How AI Can Optimize the Radiology Revenue Payment Lifecycle

By Infinx
September 19, 2019

As the radiology reimbursement landscape evolves and profit margins continue to tighten, forecasting and strategies turn towards new technologies and streamlined procedures as the way forward. Artificial intelligence (AI) is one of these technologies that deliver on that promise today.

Successful AI initiatives focused on the patient encounter are renewing interest in the efficiencies gained by automating redundant, time-intensive processes. Where over 70% of prior authorizations, as an example, are still submitted and followed up manually, bold new AI-driven software options implemented in radiology groups around the country.

How AI-Enhanced Technology is Changing the Revenue Lifecycle

Traditionally, aspects of the healthcare payment lifecycle have developed as passive responses to new governmental, regulatory, and insurance payer guidelines and rules. Working within the foundations of a financial model, patient access, prior authorizations, and the denials process took demographic and clinical information and codified it within the billing function.

Now well-established, the solution may be to find automated alternatives to these manual processes that can streamline the workflow and allow providers and employees to return their focus to the patient encounter.

AI and Prior Authorization

For radiology and outpatient imaging centers, one of the most time-intensive functions performed manually in the billing lifecycle is prior authorizations (PA). Using AI-driven cloud-based software that can integrate fully with your EMR/EHR, functions that have taken on average of 14 hours per week, per provider (at the cost of roughly $80K per year) can now be accomplished in real-time as follows:

  • Make the determination in real-time if a PA is required, or not
  • If it is, initiating and submitting the PA claim to the appropriate insurance payer
  • Automated follow-up with payers and real-time status updates to help your staff schedule procedures on time
  • Real-time notification when a claim has been approved

Not only does this exponentially improve reimbursement, but equally important, it increases patient compliance and more readily achieves positive care outcomes with minimal rescheduling issues. Patient encounters become much more affirmative.

Insurance Verification and Benefits Eligibility

As an additional enhancement for radiology groups and outpatient imaging centers, insurance verification, and benefits eligibility make a smooth expansion in an AI and machine learning environment. By accessing patient insurance information, radiology testing, and procedure eligibility and benefit coverage can be verified in real-time.

Clinical Decision Support Mechanism

As of January 1, 2020, Clinical Decision Support Mechanisms (CDSM) will be required for reimbursement. While this process must be initiated by the ordering provider, radiology groups will have reimbursement impact for Medicare patients if the certificate of care is not present. This is another area in the patient access arena where automation and AI-driven software can ensure overall compliance and capture reimbursement.

AI and Denials Management

Turning focus to after the fact, the denials management process has long been a source of abandoned revenue and overinflated days outstanding. With between 55-65% of denials never corrected, followed up, or appealed due to a lack of time or expertise, AI can reduce this revenue leakage by automating the denials management function in the following ways:

  • Forecast and prioritize the probability of effectiveness, based on payers, aging, modality, etc.
  • Initiate predictive rules to determine the next best action
  • Follow up with insurers through auto-created claims for resubmission and appeals letters
  • AI-assisted automation prioritization that can include insurance verification checks, coding mismatch checks, etc.
  • Root cause analysis and operational analytics for ongoing oversight and future improvement forecasting

Gaining ground in the reimbursement fight in minuscule increments makes less sense when state-of-the-art automation and AI-driven solutions are available today. The ROI and the impact on the bottom-line for radiology groups and outpatient imaging centers can be felt in real-time, and patient satisfaction will be measurably improved with increased efficiency and timely scheduling and billing practices.

Contact us today to explore the ways AI can improve your radiology revenue payment lifecycle.

About the Author

Infinx

Infinx

Infinx provides innovative and scalable payment lifecycle solutions for healthcare practices. Combining an intelligent, cloud-based platform driven by AI with our trained and certified coding and billing specialists, we help clients realize revenue, enabling them to shift focus from administrative details to billable patient care.

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