How does Sarva help with audit readiness?

Sarva reviews 100% of encounters (vs. 5–10% manual audit sampling) and maintains a full audit trail of every validation action. This provides documented evidence of coding quality review for payer audits and compliance reporting.

Use Case

Coding Quality Automation with AI-Powered Code Validation

Coding quality automation uses AI to validate assigned diagnosis and procedure codes against clinical documentation, payer-specific rules, and coding guidelines before claims are submitted. Sarva identifies undercoded services, overcoded encounters, missing modifiers, and diagnosis-to-procedure linkage errors — ensuring every claim reflects the legitimate level of service documented without inviting audit risk.

Assess Your Coding Quality

The Business Problem

Coding errors flow in both directions. Undercoding leaves legitimate revenue on the table — missed add-on codes, unspecified diagnosis codes that could be more specific, and undocumented services. Overcoding invites audit risk and potential fraud exposure. Manual code review is inconsistent — different coders interpret documentation differently, and no team can review 100% of encounters manually.

Affected Team

Coders, coding supervisors, compliance officers, and revenue cycle leadership. Coding quality directly impacts revenue capture, compliance risk, and audit readiness.

How It Works

Current Manual Workflow

Coders assign codes based on clinical documentation. A coding supervisor may audit a random sample (typically 5–10%) for quality. The remaining 90–95% of encounters are submitted without review. Coding errors are caught only when a claim is denied or during retrospective audits — by which time the pattern has been ongoing for weeks or months.

Automated Workflow with Sarva

Sarva reviews 100% of coded encounters. It validates ICD-10 specificity, CPT/HCPCS appropriateness, modifier correctness, diagnosis-to-procedure linkage, and payer-specific coding rules. Undercoded encounters are flagged with suggested additions. Overcoded encounters are flagged for review. The result is consistent, comprehensive coding quality validation without adding headcount.

Inputs

Assigned ICD-10, CPT, and HCPCS codes
Clinical documentation (notes, operative reports)
Payer-specific coding rules and LCDs/NCDs
Provider specialty and service type

Outputs

Code validation results per encounter
Undercoding flags with suggested additions
Overcoding flags for review
Modifier validation results
Coding quality metrics by provider and coder
Audit trail for compliance reporting

Human Oversight

Coders review flagged encounters and confirm or adjust codes. Sarva surfaces potential issues but does not change codes without human confirmation. The system learns from coder decisions to improve future flagging accuracy and reduce false positives.

Security Considerations

All clinical documentation and coding data is encrypted and processed in an isolated environment. No data shared between customers. Full audit trails for compliance reporting. HIPAA BAA included. SOC 2 Type II certified.

Integration Considerations

Sarva integrates with your EHR to access clinical documentation and your practice management system for code data. The validation engine works alongside your existing coding workflow — coders see flags within their normal review process, not in a separate tool.

Limitations

Sarva cannot code encounters from scratch — it validates codes that have been assigned. If clinical documentation is insufficient to support any code, Sarva flags the documentation gap but cannot generate the missing documentation. Coding quality automation supplements, not replaces, certified coders.

Key Performance Indicators

Coding error rate

Target

< 2%

Undercoded encounters caught

Target

> 90%

Coding audit pass rate

Target

> 95%

Revenue from missed codes

Target

Measurable increase

See how this workflow applies to your practice.

Assess Your Coding Quality

Related Connectors

AI-Assisted Medical Coding: Accuracy, Compliance, and Revenue Capture

Frequently Asked Questions

No. Sarva augments coders by validating their work and flagging potential errors. Coders review flags and make the final coding decision. This shifts coders from manual code assignment to quality review and exception handling — improving both productivity and job satisfaction.

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