Medicaid Membership and Premium Reconciliation

One Size Does Not Fit All

Medicaid presents payers with a unique set of challenges. While federal regulations mandate coverage for certain populations and services, variances among state Medicaid programs abound, prohibiting health payers from developing a comprehensive strategy for Medicaid on a national or even regional scale.

Change on the Horizon

The possibility of Affordable Care Act (ACA) repeal currently looms large, with the real possibility that Medicaid program variability between states will increase exponentially, as more responsibility for Medicaid is ceded to state government.

What Always Stays the Same?

But what doesn’t change, no matter the state, is the need for payers to ensure data quality and integrity, and safeguard process accuracy and efficiency in their Medicaid programs. What’s needed is a platform solution with the flexibility and agility to adapt to individual state nuances along with future regulatory changes.

The Infogix integrated suite of data and analytics software solutions provides a single, highly configurable platform that allows a payer to easily adapt their Medicaid program for any state regulatory and process environment. In Medicaid administration, there is a constant flow of information to and from many entities, including the payer, member, state, third-party vendors and providers. Controls must be enacted for effective transactions and interfaces, and data quality must be reconciled between sources and systems to maintain integrity. Infogix reduces risk and cost through comprehensive data reconciliation across your Medicaid program.


Medicaid Membership & Premium Reconciliation


Case Study

Healthcare Membership Visibility And Analytics Through a Single Platform


Membership Reconciliation

Left unchecked, even the most minute issue with inaccurate membership data can result in compliance exposure and reputational damage. Failure to implement an automated reconciliation solution, or reliance on an antiquated process comprised of semi-automated and manual workarounds, only means increased costs and wasted resources. An automated membership reconciliation approach has numerous advantages, including:

  • From Reactive to Proactive: Automatically reconcile data between payer and government (or designated government agent), with immediate identification of inaccuracies
  • Stops Inaccuracies at the Source: Detect and flag incomplete and/or duplicate data/file submissions
  • Flexible and Adaptable: Capture data from any enrollment source, on a custom-
  • designed schedule
  • Big Picture Visibility: Generate both summary and detail-level membership reconciliation and discrepancy reports
  • Peace of Mind: Ensure smooth administration and avoid delays in member processing

Membership reconciliation can assure the accuracy of your membership data early on, before issues like duplicate member files or other errors can negatively impact member satisfaction or HEDIS scores.

Premium Reconciliation

Just as with membership, Medicaid premium arrangements vary widely by state. States who have been granted a Section 1115 Demonstration Waiver may charge enrollment fees or monthly premiums to certain enrollees. Payers may be receiving these and other premium payments from a state agency or affiliate, directly from enrollees, or a combination thereof.

Whatever the state process for Medicaid premium payments, the Infogix automated reconciliation solution can:

  • Ensure accurate payments and allocations
  • Flag payment discrepancies and route for investigation and resolution
  • Detect duplicate file submissions
  • Correctly calculate member invoices
  • Assure monthly adjustments reconcile with outstanding balances

In Medicaid, premium and membership data reconciliation are two fundamental steps you can take to buttress success in any state, from Alabama to Wyoming, as successful programs are built on a foundation of quality, reliable data. And the agile Infogix solution can be leveraged in any state, no matter what the future may hold.