Maximizing Reimbursement Rates with Data Intelligence

Getting claims paid is a tricky subject – there are millions of combinations of procedures, payers, payer contracts, and documentation – too many to keep track of. Billing staff need to remember what denial code combinations mean and how to respond to payer denials to maximize the likelihood of payment – it’s far from an exact science. 

So, let’s dive into three services we provide our client, we’ll call them Company M. With these services, we’ve augmented the billing team’s workflow and digitally transformed their department.

We worked closely with our client’s billing team to understand what their needs were.  They expressed their frustration with their billing process for reviewing a single claim, explaining that to find one piece of information they had to click through many pages of confusing billing software. Tasks that should be quick, such as running a simple report of transaction-level denial code frequency, would take a few minutes, ultimately adding unnecessary time. Manual work like this was required to accomplish minor tasks, many times throughout the day.

In response to this challenge for the billing team, we built a service to provide them with the information they needed at a glance, upon their request. Our claim forensics service now allows the billing team to send us a claim number and receive a report with an analysis of the claim, its transactions, and remittances. We can also do this analysis for multiple claims, or a specific subset of data. For example, our client may request analysis of all claims under a specific combination of payers and procedures. We use intuitive chart designs that help our client understand the claim from a bird's eye view. This service helped to empower Company M’s billing team to focus on their job, getting claims paid, instead of wasting energy and time on wrangling data. 

Here’s a drawing of how a report might look:

Before our collaboration, when company M submitted a batch of claims to a payer, they had little knowledge about which claims would be paid or denied. Our client had to wait until they received remittances to know:

• Will this claim be paid?
• Why will this claim be paid or denied?
• What can I do to ensure this claim is paid? 
• How many claims in this batch will be paid?

In addition, there were many questions with very high value and yet very high uncertainty:

• What can I do to improve the likelihood of this claim being paid?
• Where should I focus my resources?
• How can I minimize the DSO?

Methodiq found that these questions could be answered by leveraging our client’s large dataset. By using machine learning techniques, we created predictive and prescriptive models, which helped to augment and empower the billing team to focus on the claims that were most at risk of being denied. Furthermore, we were able to help them answer these decision-driving questions:

• Which claims are most likely to be denied?
• Are claims more likely to be paid if we add some specific sets of information?
• Which claims are surely going to be denied and are not worth spending time on?

Answering these questions helped us to identify impactable events and optimize the billing team’s workflow.

We used an interpretable model, a method we use to allow us to explain how our model came to its conclusion. This helps our clients to track the reasoning for acceptance or denial, so they are better able to anticipate what information is required before they submit a claim.

Large insurance companies have teams tasked to provide analytics and information on how their company can make decisions directed towards minimizing or delaying payments to providers. They also have teams working on proactive care, used to reduce their insured customers’ need for expensive reactive healthcare. These strategies are aimed at reducing costs and optimizing profits for the payer.

Providers on the other hand, like Company M, provide healthcare and must submit claims for payment. Providers have to worry about the quality of care they provide and about getting paid. This is where our Payer Tactics Identification service helps providers get paid.

We analyze the claims data of healthcare organizations to uncover trends in payer payments and denial reasoning. We then create reports that, in collaboration with the billing team, help us create a set of customized recommendations that apply to specific classes of payers or classes of procedures. The result is a powerful service that helps our client’s billing team stay ahead in a rapidly changing environment.

The healthcare industry is undergoing a digital revolution. With our Data Intelligence services we provide our clients with access to the newest, most secure, and most advanced analytics. Data Intelligence helps us turn analog billing teams digital.