How machine learning transforms credit balance management 

Most healthcare revenue cycle leaders would agree: Resolving credits is necessary but a drag.  

The good news is that automation and machine learning are taking both the time and tedium out of the routine work of resolving credits. 

What is machine learning, and what does it have to do with credit balances? 

We hear “AI,” “automation,” and “machine learning” frequently in healthcare, but what do they mean, particularly when it comes to your revenue cycle operations and resolving credit balances? 

According to IBM’s definition, artificial intelligence is a field that combines computer science and robust datasets to enable problem-solving. Machine learning, a subset of AI, is a set of algorithms that analyzes and learns from data, quickly and efficiently identifying patterns that might otherwise be obscure and difficult for people to identify. Machine learning also enables you to build automations based on those patterns. 

There are many processes staff complete when reviewing transactions and attempting to resolve credit balances, from identifying patient overpayments to issuing refunds to correcting contractual adjustments and more. Machine learning models can take historical patient accounting system data and analyze patterns to predict how accounts might be resolved. These models help your team zero in on the actions that need to be taken. Then, you can layer on automation to drive those actions. 

These technologies essentially can provide revenue cycle teams with high-confidence predictions about their credit accounts—insights that are most likely not possible with traditional, manual methods. 

How else can leveraging machine learning benefit credit balance management? 

Putting people resources toward working credit accounts—accounts that are likely going to require you to send cash out the door—is understandably not a high priority for revenue cycle leaders. Let’s face it.: Your organization would rather keep your people focused on the accounts that are generating cash for your organization. 

Kodiak’s customers report they have spent upwards of 15 minutes per account on average researching transactions and communicating with payors to determine what the appropriate resolution is before they post the transaction. Machine learning automates some of the routine activity it takes to resolve credit balances, augmenting your staff’s work and giving them time back to focus on accounts that require a human touch, such as those that need a more detailed analysis or interaction directly with payors. It’s about gaining efficiency, not replacing staff with machines. 

Machine learning also can be useful in resolving more complex accounts. For example, some credit balance accounts might require more than one transaction. An account might need a contractual correction prior to sending a refund check to a patient. Or a balance might need to be moved from the patient bucket to the insurance bucket. Machine learning is adept at identifying the steps that need to be taken and can help facilitate those processes. 

How can Kodiak help? 

Why turn to Kodiak for help incorporating machine learning and other technology tools into your credit balance management processes? First, our visibility into data is unmatched in the industry. In our work with customers, we see patient accounting transactions for 2,300 hospitals and 375,000 physicians. We aggregate more than 50 million transactions daily in our system, the Kodiak Platform, which is powered by Kodiak Revenue Cycle Analytics.  

We’re able to build our machine learning models based on that volume of transaction-level detail that is flowing through our system. This, in turn, helps us arrive at better resolutions for our customers. We’ve also been in the accounts receivable space for a long time. Our expert team has reviewed thousands of accounts and has years of experience working to make sure healthcare organizations aren’t wasting valuable resources and sending money out the door. 

Ultimately, Kodiak takes our vast amount of data, combined with our expertise and technology, and helps organizations like yours spend less time and energy resolving credit balances. That means you can focus on the business areas that help you better serve your patients and turn credit balance management—a process that might otherwise be a pure cost center—into a benefit for your organization. 

To learn more about Kodiak Credit Balance Management, visit our website or contact our experts today. Read more about how automation can enhance credit and debit balance workflows here.