The dental industry faces a unique situation that is rare in other industries and can be described as the "dual-payer problem."
On one end of the spectrum, dental practices face challenges in collecting full and timely payments, largely due to inefficiencies in the interactions between patients, providers, and payers.
On the other end, patients are often confused about what they owe after insurance and why they owe it, leading to questions and delayed payment. This confusion is compounded when patients are not presented with easy and intuitive online bill payment options, and instead must contact practices via phone calls or pay via postal mail.
However, recent advances in dental revenue-acceleration technology and artificial intelligence (AI) are providing relief for this problem, which enables patients to obtain the dental care they need before their oral health issues progress into more serious, more expensive health conditions.
A deeper look at the problem
Consider the usual routine of making a purchase at a grocery store or the pharmacy. Customers simply walk in, select the products they'd like to purchase, present payment, and get on with the rest of their day.
Things are not so simple in the dental industry. Often, patients show up at the dentist's office with no idea of what they'll pay for a given procedure. Once they're done in the chair, they walk out the door being told they'll be billed later without having a clear idea of what they must pay out-of-pocket for the procedure.
For dental practices, the process is equally murky. Due to the mess of different and sometimes contradictory policies and procedures between different insurers, staff members may struggle to understand the proper documentation to send to each insurer for each claim. When practices submit incomplete or inaccurate information, reimbursement timelines are extended and practices must wait longer to obtain the payments they need to fund operations.
For example, let's say a staff member is submitting a claim and includes an x-ray from the wrong quadrant of the patient's mouth as an attachment. This creates an administrative burden for the payer, who must first verify that an attachment is included, ensure that it corresponds correctly to the medical code for the procedure, and, if it doesn't, contact the practice to request the proper documentation.
Payers also employ licensed dentists to perform clinical reviews on claims to help guard against fraud, waste, abuse, and unwarranted payments. These clinical reviews help validate that insurers are paying for treatments and services that are medically justified, but the process is time-consuming and costly.
As a result of the dental industry's dual-payer problem, providers and other stakeholders are increasingly looking to AI and other technological solutions to alleviate this challenge. Here are three ways revenue-acceleration technology is enhancing operational efficiency for dental providers, patients, and payers:
Previsit benefits and eligibility checks
Among the most common reasons that payers deny claims is the provider submitting incorrect insurance information for patients. Modern dental revenue-acceleration systems reduce this problem to ensure providers get paid by checking patients' insurance information prior to a visit, identifying when data is missing or incomplete, and sending text messages and emails that direct patients to online portals where they can enter the correct information prior to a visit.
Instant claims adjudication
Dental providers can leverage AI to enter, review, calculate, and process claims with minimal staff input, enabling faster claims processing, more accurate adjudications, and less manual work. When the software identifies that a claim has missing or incorrect documentation, it notifies the practice of the error in real- time. This allows the practice to correct the issue before submitting the claim, reducing overhead expenses for the payer and expediting reimbursement for the provider.
Clinical review prioritization
When payers employ dentists to perform clinical reviews, they generally target a portion of submitted claims, largely at random. This lack of informed prioritization results in remunerated claims that should not have been paid while incurring expensive clinical review costs for claims that ultimately do get paid. However, AI can analyze claims and attachments to flag submissions that appear to be inconsistent with a payer's rules. That allows payers to prioritize those claims for clinical review, increasing the cost-effectiveness of such evaluations. Perhaps more importantly, this also allows all unflagged claims to bypass the manual review process, greatly expediting payment of those claims for their submitting practices.
Conclusion
The key to eliminating the dual-payer problem and removing this waste from the dental industry is establishing strong engagement points with three major constituencies: patients, providers, and payers. With technology that delivers innovation, integration, and automation, dental practices can be armed with the tools they need to improve operations and profitability.
