The Underpayment Problem
Picture this: You go to the store and buy a pair of sneakers that cost 100 dollars. At the counter, you hand the sales clerk 97 dollars and leave the store. The sales clerk thinks that you may have paid an incorrect amount, but they have a line of people waiting to pay and don’t have the time to look up the actual cost of the sneakers. On top of that, the price of the shoes changes frequently with sales, so they aren’t sure what the cost is today, and the store and their catalog of shoes is massive, meaning that they don’t even know where they’d find the accurate price if they wanted to. Now, imagine every single person in line does that. While being 3 dollars short doesn’t seem like a lot of money, it can have a massive impact if it happens over and over again.
Now, this scenario likely wouldn’t happen at the shoe store for a few reasons, mainly because the sales clerk has technology that tells them if you paid the right amount at the time of purchase. If you pay an incorrect amount, the sales clerk will know immediately, and can address it with you before moving on to the next customer. The technology that the store has ensures that they are getting paid the exact amount that they expect for each pair of shoes at the time they receive the payment. They don’t need to take time out of their busy day to search around for the price of the shoes to make sure you’re not paying them less than they expect.
What Does this Have to Do With Healthcare
Unfortunately for RCM teams in healthcare, this scenario does happen all the time. Payer contracts are constantly changing, and teams often don’t have the time to find and extract expected payment data for each payment that comes through. This results in frequent underpayments by payers to providers, and according to Becker's Hospital Review, accounts for an average of 1 to 3 percent of provider net revenue being lost annually to commercial payers. Because underpayments are tricky to identify and time consuming to look into, they are the sneaky underlying cause of thousands of millions in lost revenue each year.
In a perfect world, healthcare teams would have technology like the shoe sales clerk that tells them immediately when they’re being underpaid, so they wouldn’t have to worry about monitoring or analyzing payments on top of their busy schedules. That’s where we come in.
Adonis Intelligence: Solving the Underpayments Problem
What if you had a single platform that not only helped you manage payer contractual data, but proactively alerted you to true underpayments, identified root cause issues, and analyzed your revenue cycle for patterns and trends?
Adonis Intelligence’s underpayments feature can do just that. Adonis Intelligence provides a one-stop-shop to significantly minimize your underpayments problem and help you recover tens of thousands of dollars more in revenue each year.
Underpayments Challenges and Our Solutions
Let’s take a look at the challenges that Adonis Intelligence’s Underpayments feature can help solve:
Finding and analyzing payer contractual data takes forever:
- The Problem: Storing and managing ever-changing payer contractual data is complex and siloed. This makes it difficult to quickly pull a payer contract to compare the expected allowed amount with the actual amount paid to identify underpayments.
- The Solution: Adonis Intelligence stores and manages all of your payer contractual data in one place and uses machine learning to let you know if the actual amount paid is less than the expected allowed amount in the unique payer contract. Gone are the days of taking the time to search for the most updated version of a payer contract and comparing the numbers. Adonis Intelligence does this for you in the backend and lets you know if something doesn’t look right, saving your team time and headaches.
Incorrectly flagging an underpayment results in a waste of time and prioritization challenges:
- The Problem: Because contracts are constantly changing, it can be easy to misidentify underpayments. Falsely identifying something as an underpayment results skews priorities and results in time lost that could have been spent tackling real underpayments.
- The Solution: Adonis Intelligence keeps a finger on the pulse of all of your updated payer contracts as well as the payments you have coming in. The platform is continuously monitoring your revenue cycle and comparing the payments coming in with what is expected. The platform only flags you when true underpayments arise, enabling you to prioritize the claims you need to appeal and preventing you from getting caught up with false flags.
Bandwidth to focus on underpayments simply doesn’t exist: some text
- The Problem: Unless you have a team that is solely focused on monitoring for underpayments (which we know is often not the case), it’s impossible to find time in the day to monitor every single payment that comes in and research if it aligns with the expected amount from that payer. Leaner teams don’t have the bandwidth to focus on underpayments when they have so many other things going on.
- The Solution: Adonis Intelligence does all the work for you. You can increase the amount your team is getting done, without increasing their workload. With Intelligence, you don’t need to have a big team to focus on underpayments, even the leanest teams are equipped to action underpayments and recover lost revenue.
With Adonis Intelligence, your team can get paid the amount that they deserve without having to lift a finger. Let the technology do the work for you and start recovering 1-3% more revenue each year.
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