Staying ahead in the ever-evolving landscape of insurance requires precision, speed, and adaptability. Artificial Intelligence (AI) is not just a buzzword but a truly transformative force reshaping the payment integrity processes for insurers.
In the US, payment integrity issues cost an astonishing $800 billion in healthcare losses each year! Based on reports by CMS (Centres for Medicare & Medicaid Services), Medicare FFS (fee-for-service) estimated $25.74 billion in improper payments including overpayments and fraudulent billings. Healthcare fraud is a massive challenge that drains billions from the industry every year with less than 10 percent of that amount getting recovered, only if the fraud can be proven in court in an arduous and expensive process.
According to the National Health Care Anti-Fraud Association (NHCAA), the financial losses due to healthcare fraud are in the tens of billions annually, which accounts for about ten percent of the total US healthcare spending! Estimates by the Coalition Against Insurance Fraud show that fraud costs businesses and consumers $308.6 billion a year, which affects Medicare by $60 billion and Health insurance by 36.3 billion!
Shockingly, fraud accounts for only a small part of the total loss. Recovering funds from claims already paid, (post-pay recovery or “pay-and-chase), proves to be even more time-consuming and costly. On top of this, around $47 billion is spent on PI administrative operations.
Putting together a more efficient payment integrity process can result in huge savings for insurers. According to recent market data, having a foolproof payment integrity program could save 10-20% of healthcare costs by putting a stop to improper payments on claims.
The Pre-Payment Method
There has been a rising trend in the industry by way of a shift from post-payment recovery models to pre-payment models. The latter helps avoid 100% of false claims costs instead of recovering only around 30% in the post-payment model.
By detecting fraudulent claims before they are processed for payment, the pre-payment method of claims also reduces the cost associated with reworking, reprocessing, and recovering claims.
Certain AI applications that specialize in finance audit enable a 100% audit of expenses and invoices in real time to find errors, waste, fraud, and policy violations before the payment is made. Utilizing the latest AI technology and advanced analytics can ensure that claims are paid properly from the get go, saving insurers a great deal of hassle!
Leveraging AI to Enhance PI
Here are a few ways in which incorporating AI in prepay payment integrity is reshaping how insurers operate.
- Reducing Fraud and Increasing Speed: By automating routine tasks like data entry, verification, and eligibility checks, AI accelerates the entire claims workflow. Real-time eligibility verification, predictive analytics, and fraud detection algorithms enable swift decision-making and ensure that legitimate claims move seamlessly through the process. AI also increases accuracy, reduces errors, and contributes to a more streamlined and efficient healthcare financial ecosystem. Furthermore, successfully identifying fraudulent claims most at risk for erroneous payment, also helps to maximise savings.
- Adherence to Policy and Benefit Limits: Insurance policies are an extensive blueprint of rules and guidelines that can often be too complex to comprehend. AI-powered software can meticulously evaluate whether the billed services align with the service covered by the policy as services falling outside coverage will result in claim denials. Pre-pay edits thoroughly go through and ensure that claimed amounts do not exceed the predefined limits of a policy.
- Precision in Coding: Medical coding, the standardized language that translates medical procedures and diagnoses into universally recognized codes, lies at the center of healthcare claims. AI-powered pre-pay systems thoroughly assess coding accuracy to prevent billing errors or fraud like misinterpretation or manipulation of codes.
- Duplication Detection: Instances of duplicate claims can seriously inflate costs and squander resources. By detecting and flagging such cases, pre-pay edits protect insurers against overpayment.
- Reducing Provider Abrasion: Automation also minimizes the burden of repetitive tasks like billing, claims processing, and documentation, which allows healthcare providers to focus their attention on patient care. By facilitating smooth and efficient communication and data exchange between multiple healthcare systems, AI also makes it easier to navigate different platforms, reduces provider abrasion, and improves overall satisfaction.
- Reduced Administrative Burden: AI also reduces administrative strain significantly byimproving the accuracy of coding and billing, enabling fewer reviews, and faster payments, and therefore reducing the likelihood of claim denials and disputes. Overall, AI’s ability to optimize workflows and improve communication leads to a more harmonious and efficient relationship between healthcare providers and payers.
With its magnitude for real-time precision, fraud prevention, administrative accuracy, data-driven decision-making, and cost savings, AI stands out as an essential tool to achieve financial stability in the insurance industry. Additionally, AI’s capacity for adaptive learning promotes continuous improvement, ensuring continued refinement with time. As insurers look to this transformative technology, they position themselves to thrive in an ever-changing landscape and come out on top. For more information, please write to hello@felixsolutions.ai.