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Until the new regulations are enforced, Medicaid managed care remains the only major health insurance market that lacks nationally representative data on the share of insurer revenues allocated to medical care versus overhead and profits. By contrast, Medicaid managed care is not subject to these federal requirements, and only half of managed care states impose their own. The private insurance plans that administer coverage for the majority of Medicaid beneficiaries may undergo enhanced financial reporting as recent federal rules begin to be enforced. [Extracted from the article]

Objective: To re-evaluate the effect of Medicaid on poverty using a poverty measure that accounts for health insurance needs and benefits and an evaluation approach that reflects disparities in access to alternative coverage. Data Sources: The Current Population Survey (CPS) for calendar year 2015. Study Design: We estimate the effect of losing Medicaid on poverty, combining two previous approaches: (1) A propensity impact, which simulates a no-Medicaid counterfactual incorporating changes to health insurance and medical out-of-pocket spending, using the Supplemental Poverty Measure (SPM). This measure does not reflect a need for health care access nor how health benefits meet that need. (2) An accounting impact, which assumes that those losing Medicaid remain uninsured and does not incorporate any behavioral changes, using the health-inclusive poverty measure (HIPM). This measure includes a need for health insurance in the threshold and health insurance benefits in resources. Data Collection/Extraction Methods: Not applicable. Principal Findings: Using the propensity-matched approach, we attributed a 2.5 percentage point reduction in health-inclusive poverty among those younger than age 65 to the Medicaid program, between the 1.0-point SPM propensity-match impact and the 3.9-point HIPM accounting impact. Medicaid's antipoverty impact and HIPM-SPM differences are greater among those who would become uninsured. HIPM propensity-matched estimates reveal much larger impacts of Medicaid on poverty disparities linked to race/ethnicity and single parenthood than SPM-based propensity estimates. Conclusions: Both the poverty measure and the method used to estimate the counterfactual make substantial, policy-relevant differences to estimates of Medicaid's impact on poverty. A poverty measure that fails to incorporate health insurance needs and benefits substantially underestimates Medicaid's effect. Failing to consider adjustments in insurance coverage and out-of-pocket spending substantially overestimates Medicaid's effect and underestimates its reduction of disparities. [ABSTRACT FROM AUTHOR]