The Million-Dollar Keystroke: How One Character Can Trigger an Audit
by Yubin Park, Co-Founder / CTO
The Million-Dollar Keystroke: How One Character Can Trigger an Audit
When I10 becomes I110, routine hypertension transforms into heart failure—and millions are at stake
Last year, HHS-OIG published something that changed the game for risk adjustment audits: their first-ever audit toolkit with actual SQL scripts showing exactly how they hunt down suspicious diagnosis codes.
The Problem: When Simple Typos Become Million-Dollar Mistakes
Consider this scenario: A medical coder, working through hundreds of claims, types I110 instead of I10. Seems harmless, right? Wrong.
- I10 = Essential hypertension (not risk-adjustable)
- I110 = Hypertensive heart disease with heart failure (highly risk-adjustable)
That single extra "1" just turned a routine condition into a complex cardiac diagnosis. At scale, across thousands of members, we're not talking about thousands—we're talking about millions in additional payments.
The OIG's Detection Algorithm: Deceptively Simple
The toolkit revealed their "Potentially Mis-Keyed Diagnosis Codes" methodology:
- Count all risk-adjustment eligible codes submitted for the year
- Flag diagnosis codes with only ONE occurrence per patient
- Cross-reference against other diagnosis codes for the same member
- Ask: Could this high-value code be a typo?
Top tip
The pattern that triggers audits: A patient with "only" one I110 claim (heart failure) but multiple I10 claims (hypertension). The OIG's algorithm flags this as potentially suspicious—and they're often right.
The Results: What We Found in Real Data
We've tested this methodology across multiple clients. The findings are striking:
- High frequency: I110 appears as the most common "singleton" high-risk code
- Clear patterns: Patients with one I110 occurrence typically have multiple I10 claims
- Financial impact: Each potential error represents significant risk adjustment payment differences
- Scale: Across large MA plans, these patterns appear in millions of member records
The Data Tells the Story
This chart shows the distribution of potential I10 → I110 keystroke errors from our client analysis. The dark teal section (12.81%) represents cases where patients had exactly one occurrence of I110 (hypertensive heart disease with heart failure) but multiple I10 codes (essential hypertension) throughout the year.
The Strategic Reality: Audit-Proofing Your Data
This isn't just about money—it's about survival. The OIG handed us their playbook. Smart organizations are using it proactively to clean their data before auditors arrive.
Top tip
Scale this across all potential keystroke errors (I120 vs I219, Z23 vs Z21, etc.) and you're looking at multi-million dollar audit exposure for large health plans.
The Competitive Advantage: Prevention Over Detection
We're helping clients build systematic reviews around these OIG methodologies. The goal isn't just finding problems—it's preventing them through:
- Real-time validation: Catching potential keystroke errors at the point of coding
- Pattern analysis: Identifying providers or systems with higher error rates
- Proactive remediation: Correcting errors before they become audit findings
- Documentation review: Ensuring clinical support exists for high-risk codes
Looking Forward: The Tool-Driven Future
The organizations that survive upcoming audits won't be those with the best explanations after the fact—they'll be those with the best detection and prevention systems in place now.
The Bottom Line: When more than 1 in 8 high-value cardiac diagnoses might be keystroke errors, and each error could represent thousands in improper payments, systematic validation isn't optional—it's essential for survival.
Have you run the OIG's keystroke analysis on your risk adjustment data? The results might surprise you—and the financial implications could be staggering.
Interested in learning more about how we help health plans identify and prevent these costly coding errors? The stakes are too high to leave this to chance.