At this organization, the connection between platform activity and follow-up revenue was clear, documented, and auditable. That level of attribution is rare in health system AI and highly valuable for leadership teams evaluating performance and expansion.
Why does the 88% attribution rate matter?
One of the strongest proof points in this deployment is the attribution rate itself.
88% of all follow-up revenue captured at this organization is directly attributable to Inflo.
That matters because it shows three things:
- Inflo is central to the follow-up program, not peripheral to it
- Leadership can tie outcomes directly to platform performance
- The organization has a measurable foundation for continued optimization
When health system leaders ask whether a platform is driving real results, this deployment offers a clear answer.
How was Inflo different from the health system’s previous process?
Most health systems approach radiology follow-up with some combination of manual report review, spreadsheet tracking, phone outreach, or reliance on providers to manage recommendations themselves. Those approaches create activity, but they rarely create scalable performance.
Inflo gave this organization a fundamentally different operating model. The platform automatically identified recommendations, built prioritized worklists, supported multi-touch outreach, and closed the loop with financial attribution tied to completed exams and billed encounters. At this scale, that difference is not marginal. It is the difference between a follow-up program that can expand and one that stalls under its own complexity.
What makes Inflo different from other follow-up solutions?
Inflo combines the capabilities health systems need to manage radiology follow-up as an enterprise workflow:
- AI-powered recommendation extraction
- Automated provider outreach
- EHR-aligned workflow integration
- Closed-loop tracking
- Clear, accountable revenue attribution
Many follow-up solutions address only one part of the problem. Inflo connects the full chain from recommendation identification through workflow execution to measurable financial results. At this organization, the 88% attribution rate is strong evidence that the platform is not simply supporting the background process. It is driving the program’s outcomes.
The outcome
- 49X ROI
- $9.5 million in attributed revenue
- 62,812 recommendations managed
- 88% of follow-up revenue captured directly attributable to Inflo
For this large integrated health system, Inflo became the operational backbone of a high-performing radiology follow-up program, delivering financial accountability and clinical impact at a scale that manual processes could not achieve.
