Professionals in a conference room for a team meeting

Advanced Revenue Cycle (ARC®): Scan

The monitoring phase.

ARC® Scan is a revenue cycle operations monitoring solution that enhances business value from revenue cycle operations by tracking operational performance and providing actionable information to drive financial improvement. It is driven by our proprietary approach that incorporates an analytic driven viewpoint developed by practitioners with deep revenue cycle subject matter expertise.

    Enhancing value from revenue cycle operations

    We scan your revenue cycle performance over time to identify ongoing opportunities to drive improved cash flow, increase annual net revenue reimbursement and reduce cost. By looking at the underlying issues over time, organizations are able to track both performance and impact of the operational improvement the solution identifies. By leveraging our deep revenue cycle subject matter expertise combined with the analytical strength of our proprietary monitoring toolkit, we are able to discover insights from the data you already have, but thinking about it in ways that provide deeper findings.

    Thorough data diagnostic of major functional areas

    ARC® Scan is built to diagnose and trend breakdowns within the core functions of revenue cycle detail level measures providing insight into all critical operational outcomes. This allows the solution to identify opportunities to improve net revenue, reduce excess costs and improve cash performance from the following areas:

    • Pre-registration                
    • Registration       
    • Financial counseling      
    • Charge management      
    • Unbilled management
    • Self-pay follow-up
    • Third-party follow-up
    • Denial management
    • Credit management

    Key solution value

    ARC® Scan provides a healthcare provider’s management team with the ability to:

    ARC Scan key solution values

    ARC® Scan Diagnostic

    Built by practitioners for practitioners 

    Patient access process rejection analysis

    • Understand process level first pass payer rejections to identify process breakdowns
    • Allow Natural Language Generation to identify deeper trends related to specific procedures or service areas

    Third part A/R analysis

    • Determine if the current A/R snapshot is within industry standards and the cash flow impact of negative performance
    • Use the power of Natural Language Generation to quickly determine “hot spots” of accounts that may be in jeopardy of untimely filing

    First pass rejection trends

    • Evaluate first pass payer rejections over time to understand if improvements are being made and have an impact
    • Identify trends that indicate poor process performance procedures or service areas