At a Glance

Background and Challenge 

A leading U.S. pediatric hospital faced a denial rate higher than the industry average. Their leadership knew that seeing trends and analyzing historical data would allow them to track and prioritize denial prevention efforts. The true challenge was finding and implementing the right infrastructure to interpret the data in their Epic patient billing and payment system. 

Tegria’s Epic revenue cycle optimization and data analytics experts were engaged for a two-part project: 

• Identify process and system changes to improve denial priorities and productivity of staff 
• Develop enhanced data reporting and visualization tools to improve denials management and decision-making 

Solution  

In-depth interviews with patient financial services managers helped Tegria understand the hospital’s present state and build requirements for data analytics. Tegria experts then used a deep understanding of Epic and denials management to extract and present key performance data on denials and write-offs.

The organization was looking for an alternative to out-of-the-box Epic denials reporting that would provide multi-level intelligence on historical denials, open denials, root cause, and ultimately net revenue loss tied to denials. Tegria’s data analytics experts focused on two essentials to deliver useful denials information:  

• Ensuring the collection of accurate and pertinent data 
• Presenting the data using a dashboard to make it easier to see, analyze, and act on patterns, trends, problem areas, and opportunities 

Results 

With a sharp focus on return on investment, Tegria used expertise in Epic, denials management, and data analytics to enable the organization to begin realizing improvements within a few short months. Key results included: 

• Identifying potential operating improvements of up to 10%, or more than $1.5 million in annual net revenue gain 
• Reducing first-pass denials by 2.5% by correcting Medicare sequestration build 
• Identifying 6,000 first-pass denials of un-reimbursed labs 
• Implementing self-service tools, which saved 20 to 40 hours each week on writing reports 
• Saving three to six months of internal development time on data warehouse integration