The Safety Net: How MedChartScan Protects Against Coding Errors

In high-stakes fields like aviation and medicine, the most advanced systems are defined by their safety features. A powerful engine is important, but the systems that prevent failure are what create trust. The same is true for AI in risk adjustment. Finding potential HCCs is one thing; ensuring the entire process is safe, reliable, and protects against errors is another.

Both humans and AI are fallible. A human coder can miss a detail after reviewing dozens of charts. An AI can misinterpret ambiguous language. A truly robust system acknowledges this and is built not just to find opportunities, but to act as a safety net that catches errors before they impact your revenue and compliance.

At MedChartScan, we've engineered this safety net directly into our platform's core logic. Here’s how it works.

1. Communicating Uncertainty with Confidence Scoring

Not all AI suggestions are created equal. A "black box" AI that presents every finding as 100% certain is misleading and dangerous. Our platform operates on transparency.

For every potential HCC it surfaces, MedChartScan calculates a confidence score. This score reflects the AI's certainty based on the clarity and strength of the supporting evidence.

• A high-confidence suggestion might be a clearly documented diagnosis like "Type 2 diabetes with morbid obesity."
• A lower-confidence suggestion might involve linking a vague symptom to a potential cause.

This allows your team to triage their efforts, quickly validating clear-cut cases and dedicating their expert clinical judgment to the more ambiguous suggestions that require it most.

2. Preventing Submissions of Invalid Codes

One of the easiest ways to trigger a takeback is to submit a code that is no longer valid under the current payment model. With frequent updates like the transition to CMS-HCC V28, this is a significant risk for manual workflows.

MedChartScan acts as a real-time guardrail. Our system is continuously updated with the latest CMS guidelines. It automatically cross-references every potential code against the active model, flagging outdated or non-payable codes to prevent them from ever being submitted. This simple check is a powerful defense against one of the most common HCC coding errors.

3. The Human-in-the-Loop: Your Ultimate Quality Assurance

The most important safety feature of our platform is the workflow itself. We fundamentally believe that no AI-surfaced code should be submitted without expert human approval.

Our entire process is built around this principle. The AI assists, but the coder decides. This mandatory validation step is the ultimate quality gate, ensuring that every single code is backed by both technological analysis and human expertise. This is the core of our AI + Human Validation workflow, and it's your strongest defense in an audit.

Technology Built on Trust

A powerful AI is exciting. A trustworthy AI is essential. By designing our platform with features like confidence scoring, real-time validation, and a mandatory human-in-the-loop process, we've created more than just a productivity tool. We've built a reliable partner designed to protect your organization, empower your team, and bring a new level of confidence to your risk adjustment process.

*Want to see our platform's safety features in action? Schedule a demo and we'll show you how we build confidence into every chart review._