What is claims automation?
Healthcare claims are complex: DBC/DOT coding, reimbursement rules, policy conditions and changes in legislation and regulation make the claims process error-prone. According to Vektis, 5–10% of healthcare claims are rejected due to coding errors or missing information.
AI claims automation automatically checks claims for correct coding, completeness and regulatory compliance, and flags errors before the claim is submitted.
How does it work?
The system analyses treatment data from the EHR and automatically matches it to the correct DBC/DOT codes. Rule-based validation checks for common errors: missing procedures, incorrect combinations and deviant tariffs.
Machine learning identifies patterns in historical rejections and continuously updates the validation rules. Ambiguous cases are flagged for manual review by the claims department.
What does it deliver?
Healthcare organisations report 50% fewer claim errors, 30% faster billing and significantly fewer rejected claims. The financial effect is directly measurable: less revenue loss from rejections and faster cash flow through shorter claims cycles.