Ohio Department of Medicaid hosted webinars in November 2025 offering the most detailed picture yet of how any large state plans to operationalize Medicaid work requirements. Deputy Director Patrick Beatty walked through a framework built around a fundamental insight: with nearly 770,000 expansion adults, the state cannot process individual compliance determinations through human review. Whatever Ohio builds must be automated first and manual second, or it will not work at all. Ohio reached this conclusion during design of its 2019 Section 1115 waiver proposing community engagement requirements verified primarily through administrative data matching. That waiver was approved during the first Trump administration but never implemented because COVID-19 intervened and the Biden administration later withdrew approval. ODM submitted a new waiver application to CMS on February 28, 2025. Then the One Big Beautiful Bill Act signed July 4, 2025, established a nationwide requirement covering all nonexempt expansion adults ages 19 through 64, requiring 80 hours monthly, imposing semi-annual redeterminations, and setting a hard January 1, 2027 implementation deadline.
Population Decomposition and the 170,000 Question#
ODM’s analysis illustrates why automation is operational necessity. Roughly 43% of expansion adults are known to be working, identifiable through unemployment insurance wage data. An additional 18% meet medical frailty or disability definitions, verifiable through Social Security Administration records and claims data. When all identifiable exemptions are accounted for, roughly 17% can be confirmed exempt through existing data sources. That leaves approximately 22%, about 170,000 individuals, requiring additional assessment or documentation. Center for Community Solutions: those 170,000 are the ones who must show they’re meeting requirements or are exempt. They represent the zone where Ohio’s automation ends and human verification begins.
Urban Institute estimated more than 200,000 Ohioans could lose coverage. ODM’s estimate was more conservative at roughly 62,000. The gap reflects different assumptions about automation effectiveness in identifying exempt and compliant individuals, and how many of the 170,000 will successfully navigate documentation. The difference between 60% and 50% automation coverage is not statistical but the difference between a system serving most automatically and one overwhelming human infrastructure handling exceptions.
Data-First Architecture and County Administration#
Ohio’s verification establishes a hierarchy of automated checks before requesting member documentation. Unemployment insurance wage data comes first through quarterly reports from Ohio Department of Job and Family Services. SNAP work requirement compliance follows, as SNAP E&T participation, ABAWD compliance, or SNAP earnings above work requirement thresholds create deemed Medicaid compliance. Educational enrollment through community college systems and vocational training programs provides third verification layer. Workforce development participation through OhioMeansJobs centers and WIOA-funded training creates fourth layer. Social Security Administration data identifying SSI, SSDI, and Medicare beneficiaries triggers automatic disability exemptions. Claims data analysis identifying medical frailty through diagnosis codes, treatment patterns, and service utilization completes the automated stack. Only after these automated checks fail does the system request member documentation. This data-first principle distinguishes Ohio from systems that failed elsewhere. Arkansas required monthly portal reporting with minimal automated verification, creating barriers that caused 18,164 coverage losses among people who were working or exempt.
Ohio’s county-administered structure creates implementation complexity. Eighty-eight county departments of job and family services process Medicaid eligibility, each with different staffing levels and technological sophistication. What works in Cuyahoga County may not translate to Vinton County. Simultaneously, SNAP work requirements create convergence Ohio must manage carefully. The farm bill eliminated state authority to waive ABAWD time limits, meaning county offices must extend work verification to larger SNAP cohort while building Medicaid capacity. The 9.13% SNAP error rate looming over $300 million in potential penalties creates institutional pressure to prioritize accuracy over speed. There is potential synergy: members meeting SNAP requirements are automatically deemed compliant for Medicaid. But this depends on data systems communicating effectively across 88 county offices.
Geographic Context and Critical Unknowns#
Ohio’s 11.8 million residents include approximately 770,000 expansion adults, among the five largest populations nationally. Geographic diversity spans urban centers like Cleveland, Columbus, and Cincinnati alongside Appalachian counties in southeastern Ohio facing persistent poverty, limited employment options, and healthcare infrastructure fragility. Sixteen Ohio counties are designated Appalachian, sharing characteristics with Kentucky and West Virginia coalfield regions where work requirements confront structural employment scarcity. Significant Amish and Old Order Mennonite populations concentrated in Holmes, Wayne, Geauga, and Tuscarawas counties present unique documentation challenges, as many limit government system interaction and maintain cash-based economic practices leaving minimal database trails. Gig economy workers in urban areas generate income through platforms that unemployment insurance systems do not fully capture.
As of February 2026, several critical components depend on federal regulations CMS will not finalize until June 2026. How CMS defines serious medical condition and what documentation will be required remains unsettled. Whether Ohio’s original January 2026 implementation target gives way entirely to the federal January 2027 deadline depends on CMS negotiation outcomes. The sequence is compressed: federal guidance in June, state operational design in summer, county training in fall, and full implementation by January 2027 leaves margins for error that experienced administrators describe as thin.
The Bottom Line#
Ohio represents the most sophisticated attempt at automation-centered verification among large states. The state has analytical depth, administrative infrastructure, and institutional memory from its 2019 design process. What it has never had is opportunity to test whether theory works at scale with real populations facing real consequences. If Ohio with 770,000 expansion adults, sophisticated data systems, strong MCO infrastructure, and years of planning cannot achieve automation levels that prevent significant coverage losses, that signals fundamental challenges with work requirement implementation rather than state-specific execution failures. The arithmetic must hold: 43% working, 18% medically frail or disabled, 17% otherwise exempt, leaving 170,000 requiring assessment. Whether those 170,000 can navigate documentation successfully, and whether automation can identify most of the 780,000 who should not lose coverage, determines whether Ohio’s model succeeds or replicates Arkansas’s failures at four times the scale.