CASE STUDY VIGNETTE
When one of the nation’s largest integrated health systems needed a better way to close the loop on radiology follow-up, it turned to Inflo. The result was a scalable model for turning diagnostic recommendations into completed care across a complex enterprise.
The Challenge: Recommendations Are Documented, but Care Still Breaks Down
Every day, radiologists identify findings that require action: a suspicious nodule, a repeat scan in six months, a finding that warrants specialist review, or a recommendation for additional diagnostic workup.
The challenge begins after that recommendation appears in the report.
Across large health systems, follow-up often breaks down between documentation and action. Patients move across care settings. Providers manage crowded inboxes and competing priorities. Recommended next steps may involve additional imaging, specialist referral, outreach, scheduling, or coordination across parts of the system that do not operate as a single workflow. For organizations managing this work at scale, follow-up becomes an enterprise operational problem rather than a simple messaging problem.
This health system, which manages more than 1.8 million annual imaging encounters across more than 100 care facilities, needed infrastructure purpose-built to help patients and providers navigate toward follow-up care across that complexity.
The Solution: Purpose-Built Follow-Up Care Orchestration
Inflo is an AI-powered diagnostic follow-up platform built to identify, prioritize, and operationalize follow-up recommendations across radiology and other diagnostic workflows.
For this health system, Inflo delivered:
- $6.8 million in attributed revenue from closed follow-up loops across CT, MR, and additional modalities
- 25x return on investment
- 129,743 recommendations surfaced, triaged, and tracked across inpatient, outpatient, and emergency department settings
- 10x growth in tracked volume over the course of 2025 as the program expanded across new sites and modalities
These outcomes reflect more than recommendation capture. They reflect a workflow designed to keep patients moving toward completed care.
What We Learned Working Inside the EHR Ecosystem
Inflo’s original work in diagnostic follow-up exposed a persistent structural failure in healthcare: critical clinical information is documented, but too often never translated into completed care.
Three realities shape that gap.
First, provider attention is already saturated. Any model that depends primarily on the physician inbox is operating in a channel that is already overloaded. Clinicians spend substantial time managing EHR and desk work, and the inbox burden has only intensified in recent years. As a result, follow-up workflows that rely too heavily on provider message volume face natural limits.
Second, patient portals solve access to information more effectively than they solve understanding or navigation. Patients may receive a result or notification, but that does not guarantee clarity about what it means, what the next step is, or how urgently they should act.
Third, health systems are deeply invested in their EHR infrastructure. That creates strong incentives to extend the record system as far as possible, even when the workflow problem extends beyond the practical boundaries of the record itself.
These realities do not reduce the importance of the EHR. They clarify where specialized infrastructure is needed. Health systems need a layer that works with the EHR while helping care move forward across the complexity that the record alone cannot fully manage.
How Inflo Works with Epic
Epic plays an essential role in modern health system operations, and its AI capabilities continue to expand. That matters, and it reflects an important market shift.
Inflo’s value comes from the fact that follow-up management requires more than identifying a recommendation inside the chart. It requires a purpose-built operational layer that understands radiology and diagnostic follow-up, supports prioritization over time, drives workflow, nudges both patients and providers effectively, and helps health systems manage follow-up across organizational and technical boundaries.
In this health system, Inflo’s Epic integration was central to scaling that workflow. Inflo delivered structured In Basket messages directly to ordering providers at key intervals before follow-up due dates, allowing providers to review and act within their existing workflow. This replaced a labor-intensive phone-based process with a more scalable and measurable digital model.
At the same time, Inflo’s role extends beyond the inbox. Follow-up care frequently crosses sites, settings, specialties, and systems of engagement. Patients move in and out of the health system. Records may be incomplete across environments. Responsibility may shift over time. Inflo is purpose-built to keep the patient moving toward follow-up care even when the pathway becomes fragmented.
Why This Matters
The market is moving from identifying recommendations to executing follow-ups.
Health systems increasingly have tools that can surface findings or document next steps. The harder challenge is guiding those next steps to completion in the real-world healthcare landscape, where provider attention is constrained, patient comprehension varies, and the path to care rarely remains confined to a single record system.
That is the work Inflo was built to do.
Inflo helps health systems identify radiology and diagnostic follow-up recommendations with precision, prioritize them based on urgency and context, orchestrate the outreach and workflows required to advance care, and measure what was completed and the value created.
What Makes Inflo Different
Inflo brings together the capabilities health systems need to close the follow-up gap at enterprise scale:
- AI-powered extraction of radiology and diagnostic follow-up recommendations
- Purpose-built workflow orchestration for follow-up management
- Provider engagement embedded into existing clinical workflow
- Patient nudging designed to improve follow-through
- Automation that works across EHR and non-EHR boundaries
- Measurable tracking of follow-up completion and attributed revenue
This combination allows health systems to move from visibility to execution and from recommendation to completed care.
The Outcome
For this large integrated health system, Inflo helped redefine what radiology follow-up can look like across the enterprise:
- 25x ROI
- $6.8 million in attributed revenue
- 129,743 recommendations managed through a purpose-built follow-up workflow
- A scalable model for guiding patients and providers toward completed care
Inflo helped this organization build the operational infrastructure to close follow-up gaps across the complexity of modern healthcare.
