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We use data on enrollment in the Supplemental Security Income (SSI) and Social Security Disability Insurance (SSDI) program and data on health care spending by Medicaid beneficiaries to analyze the extent to which Medicaid spending is predictive of future disability insurance receipt among non-disabled teenagers and future disability insurance disenrollment among disabled teenagers. In our first set of analyses, we find that we currently do not have enough data to predict future SSI and SSDI enrollment among non-disabled teenagers. In our second set of analyses, we find that observed Medicaid spending among disabled teenagers can be used to predict SSI disenrollment. Our results indicate that machine learning models using information on healthcare spending may be useful for identifying current teenage SSI recipients who are more or less likely to be removed from SSI.

∗ We thank Julia Yates and Elena Stacy for excellent research assistance. We gratefully acknowledge financial support from the Social Security Administration through grant DRC12000002-06 to the National Bureau of Economic Research as part of the SSA Disability Research Consortium, and the Agency for Healthcare Research and Quality (K01-HS25786-01). The findings and conclusions expressed are solely those of the authors and do not represent the opinions or policy of SSA, any agency of the Federal Government, or the National Bureau of Economic Research.† Harvard University and NBER. Email: layton@ hcp. med. harvard. edu‡ Harvard University. Email: liebert@ hcp. med. harvard. edu § Harvard University and NBER. Email: maestas@ hcp. med …