Data Management and Analytics to Optimize Revenue Cycle

A major healthcare organization in the US, we’ll refer to them as Company X. Their billing department receives claim information and is tasked with billing and ensuring claims get paid quickly.

Company X came to Methodiq with the following problem: A large portion of their claims were being denied by payers. For example, when Company X submitted a claim, payers often asked for additional information such as documents, attachments, and medical history, ultimately denying the claim until the documents were gathered. This is one of many tactics used by payers to delay payment.

We worked closely with Company X to identify their blockers, because our ability to assist our clients is in direct proportion to truly understanding the challenges they face.

Knowing which tactics payers use and spotting them in real-time was critical to optimizing the Revenue Cycle for our client.

Company X needed answers to the following key questions:

1. What are the specific reasons payers are denying claims?

2. How are the reasons for denials changing over time?

3. Which payers are using which denial codes?

4. Which payers are paying more slowly?

5. Which payers are behaving in a way that is anomalous?

6. Are claims being paid consistently at the same rate by all payers?

7. Which of these sets of claims will be paid, and which claims will be denied and why?

8. Which denial codes are most common with which types of procedures?

Questions 1-7 required Descriptive Data Intelligence. Question 8 required Predictive Data Intelligence.

For humans, it’s nearly impossible to manually try to answer the questions raised above. However, with our advanced analytics technology that we call Data Intelligence, it is possible. How? We leveraged the large volumes of historical medical claim data of our client. This data included records of past transactions, what was paid, what was denied, and the reasoning. We used these records to build two analytics services:

1. Claim Forensics - Generates detailed reports on claims to find trends. This allowed us to uncover payer tactics faster.
   
   
2. Predictive Engine - Predict if a claim will be paid or not paid and the reason. This allowed us to anticipate and change the future.

Company X partnered with Methodiq to solve this problem.

We worked closely with Company X to understand their pain points and empower them with reports and analytics services, helping them to stay on top of payer tactics and receive payments in a timely manner. 

We helped to:

1. Provide the client with answers to their specific questions.
   
   
2. Understand precisely what their challenges were and solved them through our analytics and AI services that we call Data Intelligence.

Throughout this process, we maintained a focus on security and ensuring compliance with HIPAA and other US laws and regulations.

We empower our clients with intelligence to help them answer similar questions in the future.

Today when our client bills their payers, they can be confident that they maximize the likelihood of claim payment. They can forecast which claims will be paid and shift resources to more difficult claims. Our client receives the benefits of:

• Improved financial performance
• Increased confidence in identifying payer tactics
• Increased efficiency and reduced manual labor
• Advanced analytics capabilities

Our mission with Data Intelligence is to provide an avenue for our client to be more aware of payer tactics in real-time and help our client focus on what matters most to them: Getting paid.