Oregon Health Study results, part 2

I’m jumping in here because I think it’s important to quote from the paper itself.  Austin has done a bang-up job of the describing the methods of the study, so I’m not going to refer you there. But I’d like to reiterate that this was a randomized controlled trial. An RCT is pretty much the best way to prove causality, especially if it’s well done. So if you wanted to prove that Medicaid causes bad outcomes (as many do), this would be the way to prove it. This is what they found with respect to health (emphasis mine):

Panel B analyzes seven different measures of self-reported health from the survey data. The first two use the question about self-reported health (fair, poor, good, very good, or excellent) to construct two binary measures: (1) self-reported health good, very good or excellent (55 percent of the population) and, (2) to examine “tail” behavior, self-reported health not poor (i.e. 86 percent of the population). The other measures are: (3) whether self-reported health status is about the same or gotten better over last six months (vs. gotten worse), (4) the number of days in good physical health in last month (0-30), (5) the number of days not impaired by physical or mental health in the last month (0-30), (6) the number of days in good mental health in the last month (0-30), and (7) whether the respondent screened negative for depression. Many of these measures capture both physical and mental health; the last two, however, capture only mental health.

The results in Panel B indicate that insurance is associated with statistically significant improvements in each of the seven measures. On average, our results suggest that health insurance is associated with a 0.2 standard deviation improvement in self-reported health (standard error = 0.04). This includes, among other things, an increase in the probability of screening negative for depression of 7.8 percentage points (standard error = 2.5) or about 10 percent relative to the control mean, and an increase in the probability of reporting one’s health as good, very good, or excellent of 13 percentage points (standard error = 2.6), or about 25 percent relative to the control mean.

And this doesn’t count the financial benefits (emphasis mine):

Table 8 reports results for four measures of financial strain: whether the respondent has any out-of-pocket medical expenditures in the last six months, whether the respondent currently owes money for medical expenses, whether the respondent had to borrow money (or skip paying other bills or pay them late) to pay medical expenses in the last six months, and whether the respondent has been refused medical treatment because of medical debt in the last six months. We find a statistically significant decline in all four survey measures of financial strain, including, for example, a 20 percentage point (35 percent) decline in the probability of having out of pocket expenses and a 15 percentage point (40 percent) decline in the probability of having to borrow money or skip paying other bills to pay medical expenses.  The average standardized treatment effect indicates that insurance is associated with a 0.3 standard deviation (standard error = 0.035) decline in these measures of financial strain.

Randomized controlled trials on this scale happen rarely. We’re still talking about the RAND health insurance experiment, which occurred decades ago. Here’s one that shows that Medicaid is both good for health and provides a significant financial benefit for it’s recipients. Since it’s an RCT, we can even start talking causality.

There’s no such studies or evidence showing the opposite, that Medicaid is bad for health. We’ll see if that talking point goes away.

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