In the realm of healthcare revenue cycle management (RCM), the accuracy of patient demographics and insurance information is one of the most important pieces to a smooth revenue cycle. Even minor errors can lead to charge lag or claim denials, and slow down the entire revenue cycle, causing significant financial strain for healthcare practices. Artificial intelligence (AI) offers a robust solution, turning what was once a meticulous manual process into a streamlined, automated operation.

‍

Inaccurate patient information is not just a minor inconvenience, but a major obstacle that can result in claim rejections, payment delays, and increased administrative burden. Traditional methods of collecting and verifying patient demographics involve multiple steps with the potential for human error. A whitepaper by the American Health Information Management Association (AHIMA) indicates that demographic data errors are among the leading causes of claim denials. In fact, revenue cycle teams at healthcare organizations surveyed in the study report over $17.4 million of revenue are lost per year in claim denials due to patient demographic errors.

‍

AI and Automation in Revenue Cycle Management

The deployment of AI in healthcare, specifically in the management of patient demographics, is a game-changer. AI-driven tools like pDemographics™ are revolutionizing this space by automatically obtaining and verifying patient data. For example, pDemographics™ uses AI to obtain accurate demographics and insurance information for patients and will update the data in the claim to match before the claim is sent to the payer. This proactive approach ensures that any discrepancies are identified and addressed before they become a problem, reducing patient-to-payment lag and contributing positively to the revenue cycle. Effective RCM companies will use tools such as these to improve your revenue cycle in the following ways:

• Reduction in Claim Denials: AI tools are designed to recognize and rectify inconsistencies in patient data, which substantially lowers the risk of claim denials due to erroneous demographics.
• Decrease in Administrative Load: Automating the data capture process frees up staff to focus on more critical tasks that require human insight, enhancing overall efficiency.
• Speeding Up the Revenue Cycle: With immediate verification and validation of patient information, the time from service delivery to payment receipt is significantly shortened, improving cash flow.
• Enhancing Patient Experience: Accurate information directly impacts patient satisfaction by reducing wait times and administrative hassles associated with insurance and billing.

‍

Technology Drives Future Improvements in RCM

By leveraging AI for patient demographic management, healthcare providers can expect to see a more robust and efficient revenue cycle. According to a report by Healthcare Financial Management Association (HFMA), automation and advanced data analytics are key contributors to RCM optimization. Over a third of healthcare system leaders who responded in a study by HFMA intend to implement automation in at least two functions related to revenue cycle management (RCM) or finance by the year 2024.The primary areas attracting attention for automation include management of denials, pre-authorization processes, enhancements in clinical documentation, coding using artificial intelligence, and self-service options for patients.

‍

How pMD^® Can Help

At pMD^®, our mission is to streamline and optimize the patient care episode and the revenue cycle. Through our advanced, end-to-end practice management and revenue cycle solutions, we can help practices consolidate vendors, reduce costs, streamline workflows, improve patient care and satisfaction, and collect their maximum reimbursement more quickly.

Not sure what a vendor could do to improve your behavioral health billing? Contact pMD^® for a no-commitment financial impact analysis by our team of healthcare RCM experts free of charge!

‍

‍