XIFIN Blog - How to Reduce Retro Authorizations to Improve Reimbursement

How to Reduce Retro Authorizations to Improve Reimbursement

  • Vice President, Growth and Strategy , Infinx

Enjoy the following content from our partner, Infinx.

The reimbursement landscape for clinical labs and remote patient monitoring has never been so challenging or so precarious. Patient and third-party payor responsibility continues to shift, and there is no end in sight for ongoing changes and increases in government regulations and insurance requirements.

In a rapidly changing and consumer-centric healthcare payment lifecycle, diagnostic providers — including those focusing on outpatient genetic and molecular laboratory tests or remote patient monitoring — are at a unique disadvantage by the very nature of the service they provide. They find themselves scrambling to manage retro authorizations in an often manual and cumbersome manner.

New advances in Artificial Intelligence (AI) and machine learning in the patient access and Revenue Cycle Management (RCM) arena answer many of those dilemmas and put diagnostic providers back in the driver’s seat.

How Advanced Automation Improves Retro Authorizations

Bridging the lack of face-to-face contact is priority number one. Diagnostic reimbursement is complicated by the fact that they receive and test specimens without ever encountering the patient. This leaves the diagnostic provider in a passive role when ascertaining patient demographic and insurance information — relying on the hospital or the ordering provider to initiate prior authorizations and adequately verify insurance coverage.

When there has been no advanced request for prior authorization approval, the lab, practice, or medical device company is left to request a retro authorization which often includes time-intensive follow-up. This backtracking is often done manually with multiple phone calls, hold times, and faxing back and forth.

When a patient receives a bill, they may have never heard of the clinical testing facility. This creates confusion with unexpected bills denied by insurance for reasons patients often don’t understand. It then falls to the overburdened medical billing personnel to follow up with the ordering provider and gently coax their participation to help resolve outstanding claims issues.

AI-enhanced automation allows an organization to capture actionable and meaningful data with +98% accuracy and then interact with a wide array of payors to accomplish painstaking tasks in real-time through bi-directional integration and communication.

Automated Retro Authorization

The sheer volume of claims and prevalence of comparatively lower-priced encounters in the diagnostic industry can be overwhelming. With the cost to collect relative to revenue being so high, it is paramount that labs streamline the process of identifying prior and retro authorization requirements for each patient quickly.

Ideally, diagnostic providers can electronically interact with the ordering provider at the time of the patient encounter since that is the ideal time to determine what is required and solicit their help if necessary. If there is something questionable, they must move immediately to resolve with the ordering provider or hospital.

For the diagnostic provider, using advanced automation with AI through a unified interface, patient information can be submitted directly to the insurance payor electronically, with all follow up being automatic. Any complex requests or exceptions can then be handled by trained specialists, ensuring an overall increased completion rate and a significant reduction in claims denials.

Whether using a proactive or retroactive approach, prior authorizations can be processed and submitted with a workflow that saves valuable staff time and resources. Retro authorization becomes less of a problem when the prior authorization technology can be fully integrated with the Laboratory Information System (LIS) or other upstream systems. Such an approach makes it far easier to take care of the prior auth during the ordering process, where providers and their office teams can be enlisted to help streamline the information collection process.

Retro Authorization Also Improves Claim Denials

Whether diagnostic providers are in-network or out-of-network, very complex rules and regulations apply to preauthorization, providing an ever-expanding opportunity for claims to be denied. The sheer volume of accounts receivables continues to grow for most labs as patient responsibility increases.

By using an AI-driven, machine learning system to tackle retro authorization, you lessen the need to chase claim denials. This ensures resolution to maximize bottom-line results.

AI-enhanced automation allows an organization to capture actionable and meaningful data with +98% accuracy and then interact with a wide array of payors to accomplish painstaking tasks in real-time through bi-directional integration and communication. 

When diagnostic providers can automate front-end processes with a criteria-based algorithmic system, they can better submit clean and accurate claims to payers. Thereby significantly reducing the denials management process at the back end to a rate less than 2% (of prior auth-related denials).

In Summary

Technological advances are now available that allow machine learning to lead the way in tackling healthcare’s most pressing reimbursement issues, including retro authorizations. AI can reduce diagnostic provider pain points to a minimum by incorporating advanced electronic solutions paired with human intelligence when exceptions exist.

Interested in learning more about automating retro authorizations with your RCM processes? Contact us today.

Published by XiFin
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