GAO recommends changes to CMS data collection to improve oversight of special enrollment

A gap in federal data could allow people who have lost insurance due to nonpayment of premiums to sign up during ACA special enrollment periods.

In a recent report, the U.S. Government Accountability Office (GAO) revealed a gap in the records kept by the Centers for Medicare & Medicaid Services (CMS) regarding individuals who take advantage of the special enrollment periods offered for those who lose health coverage outside of the open enrollment period.

The special enrollment periods are permitted under federal law for individuals who lose their coverage from another source, but explicitly prohibit signups from patients whose coverage was terminated because they failed to pay their premiums.

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According to the report, CMS and insurance providers share data on terminations, but the agency collects that information in order to ensure the accuracy of federal subsidy amounts. For that reason, CMS does not require detailed information on why individuals lose their coverage, and its monthly reconciliation forms have no place to collect such data.

The GAO cited concerns among insurers that individuals abusing the system by signing up after failing to pay their premiums will contribute to instability in the exchanges. As the watchdog agency pointed out, the current lack of information makes it impossible even to judge the size of the problem.

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As a result of the report, the GAO issued a pair of recommendations:

  • CMS should change its data-collection processes so that it receives and tracks information on enrollee terminations to determine when they occur due to nonpayment of premiums.
  • CMS should expand the process by which it reconciles discrepancies in termination data with issuers so that it includes data regarding terminations for nonpayment of premiums.

The Department of Health and Human Services agreed with both recommendations, indicating it plans to "review its transactional data requirements" on nonpayment terminations and work with insurers to improve data collection.