Claim automation

Auto-Adjudication & Optimizing Healthcare Claims Processing

Auto-Adjudication in Claims Processing: Enhancing automation to increase first-pass claim approvals and minimize manual interventions. By leveraging AI-driven rule validation and predictive analytics, providers can significantly reduce the need for manual claim reviews and accelerate reimbursement cycles. This also helps in minimizing unnecessary claim denials and reducing administrative burdens.
Prior Authorization Processing: Streamlining approvals using AI-driven validation and real-time payer integrations.
Medical Billing & Coding Accuracy: Enhancing compliance with automated claim reviews and coding validation.
Revenue Cycle Management Enhancements: Improving financial efficiency with data-driven insights and workflow automation.

Industry Challenges in Claims Editing Process

High Rate of Initial Denials: Many claims require resubmission due to minor coding or documentation issues.
Delayed Reimbursements: Manual interventions slow down revenue cycles and cash flow.
Complex Payer-Specific Rules: Different insurers apply different criteria for claim acceptance, creating inconsistencies.
Manual Review Overload: Billing and coding staff are burdened with extensive manual claim corrections.
Compliance with Changing Regulations: Keeping up with CMS updates, ICD-10 changes, and payer policies.

Enhancing Claims Editing for Providers

Automated Pre-Submission Claim Checks: Identify and correct errors before submission to prevent unnecessary denials.
AI-Driven Coding Validation: Ensuring correct CPT, HCPCS, and ICD-10 codes are used based on payer-specific rules.
Integrated Real-Time Payer Checks: Cross-referencing claims against payer policies before submission.
Predictive Analytics for Denial Prevention: Learning from historical denials to predict and prevent errors before submission.
Automated Appeal Generation: AI-driven workflows that streamline claim corrections and appeals.

AI-Based Validation Checks in Claims Editing

Duplicate Claims Detection: Identifies claims submitted multiple times for the same service, reducing overpayments.
Bundled Service Validation: Ensures that procedures billed separately are appropriately bundled under a single charge.
Modifiers & Coding Accuracy: AI-driven checks confirm the correct use of modifiers, preventing denials due to missing or incorrect codes.
Time-Based & Frequency Rules: Validates services based on frequency limitations and checks for conflicts with previously billed claims.
Place of Service (POS) Compliance: Ensures services are billed in the correct care setting (e.g., outpatient vs. inpatient).
Medical Necessity Validation: Uses AI models to match diagnosis codes with appropriate treatment procedures to reduce medical necessity denials.
Fraud & Abuse Detection: Detects anomalies in billing patterns and identifies potential upcoding or unbundling violations.

Successful Implementations

Our team comprises experienced professionals who have led and contributed to large-scale process automation initiatives for the largest US healthcare payors, including  Elevance Health, UnitedHealth Group, Cigna, Aetna, and Humana.
We have been instrumental in developing automation platforms tailored for claims editing third-party vendors, including First Source, enhancing efficiency and scalability.
Our solutions have delivered measurable gains in accuracy, operational efficiency, and cost reduction.
We ensure strict adherence to industry regulations and best practices, fostering compliance and reliability.

Benefits of Claims Automation

Faster Reimbursements – Reduced manual intervention accelerates claim approvals and payments.
Operational Cost Savings – AI-driven automation reduces administrative overhead and staff workload.
Lower Denial Rates – Automated validation minimizes errors, ensuring higher claim acceptance rates.
Reduced Manual Claim Reviews – AI-powered adjudication significantly decreases the need for manual claim corrections and processing.