Fact check: What are the estimated costs of providing healthcare to undocumented immigrants under the Biden plan?

1. Why a national price tag is missing — federal rules and patchwork policy make aggregation hard

Federal law bars Medicaid from covering undocumented immigrants directly, so federal outlays under existing Medicaid rules are generally prohibited, which forces any expanded coverage under Biden-era proposals to rely on state actions, new federal legislation, or alternative program designs. This fragmentation means cost projections depend on policy choices—whether to use state-only funding, extend federal dollars via new statutes, or build Marketplace-like subsidies—so aggregate national estimates are absent from the sources provided ^{[1] [4]}. Modeling therefore centers on scenario analysis rather than a single authoritative estimate.

2. What state experiments reveal — California’s headline number and why it matters

California’s decision to expand state-funded Medi-Cal coverage to undocumented adults has been cited with an annual projected cost of about $8.4 billion, a concrete statewide forecast grounded in state budget modeling. That figure illustrates how state budgets, population size, and service generosity drive costs, and highlights that estimates scale strongly with the size of the undocumented population in a jurisdiction and whether long-term care benefits are included ^[1]. State figures are useful for extrapolation but risk misestimating national costs if applied without adjusting for demographic and policy variation.

3. Modeling tools give ballpark estimates but not policy certainty

Researchers developed web-based tools to estimate costs and enrollment outcomes for state-funded programs aimed at immigrants; these tools provide approximate ranges rather than precise budgets. Their creators stress the outputs are ballpark estimates sensitive to input assumptions like uptake rates, service utilization, and benefit design. Analysts using these tools recommend scenario testing—e.g., expanding coverage to children versus seniors—which yields very different fiscal impacts because seniors use more intensive, costly care ^{[3] [2]}.

4. Academic and health services literature documents major variation across states

Recent studies map state-level differences—some states use Emergency Medicaid, CHIP, or fully state-funded programs to cover certain immigrant groups—producing substantial coverage gaps and cost heterogeneity. Research shows expansions targeting children and young adults reduce uninsurance at relatively low marginal cost, while extending comprehensive benefits to older adults increases expenses mainly through long-term care and chronic disease management, explaining divergent cost outcomes across analyses ^{[5] [2]}.

5. Connecticut as a case study — targeted expansions can be affordable

RAND and state-focused analyses of Connecticut’s HUSKY program project that expanding Medicaid/CHIP to children and young adults would substantially cut uninsurance for noncitizens at relatively modest state cost, whereas extending benefits to seniors would materially raise spending due to long-term care needs. That pattern underlines the policy lever: who is covered matters as much as how coverage is structured, and state fiscal exposure grows when older, higher-utilization cohorts are included ^[2].

6. What the Biden plan debates leave unquantified in these sources

The assembled documents do not specify an exact Biden-plan national price tag; rather they outline policy options, state costs, and modeling tools that could be used to generate estimates under different designs. The sources show uncertainty around uptake, federal versus state funding shares, and whether long-term care is included, all of which prevent a single consolidated cost figure from emerging in the available analyses ^{[4] [6] [5]}.

7. Where the evidence converges and where it diverges

Across studies and tools there is agreement that targeted expansions (children, pregnant people, younger adults) yield larger coverage gains per dollar than blanket inclusion of older adults, and that state-level programs can be expensive in large states. Divergence stems from modeling assumptions, which populations are included, and benefit generosity; these choices produce widely different estimates, from relatively modest per-state budgets to multi-billion-dollar annual expenditures in populous states ^{[2] [1] [3]}.

8. Bottom line for policymakers and journalists seeking a headline figure

There is no single, defensible national estimate in the provided analyses; the best available approach is scenario-based modeling using state-level data and transparent assumptions, recognizing that California’s $8.4 billion state estimate provides one real-world benchmark while RAND-style state analyses show targeted expansions can be far less costly. For a credible national price tag, policymakers must define the covered populations and benefits, then apply state-by-state modeling tools to aggregate results under those specified assumptions ^{[1] [3] [2] [5]}.