I’ve spoken to a number of people in the media today about the Oregon Medicaid study. On the whole, they asked excellent questions, and made me think about my own interpretation of the results. They also forced me to think about how I would be speaking about the study if the results had been amazing. Would I still “quibble” about power?
Here’s the thing. If they had shows statistically significant improvements in health outcomes, I’d be impressed. If they had shown statistically significant harms, I’d be concerned. Non-significance doesn’t tell us that much, especially if the study is underpowered.
But am I being fair? Consistent? Some have accused me of changing course. So I looked back at what I’d written previously, when I said “we could even start talking causality”. Here’s what I said:
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.
Not too long ago, ACA opponents were claiming that Medicaid was bad for health. Some even claimed it killed people. So I was eager to see if an RCT would find that. The initial results were positive and statistically significant. So I concluded:
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.
There is still no evidence that Medicaid is bad for health. But if anyone has moved the goalposts, it’s the people claiming that now Medicaid must prove it improves health, instead of just not harming people. I stand by everything I said before. I think I’ve been pretty consistent.
