More Scans and Yet Less Cash

Here’s How Radiology Leaders Are Fixing the AR Gap

Radiology is doing more work than ever, and yet collecting less of it. Despite high volumes, many radiology groups and independent imaging practices are facing slowing cash flow, mounting margin pressure, and piling accounts receivable (AR) volume.

The underlying problem: revenue leakage that’s systemic, largely invisible until it’s too late, and increasingly expensive to operate within traditional, manual AR workflows.

The Revenue Leakage No One Sees Until It Hits the Bottom Line

1 in every 7 medical claims (~15%) is denied on first submission, with imaging especially vulnerable due to prior authorization and documentation gaps.
Radiology RCM teams spend nearly 40% of their time on manual follow-ups, rework, and status checks, driving up the cost to collect.
Underpayments and short-pays (over $130 billion annually) account for more lost revenue than denied dollars and remain buried in 835 remittance files.

For radiology CFOs and RCM directors, these trends indicate a stark paradox:

declining net revenue despite growing imaging volume.

And the impact compounds through:

Denied claims that require time consuming rework

Silent underpayments that go undetected

AR that keeps aging without a clear, ROI-driven recovery strategy

A Self-Check Every Radiology Leader Should Perform

If your AR strategy relies heavily on manual reviews and aging-based worklists, you need to ask yourself:

These questions expose where traditional AR management fail modern radiology revenue cycle workflows.

The Hidden Cost of Traditional AR Workflows

Due to a lack of data-driven, AI-led insight, traditional, manual AR management often fails because work is often prioritized the wrong way:

Low-likelihood claims getting worked before underpayments worth 10x more

Staff spending hours reviewing correctly paid claims, losing true revenue opportunities

High-value leakage getting undetected because it requires line-level reconciliation

Such processes don’t just increase administrative costs; they directly compromise the net revenue potential.

Why Radiology AR Is Uniquely Vulnerable and Challenging at the Same Time

Radiology is riddled with operational complexities that magnify revenue risk:

Many teams respond to these by hiring more AR staff and working older buckets. Yet they lose millions in revenue because they lack the visibility to work the right claims the right way.

The Industry Shift: From Reactive Labor-Led to Proactive Intelligence-Led AR

Leading radiology organizations are rethinking AR as a juncture that can maximize cash flow and minimize cost to collect if worked smartly with AI-led analytics and action.

And the shift is clear:

At the center of this shift is revenue intelligence that understands payer behavior and radiology nuances to work recoverable claims at scale.

How Jindal Healthcare Enables Smarter Radiology AR Management

Jindal Healthcare’s AI for RCM is designed specifically for high-volume, high-complexity environments like radiology, where traditional workflows often break down.

And here’s how our RCM engine optimizes AR workflows for improved bottom line:

Automated Underpayment Detection

Line-level reconciliation of remittances (835) against submitted claims (837)
Automated detection and flagging of underpayments and incorrect payer adjustments
Pattern analysis by payer, CPT, modality, and site of service to surface systemic issues

Faster Denial Resolution with HITL

Automated appeal generation with required clinical and authorization documentation
Smart routing to subject-matter experts, so humans only intervene when their judgment is required in nuanced contexts

Smart Claim Prioritization by ROI

AI-led claim prioritization based on recoverable value, success likelihood, and ROI
Priority queueing of high-dollar, high-opportunity cases
Automated claim status checks and payer follow-ups

Proactive Denial Prevention

Continuous analysis of denial reasons by payer, CPT, modality, site of service, and ordering pattern
Insights fed back into front-end and mid-cycle workflows, enabling a continuous learning loop

How Radiology Leaders Are Witnessing AR Transformation

Organizations adopting our revenue cycle management (RCM) solution are reporting:

35%

increase in recoverable revenue from denials and underpayments

50%

reduction in RCM operating cost through automation and smarter prioritization

60%

decline in 90+ day AR, accelerating cash without adding headcount

The Takeaway for Radiology CFOs and RCM Leaders

The future of radiology RCM isn’t about treating all claims the same way. It’s about working claims smartly—with a clearer insight into what revenue is truly collectible—faster and at a lower cost.

Let’s Compare Notes

If you’re exploring how revenue intelligence–led RCM can help prevent denials, uncover underpayments, and unlock revenue trapped in the aged AR limbo—without adding administrative burden or additional headcount—we’d welcome the conversation.

Connect with us for a brief expert consultation to understand where revenue’s leaking in your RCM and how you can recover it.

Because imaging excellence deserves revenue performance to match.

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