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  • Using Data to Understand Pre-pandemic Enrollment Patterns and Protect At-risk Patients During Medicaid Redetermination

    When the COVID-19 public health emergency (PHE) expires, it will be a pivotal time for providers, payers, and patients.

    When the COVID-19 public health emergency (PHE) expires, it will be a pivotal time for providers, payers, and patients. As state Medicaid program administrators and managed care organizations (MCOs) navigate the unwinding of the PHE declaration, they’re uncovering significant concerns around Medicaid redetermination, including:

      • Whether state partners will be able to successfully meet the continuous enrollment requirement
      • Insufficient staff resources needed to manage Medicaid redetermination
      • At-risk patients who will lose their Medicaid coverage despite eligibility
      • Uncertainty about enrollment patterns during continuous enrollment
      • Downstream surge of uninsured and self-pay patients who have fallen off Medicaid rolls

    Mammoth Redetermination Administrative Burden Overwhelms Traditional Solutions

    One of the main impediments to states efficiently managing the post-PHE environment is the antiquated eligibility systems and processes. The most vulnerable people often don’t have regular encounters with a healthcare provider who can update basic patient information. If people move, get a new job, lose a job, or otherwise have changes to demographic and insurance information, MCOs and state agencies may have no way to reach them to redetermine eligibility.

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    Common strategies that states and MCOs use to deal with these looming challenges include:

    • Adopt more effective and efficient use of data
    • Improve account transfer data quality
    • Expand capacities and capabilities of online portals

    Yet, these “table stakes” approaches to redetermination are insufficient to effectively tackle the size and complexity of the post-PHE challenge. According to Juli Smith, Director at ZOLL® Data Systems, “Third-party data partners can be invaluable for enhancing demographic data, as well as for better understanding the behavioral and financial background of enrollees, as it pertains to their healthcare. The burden of redetermination as we unwind the PHE will profoundly impact states and MCOs. We recommend taking advantage of Medicaid redetermination solutions to reduce the risk of terminating vulnerable adults and children who are actually eligible.”

    Data-as-a-Service Solutions Can Improve Demographic Data on 55% or More Patient Encounters

    While states already have some data on Medicaid patients, it is often outdated and contains inaccurate information. The best data-as-a-service solutions can access multiple data sources in real time to find, verify, and correct patient information. For example, automated demographic redetermination, retroactive Medicaid, and Medicaid eligibility tools can help ensure continuous coverage for eligible individuals in compliance with the Centers for Medicare and Medicaid Services (CMS) redetermination requirements. Self-pay and propensity-to-pay tools, coordination-of-benefits technologies, and technologies that facilitate stronger patient engagement can ease the pain of transition for patients who are terminated from Medicaid and must find other options.

    Smith suggests exploring data solutions that can deliver improvements in core demographic contact information for at least 55% of encounters. She cautions that all data sources are not equal, and that confidence scoring is a must-have if states are to avoid acting on inaccurate information.

    During a recent webinar, Smith dove into the data to examine pre-pandemic enrollment patterns and discussed what the data trends reveal about best practices for Medicaid redetermination. To learn more about how to leverage data to reduce the potential risks to the most vulnerable Americans and ease the administrative burden of Medicaid redetermination, watch the webinar: “Unwinding the PHE: What We Can Learn from Pre-Pandemic Enrollment Patterns and How Data Informs Our Redetermination Efforts.”

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