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Academic Health System Stabilizes DNFB in 60 Days

Client Overview

The conversation began in a small executive conference room just off the finance suite.

On the screen: DNFB trending upward for the fourth consecutive month. Coding queues growing longer. Overtime costs climbing faster than budgeted. For a mid-sized Academic Medical Center with roughly 350 beds and $750M in annual net patient revenue, the margin for inefficiency was shrinking fast.

Patient volumes were steady, approximately 28,000 inpatient discharges and more than 220,000 outpatient encounters annually, but cash flow was becoming increasingly unpredictable. Leadership knew the issue wasn’t demand. It was how work was moving through the revenue cycle.

Stabilizing DNFB in 60 Days Through Labor Optimization

When Complexity Meets Capacity Limits

As a teaching hospital, the organization managed:

  • Teaching physician documentation requirements
  • High-acuity inpatient services
  • Complex surgical and specialty-driven outpatient encounters
  • Ongoing audit and compliance scrutiny

At the same time, the revenue cycle team operated under persistent workforce pressure. Coding vacancies remained open for months. Overtime and contract labor filled gaps, but costs continued to rise.

Despite experienced staff and strong institutional knowledge, the symptoms worsened:

  • Coding backlogs delayed billing on high-dollar cases
  • DNFB continued to climb, particularly on inpatient encounters
  • Productivity gains came at the expense of higher query rates
  • Cost-to-collect increased without a corresponding improvement in cash

Leadership faced a familiar academic health system dilemma: how to improve throughput without sacrificing compliance, or burning out the team.

The Moment of Clarity

A focused assessment reframed the problem. It wasn’t that coders lacked skill. It wasn’t that volumes were unmanageable. It was that all claims were being treated the same.

Low-risk outpatient encounters moved through the same queues as complex inpatient cases. Experienced coders spent hours touching claims that required little judgment, while high-acuity cases waited. Efforts to “push productivity” only increased rework and DNFB. That realization changed the direction of the engagement.

Redesigning How Work Flowed

Instead of adding staff or accelerating pace, the organization redesigned the operating model itself. Claims were segmented by complexity and financial risk, creating intentional differentiation in how work moved through the system.

  • Low-risk claims were routed through touchless workflows supported by embedded compliance logic
  • Moderate-complexity claims followed streamlined paths with limited manual intervention
  • High-acuity, high-dollar encounters were prioritized for experienced coders

Documentation standards were tightened to reduce avoidable queries, and real-time dashboards gave leadership visibility into DNFB, productivity, and quality at the same time, something they had not previously had in one place. The goal wasn’t to move faster.It was to move smarter.

Momentum Within 90 Days

The impact became evident quickly, and held. Within 90 days:

  • Touchless claims increased from 19% to 46%
  • Coder productivity improved by 21%
  • Coding backlogs were reduced by 38%
  • DNFB stabilized within 60 days after months of steady growth
  • Cost-to-collect declined by 110 basis points
  • Coding audit pass rates remained above 98%

Notably, these improvements were achieved without adding headcount, increasing overtime, or loosening compliance standards.

A More Sustainable Operating Model

To ensure results endured, the organization embedded governance into daily operations:

  • Weekly DNFB and productivity reviews
  • Routine coding audits aligned to automation thresholds
  • Periodic reassessment of claim routing logic
  • Executive oversight tied to both financial and quality outcomes

What emerged was a revenue operations model better aligned to the realities of a mid-sized academic system, resilient, disciplined, and less dependent on scarce labor.

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