When Medicaid’s Data Can’t Verify Eligibility, Members Shouldn’t Lose Coverage

As states prepare to implement new Medicaid eligibility requirements under H.R. 1, much of the attention has focused on the administrative challenges ahead for states, health plans and members. New community engagement requirements and more frequent eligibility checks will add to an already complicated process. Automated data matching will help manage the workload, but it won’t work for everyone. What happens when the system can’t verify someone who is actually eligible? And how do we keep that person from losing coverage and the care they need?

The consequences extend beyond administrative efficiency. When verification fails and an eligible member loses coverage, treatment can be interrupted, medications can go unfilled and manageable conditions can become medical emergencies. Systems designed to verify eligibility must not inadvertently undermine continuity of care.

When the data don’t tell the whole story

Automated eligibility verification is certainly not new to Medicaid. States already use electronic data sources to confirm income, employment and other eligibility factors, often renewing coverage without requiring additional documentation. This reduces paperwork, lowers administrative costs and helps eligible members maintain coverage. But automated systems can only work with available information, which may be incomplete, inconsistent or outdated.

Consider someone who works irregular hours, changes employers or earns income through temporary jobs. Employment databases may not reflect current circumstances. A member experiencing housing instability may have an outdated address. Someone providing unpaid care for a family member may qualify for an exemption from community engagement requirements, but the information needed to establish that exemption may not be available electronically.

In each case, the member may be eligible even though the available data cannot establish eligibility. These aren’t necessarily failures of technology. They reflect the limitations of the information on which technology depends. The danger comes when an inability to verify eligibility becomes a pathway to losing coverage.

The Medicaid unwinding following the Covid-19 public health emergency demonstrated how administrative processes can disrupt coverage. According to ⁠KFF’s analysis of Medicaid renewal outcomes, more than 25 million people were disenrolled as states resumed eligibility redeterminations. Nearly seven in ten disenrollments were for procedural reasons, such as failure to complete renewal paperwork, rather than a determination of ineligibility. Not everyone who lost coverage was necessarily eligible to remain enrolled, but the scale of procedural disenrollments exposed how administrative requirements can become barriers to coverage.

H.R. 1 raises the stakes. No doubt. New community engagement requirements, which ⁠CMS requires states to implement by January 1, 2027, and more frequent eligibility checks will create additional opportunities for discrepancies between electronic records and members’ actual circumstances. Without effective safeguards, states risk repeating problems revealed during unwinding.

Continuity of care must be part of the equation

Coverage disruptions are often discussed in terms of enrollment numbers and administrative performance, but their consequences for healthcare delivery deserve equal attention. A member managing diabetes may miss appointments or lose access to medication. Someone receiving behavioral health treatment may experience an interruption in services. A member with multiple chronic conditions may lose access to clinicians coordinating care.

For plans, these disruptions can complicate care management and increase the risk of avoidable emergency department visits and hospitalizations. For providers, they can mean treating members whose conditions have deteriorated after routine care was interrupted. And for states, they can undermine Medicaid’s goals of improving health outcomes and using public resources effectively.

Build safeguards into the system

The answer, of course, isn’t to abandon automation. Electronic verification is essential to administering Medicaid efficiently, particularly as states face growing workloads and constrained resources. The answer is to recognize the difference between an unsuccessful data match and an ineligible member.

Existing ⁠CMS guidance on financial eligibility verification establishes important protections. When electronic information is insufficient, states generally must provide opportunities to submit additional documentation before terminating coverage. Under the new community engagement rules, members whose compliance cannot be verified must receive notice and 30 days to demonstrate compliance or an exemption.

But let’s face it: safeguards are only effective if members can use them. States should maximize reliable data sources before requesting additional information. A discrepancy in one database shouldn’t automatically trigger paperwork when another source can resolve it. When verification remains inconclusive, members need clear explanations of what’s missing, accessible ways to submit documentation and assistance resolving discrepancies.

States should also track unsuccessful data matches, how frequently those cases are resolved, procedural disenrollments and coverage interruptions. These measures can reveal whether administrative efficiencies are coming at the expense of continuity of care.

Medicaid’s new requirements will test states’ ability to administer a more demanding eligibility system. Automation will be indispensable, but success shouldn’t be measured solely by how quickly cases are processed. It should also be measured by what happens when the data are insufficient.

As states implement H.R. 1, protecting continuity of care must be part of the design, not an afterthought. The goal should be straightforward: Verify eligibility accurately, administer the program efficiently and ensure that members who qualify for Medicaid don’t lose access to care simply because the data couldn’t tell their whole story.

Photo: designer491, Getty Images

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