In today’s healthcare environment, radiology groups are experiencing a drain to their bottom line that’s impacting their ability to expand and grow. Overlooked revenue leakage from A/R, and the revenue cycle process is limiting their ability to compete and threatens to impact their future earning capacity by limiting growth opportunities negatively.
Many radiology groups are operating well below their potential in preserving and maximizing revenue. Their A/R is growing due to changes in payment structures, regulatory initiatives (i.e., CDSM requirements for Medicare patients now in place), and increasing patient balances (after insurance has paid). Being hit from all sides, these problems are the results (at least in part) of overall inefficiency, high churn rate with billing staff, and increasingly tight margins.
How to Gain Much Needed Efficiency in the Billing Process
By leveraging technology and bringing process efficiencies to the healthcare payment lifecycle, A/R optimization is attainable. The problem is existing revenue cycle management systems don’t readily answer these questions. They simply don’t have the newest technologies and capabilities that are needed to enhance efficiencies, reduce denials, and improve collections but are already a major investment to the group in terms of time and resources.
So what is needed to make meaningful and substantive headway in A/R optimization that doesn’t require replacing the entire revenue cycle management system currently being used?
An alternative to struggling day-to-day with the ongoing A/R process would be to find a solution that provided:
- Engaging and efficient technological enhancements and
- Support by expert billing and denials specialists focused and concentrated on outlying or problematic A/R issues
This not only frees up professional staff to focus on higher-level patient experience improvements but increases revenue and reduces write-offs and days outstanding.
Next Level Automation with Artificial Intelligence and Machine Learning
The key is to find complementary technology that is designed to work in harmony with existing revenue cycle management systems and redefine the A/R workflow. An ideal solution would be able to provide the following:
- An Automated Engine to Determine the “Next Best Action”—a system using AI and machine learning, that through predictive insights and deterministic rules could rank outstanding A/R and categorize the next steps to expedite reimbursement
- Smart Prioritization—an automated, real-time strategy powered by machine intelligence that would prioritize workflow so that efforts are expended in the most efficient and meaningful way
- Predicted Recovery—risk assessment that accurately forecasts potential collectible revenue to allow for appropriate financial planning.
- Denial Analytics—automated claim denial review that would quantify issues and provide actionable insights for operational improvements, to include:
- Missing prior authorizations
- Inaccurate patient demographic information
- Insurance verification errors
With the ability to optimize A/R workflow through a combination of improved technology and expert third-party support, radiology and imaging centers could expect to reduce 60+ days aging A/R by more than an estimated 38% almost immediately as well as significantly boosting profitability. Additionally, practices could reduce the number of claims that are abandoned for reasons of timeliness or efficiency-related issues.
To learn more about optimizing A/R and AI-driven, automation solutions that are available today, contact us.