DRG validation that protected cash and compliance

A large Southwest nonprofit health system needed to maintain dependable facility and professional coding flow while strengthening its pre-bill revenue integrity controls. Growth increased throughput demands and raised the cost of coding variability across DNFB sensitivity, denial triggers, and Diagnosis-Related Group (DRG) audit exposure.

The provider engaged our team to operate the work as a measured, visible, and governed system. The operating model connected coding production, quality analytics, and pre-bill DRG validation so inpatient claims could move with stronger controls before submission.

The Challenge

Revenue cycle and coding leaders measured success through accuracy and turnaround time. Those measures had to hold through volume spikes, PTO seasons, and backlog events, at the same time that inpatient claims needed more disciplined DRG review before billing.

The operational risk involved both sides of DRG accuracy: missed legitimate reimbursement from down-coded accounts and avoidable over-coding exposure from up-coded accounts. A standalone audit model would not solve the throughput problem or feed learning back into coder workflows. The provider needed a governed pre-bill control that could improve coding accuracy without slowing claims.

The Solution

A governed, tech-enabled DRG validation engine

We built a workflow that treated DRG validation as an operating control across production, quality, and revenue integrity. The approach was anchored in four mechanisms:

• Production control with performance visibility: Used recurring, structured reporting for volume and quality across chart types, including IP, DRG review, observation, surgery, and endoscopy, to create a predictable operating cadence.
• Quality analytics and closed-loop CAPA: Tracked error trends, performed root-cause analysis, and reinforced corrective and preventive action through targeted education on PDx, CC/MCC validation, PCS capture, disposition, and POA.
• Pre-bill DRG validation control: Prioritized high-impact cases, reviewed the full medical record against coding guidance, issued compliant corrections and query opportunities, and fed learnings back into coder workflows.
• Governed platform transition support: Supported a major platform transition in the coding environment within the same governance model so throughput remained predictable instead of treating the transition as a side event.

The Impact

• DRG validation delivered about $784,000 in total value by recovering legitimate reimbursement from down-coded accounts and preventing over-coding exposure from up-coded accounts.
• Quality held at about 99% across more than 5,200 facility accounts comfortably above the 95% benchmark while maintaining steady throughput across chart types.
• DRG audit corrections produced about $205,000 in combined impact by improving under-coding and reducing over-coding exposure before claim submission.
• Coding throughput stayed predictable across chart types including IP, DRG review, observation, surgery, and endoscopy, supported by volume and quality reporting routines.
• Coder feedback loops strengthened DRG accuracy controls through dashboards, trend analytics, standardized feedback, and CAPA tied to documented coding topics such as PDx, CC/MCC validation, PCS capture, disposition, and POA.

Why Us

The provider prioritized risk-managed adoption and operational confidence. The work started small, validated performance, and expanded scope while maintaining control. The provider valued the ability to ramp coverage during backlogs and peak periods while staying consistent on accuracy and turnaround time, alongside satisfaction with security and operational reliability.

“When volume spikes hit, you ramp quickly - and quality still holds.”
- Leader

Transferable Insights

For health system CFOs, Chief Revenue Cycle Officers, and HIM, coding, CDI and mid-cycle leaders, the practical lesson is to treat DRG validation as a pre-bill control system. Pair clinically informed review with dashboards, trend analytics, CAPA, and coder feedback so revenue integrity improves while coding throughput remains visible and governed.