Evaluating Electronic Benefit Verification Solutions for Your Patient Support Program
By Myra Reinhardt |
Electronic benefit verification (eBV) has emerged as an efficient method for allowing providers to verify a patient’s coverage while in the office and reducing delays in time to therapy. But as eBV technology and methodologies evolve, manufacturers may find themselves overwhelmed with options—and questions—as they design patient access solutions. For example, can the process be too streamlined? Where does eBV add value to the therapy on-boarding experience? When is a comprehensive BV the best approach?
eBV options on the market today
To make an accurate assessment of your options as a manufacturer, you'll need an understanding of where different solutions source the benefits information they return. Here's an overview of the most common methods:
- Payer Surveillance: This method uses a data repository of formulary information from private and government payer plans. Electronic queries provide general coverage guidelines for the requested therapy. The risks associated with this model include inaccurate results due to commercial group coverage carve-outs and lags in updated coverage data.
- Rules-Based: This hybrid approach uses payer surveillance data with an added layer of logic to accommodate unique coverage guidelines at the group level. While more sophisticated than payer surveillance alone, stale data can still lead to inaccuracies.
- Predictive: This model uses artificial intelligence (AI) powered by machine learning. Completed payer verifications continuously teach the model to predict accurate coverage responses in real-time. When the technology detects a variation from an expected result, the system triggers a reconciliation by a trained benefit counselor.
Choose a patient-centric solution from a consultative partner
Which model makes the most sense for your product? Taking
into account the coverage mix and volume of your patient population will help
you choose the most appropriate eBV methodology. The payer surveillance
approach is most viable for patient populations made up of mostly Medicare
eligible beneficiaries. If a significant portion of the population has
commercial insurance, a rules-based model could work better, and a predictive
model is the best option. Patient volumes will influence the effectiveness of
all solution types. Smaller patient populations that are typically seen in
orphan products require special consideration when evaluating options.
The value of AI
Determining whether to invest in a system with advanced
technology capability is critical. It's rather like deciding if the latest
smartphone will meet your personal needs better than a flip phone.
If your needs are basic and you only make a few calls a month, a flip phone will probably fit the bill. If you have frequent touchpoints with contacts via many channels (text, social media, phone, apps, etc.), you'll want to go with a smartphone. Likewise, a program with predominantly uniform insurance coverage has simpler benefit verification needs; therefore, a payer surveillance system could offer the right value.
For a program that requires a more sophisticated eBV solution, the advanced underlying technology and related services to support, groom, and develop the technology will ultimately deliver incrementally more value. It streamlines workflows, lowers administrative costs, improves patient and provider experience, and improves outcomes.
A predictive eBV system has the greatest benefit when it
blends AI and machine-learning technologies with the expertise of humans. This
truly comprehensive eBV solution continually improves the precision of the
results and gives patients better and faster access to therapy.
As these technologies keep evolving and advancing, there is an opportunity to combine all three methodologies to offer an even more robust eBV experience.