Most Pathology and Laboratory practices, whether hospital-based or free-standing, struggle with the prior authorization mandates issued by insurance payers. Originally instituted as a utilization review technique, prior authorization has evolved into an administrative burden with far-reaching influence on an organization’s bottom line, impacting staffing requirements on the expense side and potentially limiting revenue through uncollected denials.
With the administrative burden placed on staff to execute and manage the prior authorization process and cost estimated at $11.18 per manual approval (vs. $2.18 per automated approval), it’s quick to assess that minimizing these factors through automation and supporting specialized guidance can positively impact the bottom line. The return on investment would have a lasting impact and lay the foundation for further automation that’s sure to follow in the future.
Artificial Intelligence Can Positively Impact Prior Authorizations for Pathology Labs
Hospital executives and laboratory administrators, faced with declining revenue, have not yet fully embraced the efficiencies that can be brought by automation and augmented intelligence in the front-end patient access and revenue cycle management processes. It’s estimated that 90% of claims denials are preventable with a more accurate and vigorous prior authorization system.
To further squeeze pathology and lab revenue, the Medicare Clinical Laboratory Fee Schedule (CLFS) is being developed by CMS using private pay pricing input, required from all labs through June, 2019. The Protecting Access to Medicare Act (PAMA) tied Medicare payment rates to those paid by private payers rather than based on historical charges for the first time. It has never been more critical to streamline and automate the healthcare payment cycle starting with prior authorization.
An Ideal Prior Authorization System Augmented by Artificial Intelligence
Currently, most pathology and laboratory teams are manually approaching the preapproval function. This includes filling out forms, faxing, calling, follow-up, and tracking by hand. With most insurance carriers able to process automated submissions, the human effort and possibility for error can be reduced to less than two percent using computerized prior authorization augmented by human specialist support for outliers and emergent/STAT requests.
Let’s look at how AI can support the process for prior authorizations for pathology labs:
- Cloud-based software with dashboard access would extrapolate patient information, evaluate and determine requirements for preapproval
- The program would then submit the requests electronically to the appropriate insurance carrier, with outlier approvals directed to needs-based support from a specialized and highly trained team
- Ongoing and automated follow-up would ensure no requests slipped through the cracks
- Once approval was obtained, patients could be efficiently scheduled with less rescheduling and cancellations and their care would be tracked to ensure compliance with insurance carriers’ instructions and limitations
- Emergency and STAT approvals would be handled by specialists with a goal of 20- to 30-minute resolution
In this type of scenario, patient, provider, and staff frustration are reduced or eliminated, denials significantly decrease, and patient care abandonment due to lack of understanding or fear of accelerating costs is diminished. Conceivably, a pathology laboratory could see more patients, resulting in additional revenue with fewer appointment cancellations.
Currently, the healthcare industry and pathology labs specifically, are experiencing tighter and tighter margins. This is largely due to unyielding pressure on lab reimbursement, value-based care initiatives, and the continuing rise of healthcare consumerism.
Laboratory Economics, in their Forecast & Trends 2018-2020, has projected that lab testing will decline from 3.3% to 2.8% of the industry revenue total by the end of 2020. While the future will remain uncertain, Artificial Intelligence is sure to be a part of the technological resources available to stabilize and enhance the bottom line for pathology groups and hospital and free-standing laboratories.
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