Transforming Healthcare Processes and Revenue Cycle Management with Intelligent Automation

Automated credentialing is the use of technology, including AI, machine learning, and robotic process automation (RPA), to streamline the verification and approval of healthcare providers’ qualifications, certifications, and compliance requirements. This ensures that providers meet the necessary legal, regulatory, and payer-specific standards to practice and receive reimbursement.

The process includes:

1. Data Collection
   • Providers submit their information, including:
     • Personal details (name, NPI, contact info)
     • Educational background (medical school, residency)
     • Board certifications and licenses
     • Work history and malpractice claims
     • Continuing medical education (CME) records
   • This data can be collected via a self-service portal or integrated with provider databases.
2. Primary Source Verification (PSV)
   • The system connects to official sources, such as:
     • National Provider Identifier (NPI) registry
     • State medical boards
     • DEA and OIG exclusion lists
     • Educational institutions and certification boards
     • Medicare and Medicaid databases
   • AI-powered tools extract and validate information in real time, reducing the risk of human error.
3. Compliance Checks
   • Automated systems cross-check providers’ credentials against:
     • Federal and state regulations
     • Hospital or payer-specific policies
     • Sanctions or disciplinary actions (e.g., National Practitioner Data Bank - NPDB)
     • License expiration or renewals
4. Application Processing & Workflow Automation
   • AI-driven workflows automatically:
     • Fill out payer enrollment applications
     • Submit applications for approval
     • Track credentialing status in real time
     • Notify providers of missing or expiring documents
5. Approval and Provider Enrollment
   • Once verification is complete, the system:
     • Generates digital credentials for approval
     • Submits applications to insurance payers for network enrollment
     • Integrates approved providers into hospital or clinic databases
6. Ongoing Monitoring and Re-Credentialing
   • The system continuously monitors for:
     • Expired licenses or certifications
     • Changes in provider status (e.g., sanctions, lawsuits)
     • Regulatory updates requiring re-credentialing
   • Alerts are sent for required renewals to maintain compliance.

• Increased Accuracy – Reduces coding errors and claim denials.
• Faster Reimbursements – Speeds up claim processing and approvals.
• Cost Savings – Lowers administrative workload and operational costs.
• Regulatory Compliance – Ensures adherence to coding guidelines and payer policies.
• Revenue Optimization – Identifies undercoded services and maximizes reimbursements.
• Real-Time Insights – Uses predictive analytics to improve billing efficiency.
• Scalability – Handles large claim volumes seamlessly across specialties.

AI-driven coding and billing enhance efficiency, reduce errors, and optimize revenue cycle management.

AI-powered payment posting and reconciliation automates the process of recording payments, matching them with claims, and ensuring accurate financial reporting. This eliminates manual errors, speeds up reimbursement cycles, and improves revenue cycle management (RCM) for healthcare providers.

• Automated Data Capture – Extracts payments from ERAs, EOBs, EFTs, and bank statements.
• Smart Payment Matching – Accurately assigns payments to claims, reducing errors.
• Denial & Underpayment Detection – Flags discrepancies and automates resubmissions.
• Bank Reconciliation – Matches payments with deposits for financial accuracy.
• Real-Time Reporting – Provides insights on cash flow and revenue trends.

AI streamlines payment posting, minimizes errors, accelerates reconciliation, and enhances financial efficiency.