Background: Maternal opioid use disorder (OUD) has serious consequences for maternal and infant health. Analysis of Medicaid enrollee data is critical, since Medicaid bears a disproportionate share of costs. Methods: This study analyzes linked maternal and infant Medicaid claims data and infant birth records in three states in the year before and after a delivery in 2014-2015 (2013-2016) examining health, health care use, treatment, and neonatal outcomes. Diagnosis and procedure codes identify OUD and other substance use disorders (SUDs). Results: In the year before and after delivery, 2.2 percent of the sample had an OUD diagnosis, and 5.9 percent had a SUD diagnosis other than OUD. Of the women with OUD, 72.8% had treatment for a SUD in the year before and after delivery, but most had none in an average enrolled month, and only 8.8% received any methadone treatment in a given month. Pregnant women with OUD had delayed and lower rates of prenatal care compared to women with other substance use disorders (SUDs). Infants of mothers with OUD did not differ from infants of mothers with other SUDs in rate of preterm or low birth weight but had higher NICU admission rates and longer birth hospitalizations. Health care costs for women with an OUD were higher than those with other SUDs. Conclusions: There is an urgent need for comprehensive, evidence-based OUD treatment integrated with maternity care. To fill critical gaps in care, workforce and infrastructure innovations can facilitate delivery of preventive and treatment services coordinated across settings.

Objective To synthesize evidence on the accuracy of Medicaid reporting across state and federal surveys. Data Sources All available validation studies. Study Design Compare results from existing research to understand variation in reporting across surveys. Data Collection Methods Synthesize all available studies validating survey reports of Medicaid coverage. Principal Findings Across all surveys, reporting some type of insurance coverage is better than reporting Medicaid specifically. Therefore, estimates of uninsurance are less biased than estimates of specific sources of coverage. The CPS stands out as being particularly inaccurate. Conclusions Measuring health insurance coverage is prone to some level of error, yet survey overstatements of uninsurance are modest in most surveys. Accounting for all forms of bias is complex. Researchers should consider adjusting estimates of Medicaid and uninsurance in surveys prone to high levels of misreporting.

Steep declines in the uninsured population under the Affordable Care Act (ACA) will depend on high enrollment among newly Medicaid-eligible adults. We use the 2009 American Community Survey to model pre-ACA eligibility for comprehensive Medicaid coverage among nonelderly adults. We identify 4.5 million eligible but uninsured adults. We find a Medicaid participation rate of 67% for adults; the rate is 17 percentage points lower than the national Medicaid participation rate for children, and it varies substantially across socioeconomic and demographic subgroups and across states. Achieving substantial increases in coverage under the ACA will require sharp increases in Medicaid participation among adults in some states.

The widely cited Census Bureau estimates of the number of uninsured people, based on the Current Population Survey, probably overstate the number of uninsured people. This is because of a Medicaid "undercount": Fewer people report to survey takers that they're covered by Medicaid than program administrative data show are enrolled. Our study finds that the undercount can be explained by the inability of people to recall their insurance status accurately from the previous year. We suggest that other data sources, such as Census's American Community Survey, should be studied to determine whether they would provide better estimates of the uninsured.