Published September 23, 2024 | Version v1
Journal article Open

Heterogeneous effects of Medicaid coverage on cardiovascular risk factors: Secondary analysis of randomized controlled trial

  • 1. Kyoto University
  • 2. Stanford University
  • 3. University of Chicago
  • 4. University of California, Los Angeles

Description

Objectives: To investigate whether health insurance generated improvements in cardiovascular risk factors (blood pressure and hemoglobin A1c (HbA1c) levels) for identifiable subpopulations, and using machine learning to identify characteristics of people predicted to benefit highly.

Design: Secondary analysis of randomized controlled trial.

Setting: Medicaid insurance coverage in 2008 for adults on low incomes (defined as lower than the federal-defined poverty line) in Oregon who were uninsured.

Participants: 12 134 participants from the Oregon Health Insurance Experiment with in-person data for health outcomes for both treatment and control groups.

Interventions: Health insurance (Medicaid) coverage.

Main outcomes measures: The conditional local average treatment effects of Medicaid coverage on systolic blood pressure and HbA1c using a machine learning causal forest algorithm (with instrumental variables). Characteristics of individuals with positive predicted benefits of Medicaid coverage based on the algorithm were compared with the characteristics of others. The effect of Medicaid coverage was calculated on blood pressure and HbA1c among individuals with high predicted benefits.

Results: In the in-person interview survey, mean systolic blood pressure was 119 (standard deviation 17) mm Hg and mean HbA1c concentrations was 5.3% (standard deviation 0.6%). Our causal forest model showed heterogeneity in the effect of Medicaid coverage on systolic blood pressure and HbA1c. Individuals with lower baseline healthcare charges, for example, had higher predicted benefits from gaining Medicaid coverage. Medicaid coverage significantly lowered systolic blood pressure (-4.96 mm Hg (95% confidence interval -7.80 to -2.48)) for people predicted to benefit highly. HbA1c was also significantly reduced by Medicaid coverage for people with high predicted benefits, but the size was not clinically meaningful (-0.12% (-0.25% to -0.01%)).

Conclusions: Although Medicaid coverage did not improve cardiovascular risk factors on average, substantial heterogeneity was noted in the effects within that population. Individuals with high predicted benefits were more likely to have no or low prior healthcare charges, for example. Our findings suggest that Medicaid coverage leads to improved cardiovascular risk factors for some, particularly for blood pressure, although those benefits may be diluted by individuals who did not experience benefits.

Data availability

All data used in this study are available online from the National Bureau of Economic Research's Public Use Data Archive and can be accessed at https://www.nber.org/research/data/oregon-health-insurance-experiment-data. Statistical code available from the corresponding author on reasonable request.

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Additional details

Identifiers

DOI
10.1136/bmj-2024-079377
Other
oai:uchicago.tind.io:13588

Funding

Japan Society for the Promotion of Science
22K17392
Japan Society for the Promotion of Science
23KK0240
Japan Science and Technology Agency
JPMJPR23R2
National Institutes of Health
P01AG005842
National Institutes of Health
R01AG034151
Annenberg Foundation
GRoW @ Annenberg

UChicago Information

Division(s)
Harris School of Public Policy Studies
Department(s)
Harris School of Public Policy Studies Research Publications