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Most health systems are locked in a race for coding efficiency, yet many are overlooking a critical vulnerability: where do your quality gaps actually hide?

While “95% accuracy” has become the industry’s security blanket, it can often mask systemic risks.  Coding quality opportunities are not always obvious. In many cases, they sit inside workflows that appear to be performing well, until they show up as denials, rework, or inconsistent coding outcomes in retrospective audits. Spring is a good time to take a closer look and clean out some of the corners of your coding workflows that have become outdated and covered in cobwebs.

The illusion with “95% accuracy”

Most coding technologies today claim around 95% accuracy. But there’s a fundamental issue: there is no consistent definition of 95%. Two systems can claim the same percentage of quality while delivering wildly different financial and operational results because they:

• Measure differently: there is no standardized methodology for what constitutes “accurate”
• Use skewed samples:  accuracy is often calculated using inconsistent sample sizes
• Flatten Impact: minor administrative errors are often weighted the same 

Where coding quality gaps actually show up

In our experience, coding quality gaps tend to concentrate in three specific “blind spots”:

• High-volume workflows with subtle inconsistencies that compound over time
• Diagnostic complexity and nuance in clinical context
• Site-specific documentation patterns that vary across organizations

In many approaches, performance relies heavily on pattern recognition. But those patterns aren’t universal. The way physicians document at one organization can be meaningfully different from another. What works in one environment doesn’t reliably transfer to the next. Without an objective way to define and measure quality, these differences:

• Go undetected
• Vary across sites
• And introduce inconsistency into coding outcomes 
• Lack the ability to learn and adapt over time

This is where many systems hit their limits.

The Strategic Shift: Questions to ask yourself today

To find the gaps that percentages often hide, leadership must shift the conversation from “how fast?” to “how precise?”. 

Start by asking:

• How are coding quality audits defined and measured?
• Are errors evaluated based on severity and impact?
• Can we audit how results are determined?
• Where is performance already strong, and where is it not?
• How are site-specific documentation patterns accounted for?

The Path Forward: Quality as a growth engine

Improving coding performance doesn’t require a total system overhaul. The most effective strategy is to make quality visible:

• Define quality clearly and consistently across your teams
• Identify where performance already meets that standard
• Scale with confidence by building outward from those areas of proven strength

By shifting focus from generic accuracy to site-specific clinical precision, health systems can eliminate the “hidden” gaps that drain resources and finally achieve a coding operation that is both efficient and unshakeable.