Improving Operations and Payment Integrity for Medicaid Programs
The CAQH Member Data Solution is a one-of-a-kind resource that is helping Medicaid programs streamline operations, improve enrollee services and advance payment integrity initiatives.
How Nationwide Coverage Data is Transforming State Programs
Every national health plan and many federal and state programs contribute data to the CAQH registry of coverage information and update it weekly. We use this information to help Medicaid programs streamline redetermination, automate operations and lower costs.
Improved Enrollee Services
Programs can quickly identify if members have third party coverage and make quick and accurate eligibility determinations.
Simplified Administration
The solution integrates with existing Medicaid management systems to simplify implementation and streamline data exchange.
Lower Costs
By identifying other coverage before claims are paid, programs can avoid millions of dollars in costs and reduce their reliance on expensive recovery efforts.
Improved Eligibility Determinations
CAQH provides Medicaid programs an analysis of coverage overlap of enrollees, including demographic and contact information, coverage types and dates and payment responsibility.
This information can be used for eligibility, benefit coordination, payment and enrollee outreach activities. A secure payer-to-payer messaging system enables programs to share documents and resolve issues.
Our Impact
An Innovative Medicaid TPL Approach Drives Cost Avoidance
A Medicaid Program in the Mid-Atlantic was able to perform verifications with 99.5% data accuracy and validate the results directly with commercial carriers. This unique approach to leveraging Third-Party Liability coverage resulted in cost avoidance and reduced out-of-pocket costs for beneficiaries.
8 Pitfalls to Watch Out for in Identifying Third Party Liability
SUPPORTING THE MISSION
CAQH solutions transform eligibility, enrollment, coordination of benefits and third party liability processes for Medicaid programs.
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