An individual’s health status affects Medicaid enrollment (the ill are more likely to enroll). Medicaid enrollment affects an individual’s health status too (one can argue about which way, for the better or worse). The two are simultaneous. That makes inferring the causal effect of Medicaid on health outcomes difficult.
A few weeks ago I described the right way to tease out the causal effect of Medicaid enrollment on health outcomes:
There are undoubtedly studies that consider Medicaid vs. uninsured outcomes using the random variations provided by the natural experiment that is Medicaid. Characteristics of the program vary by state and year, making it a perfect set-up for such an analysis of this issue. [...]
[I] will [...] describe the relevant literature as I read the papers. I’m not going to filter or cherry pick papers based on their findings. All that matters to me is the quality of the methods applied. Feel free to send me links to papers you think qualify (look for peer-reviewed, natural or randomized experiments and/or instrumental variables approaches; the run-of-the-mill observational study that controls for observable individual characteristics won’t do). [...] When I think I’ve summarized them all, I’ll post a conclusion that reports on the full body of evidence.
To date, readers have sent me zero papers. But I’ve found six on my own, the one summarized below being the last. In a post later this week I’ll sum up all that I’ve found.
I’ve already summarized two 1996 papers by Currie and Gruber. They wrote a third, a 1997 NBER working paper titled “The Technology of Birth: Health Insurance, Medical Interventions, and Infant Health.” The techniques are similar to those of their other papers so you can click back to read about them. I’ll just cut right to the results. From the abstract:
[U]sing Vital Statistics data on every birth in the U.S. over the 1987-1992 period [we study t]he effects of insurance status on treatment and outcomes [...] identified using the tremendous variation in eligibility for public insurance coverage under the Medicaid program over this period. Among teen mothers and high school dropouts, who were largely uninsured before being made eligible for Medicaid, eligibility for this program was associated with significant increases in the use of a variety of obstetric procedures. On average, this more intensive treatment was associated with only marginal changes in the health of infants, as measured by neonatal mortality. But the effect of eligibility on neonatal mortality is sizeable among children born to mothers whose closest hospital had a Neonatal Intensive Care Unit, suggesting that insurance-induced increases in use of `high tech’ treatments can have real effects on outcomes. Among women with more education there is a counter- vailing effect on procedure use. Most of these women had private insurance before becoming Medicaid-eligible, and some may have been ‘crowded out’ onto the public program. These women moved from more generous to less generous insurance coverage of pregnancy and neonatal care. This movement was accompanied by reductions in procedure use without any discernable change in neonatal mortality.
A shorter and cruder summary is that Medicaid increases utilization of high-tech interventions, relative to being uninsured, and this has measurable health effects. However, relative to private insurance, Medicaid reduces the use of high-tech procedures and has no effect on health.