Radiology backlog recovery that protected timely billing

A large, not-for-profit academic health system operates a multi-hospital network with a broad outpatient footprint and a high-volume physician enterprise. The provider’s near-term goal was straightforward: bring PB Radiology inventory back under control, keep current volume moving, and maintain coding quality while the backlog was reduced.

Vee Healthtek was brought in to run the recovery like an operating system - prioritized, visible, and governed - rather than a one-time staffing push.

The Challenge

The provider was not facing a routine work queue cleanup. It needed to address three pressures at once: older Radiology inventory, new weekly volume, and encounters moving closer to timely filing thresholds. The issue was not only the size of the backlog; it was the fact that incoming work continued while aged inventory still had to be cleared.

The primary bottleneck was capacity. The available resource model was not sufficient to manage both backlog and incoming volume simultaneously, and if the situation was not addressed promptly, it could delay billing and reimbursement cycles. In short: the work could not simply be pushed harder through the same model. It had to be prioritized, segmented, staffed differently, and governed more tightly.

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The Solution

We ran the backlog recovery as a measured, governed operating model rather than a one-time staffing push. Our approach was anchored in four mechanisms:

• Production control with risk-based prioritization: Prioritized timely filing-sensitive inventory first, then shifted into a hybrid model that kept 2026 date-of-service inventory close to current while continuing to reduce older 2025 date-of-service inventory.
• Complexity-based workflow segmentation: Separated simpler Radiology work from more complex charts. Simpler modalities and lower-complexity charts were routed to appropriate resources, while experienced Radiology coders stayed focused on complex charts where accuracy risk was higher.
• Rapid capacity expansion with dedicated current-volume coverage: Expanded capacity through skilled coders across multiple locations, part-time support, weekly onboarding, and extended weekday and weekend coverage. A dedicated team also handled regular incoming inventory so new volume did not simply become the next backlog.
• Quality governance and daily operating discipline: The recovery was managed through daily stand-ups, work allocation routines, dedicated reporting ownership, quality consolidation, and weekly provider status reviews. Audit controls, error-trend analysis, corrective action planning, and refresher education helped keep quality stable during the ramp.

The Impact

• Processed 1 million+ PB Radiology records during the recovery period, helping clear a high-volume backlog while keeping current Radiology coding work moving.
• 8 months of backlog completed in 16 weeks, with the 2025 PB Radiology backlog completed and 2026 DOS brought to a nearly current position.
• Collections run-rate lift: average monthly collections increased from ~$490k/month to ~$680k/month (~38% uplift).
• Weekly throughput scaled from about 10,000 to 130,000 records giving the provider the capacity needed to reduce aged inventory while continuing to absorb new weekly volume.
• Radiology coding quality held at 96% during the 2026 recovery period, even as production accelerated sharply.

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Why Us

The provider wanted a partner who could operate inside complex academic health system workflows, handle high-volume Radiology coding, and stand up to intense operational scrutiny. Prior Radiology performance helped open the door; disciplined execution, quality control, and a transparent operating model closed the loop.

“What stood out was how closely the team partnered with us throughout the recovery. They listened, adapted quickly, and helped us regain control without losing sight of quality.”
- Finance Leader

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Transferable Insights

Treat backlog recovery as a control system, not a cleanup project. When aging specialty inventory threatens timely billing, the answer is not simply adding more people. The stronger model is to prioritize by financial and filing risk, segment work by complexity, assign specialized resources where accuracy matters most, and maintain daily visibility through governed reporting and audit loops. That is how health systems can increase throughput without trading speed for quality.