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April 6, 2021 Case Study 1 min read

Concerned that their claims weren’t being paid fairly by Medicaid MCOs, a Chicagoland hospital engaged our revenue cycle optimization team to investigate. 

Doctor wearing a stethoscope while reviewing information on a tablet.

The challenge

A Chicagoland hospital with over 200 beds and more than $300 million in net patient service revenue was concerned that they weren’t being paid appropriately by Medicaid managed care organizations (MCOs). First, they suspected that the MCOs had underpaid their claims over the previous 12 months by using incorrect or superseded contract rates. However, they couldn’t validate this with their existing systems. They also felt many of their claims were being denied without appropriate cause. Since the hospital wasn’t confident they were being paid fairly for the care provided, they needed help to determine if they were being underpaid and understand the root cause for their higher-than-normal initial denials rate.

The solution

The hospital engaged our revenue cycle optimization team to investigate their concerns using advanced analytics and make recommendations on how to resolve these issues.

Was the hospital being underpaid?

Our team parsed nine months of claim and remittance files into a proprietary claim analytics database and used the 3M™ Enhanced Ambulatory Patient Grouping system to determine the expected reimbursement for each claim. We developed a sophisticated analytics methodology to systematically match remittances to each claim to validate actual reimbursement independently. Through this process, we uncovered specific patterns where multiple payers had systematically underpaid the hospital.

Why was the denials rate so high with the MCOs?

To determine why the hospital had such a high initial denials rate, our team performed a comprehensive root-cause analysis of denials by Claim Adjustment Reason (CARC), Remittance Advice Remark Code (RARC), payer, service line/type, location, and other variables. We categorized denials into specific reasons based on the data, root cause, and potential resolution and prevention steps. Based on this information, we discovered unique denial patterns associated with each payer which weren’t currently being proactively identified and managed. We developed an action plan to appeal the denials and implement a denials prevention strategy.

The benefit

The client gained actionable insight into specific payers who had systematically underpaid claims. Armed with objective, transparent information, the facility was able to initiate conversations with the MCOs that had underpaid in order to collect full reimbursement. Through this process, the client realized best practices for categorizing CARC/RARC codes into preventable denials, resolution denials, and adjustments. Over a nine-month time frame, our team found potential for over $5 million in recovery due to denied claims as well as nearly $500K in underpaid claims.