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Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

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Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#181

Post by protomyth »

rdl wrote: post #173
beat wrote: post #152

Earlier quoted context omitted.

The problem with that is that the people with the highest medical costs (the elderly) are retired and no longer generating income to pay for their care. Gotta pay for that somehow. The whole point of insurance is to distribute costs.

The elderly (>65, or >62 in some cases, etc.) are already covered by medicare and social security. The disabled were covered by medicaid and ssi. Underemployed (part time, whatever) or sort-of-poor and not disabled people in their 50s are a major segment who can't pay the real cost of their medical care, though. Or, people with lifelong expensive illnesses in the 0-64 age range (who are often making a lot less money…

Medicare does a good job with hospital visits but has some serious holes in the drug buying.

Those in their 50's should have had some cash built up from earlier savings, but they spent it all on premiums instead of building up a hedge. Lifelong illnesses are something that we should just acknowledge as bad for insurance and deal with otherwise. Insurance should be for events and not continuous medical conditions.

We have not dealt with the price of medical care in a sane manner. I don't think the political will exists to break the current insurance scheme while at the same time not overreaching with government.

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#182

Post by coldcode »

brandonb wrote: post #115
djKianoosh wrote: post #98

Earlier quoted context omitted.

I'm curious how you're breaking down the work and if you only take full time devs or are bringing in hourly contractors for different pieces. Do you think you'd have better luck finding good devs if you broke it down like that?

So far, it's been on a rotation -- folks go on leave from their jobs for 1-3 months, move out to DC/Baltimore area, and work as hard as possible while they're here. :) It's such a high-intensity project that I think the we'll want to keep it to full-time for the time being. Otherwise, it's hard to even keep up, let alone make progress. (As a technical point, though, even though everybody is working on this for well o…

What technology knowledge are required?

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#183

Post by gizmo686 »

vwinsyee wrote: post #74
trhway wrote: post #67

Earlier quoted context omitted.

>mortality rate is significantly higher for uninsured than for insured. correlation doesn't mean causation. >to help make our government work better i somehow doubt that throwing a team of "rockstars" to clean up the mess is making the government to work better. If anything, it enables the typical government behavior we saw in the case of healthcare.gov.

> correlation doesn't mean causation. As a statistician, I guess I should be happy that more people are aware of this. But I also think too many people are taking "correlation != causation" superficially. I mean, almost all of science is based on significant correlational findings, especially when the traditional way to prove causation (i.e. via randomized trial) is unethical (i.e. we can't randomly assign people to…

All good points, but you also should consider the plausibility of it being a correlation. By this I mean that there seem to be clear candidates for a common cause between no insurance and high mortality, for example: income.

Once you control for this, and other potential common causes, your case for causality becomes much stronger (or non-existent).

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#184

Post by PhasmaFelis »

wooter wrote: post #41
brandonb wrote: post #38

I've been working on healthcare.gov for the last few months alongside a bunch of other Google, Facebook, and Y Combinator alums. I'll always remember what Mikey told us in December, after the site was back up, could handle a non-trivial amount of traffic, and people who wanted health insurance could finally get it: "1 in 1000 uninsured people die each year. It's not an exaggeration to say that due to the work we're d…

"1 in 1000 uninsured people die each year. It's not an exaggeration to say that due to the work we're doing here, 5,000-10,000 people will live to see the end of 2014. You should be proud of what you've done, but we should also all be grateful to have this opportunity." Hospitals don't let uninsured people die and insuring people doesn't magically save their lives.

> Hospitals don't let uninsured people die

Irrelevant, even if true. Uninsured people often don't go to the hospital until it's too late, because they know the expense will ruin them and they're hoping it will get better on its own.

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#185

Post by PhasmaFelis »

I'd really like to see a proper postmortem of the launch problems. Read about how it got fixed is nice, but I want a detailed account of how such an important project with the direct attention of the U.S. President managed to get fucked so absolutely.

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#186

Post by Fomite »

aamar wrote: post #96
brandonb wrote: post #38

I've been working on healthcare.gov for the last few months alongside a bunch of other Google, Facebook, and Y Combinator alums. I'll always remember what Mikey told us in December, after the site was back up, could handle a non-trivial amount of traffic, and people who wanted health insurance could finally get it: "1 in 1000 uninsured people die each year. It's not an exaggeration to say that due to the work we're d…

> "1 in 1000 uninsured people die each year. It's not an exaggeration to say that due to the work we're doing here, 5,000-10,000 people will live to see the end of 2014." This probably a significant exaggeration. It is based on a 2009 study[1] which examined correlation, not causation. It did not control for many factors that may be relevant (e.g. smoking). The study expressed this in much more careful words: "Lack o…

> It did not control for many factors that may be relevant (e.g. smoking).

From the abstract: "After additional adjustment for race/ethnicity, income, education, self- and physician-rated health status, body mass index, leisure exercise, smoking, and regular alcohol use"

> On the authors of the correlation study, who should never have studied this question without looking at extensive control variables or without more specifically studying causation?

How do you suggest studying causation in this setting? A randomized controlled trial where we deprive people of health insurance? Even that will likely not yield a true causal estimate, because randomization only helps for pre-randomization differences in the population, and behavior change from lacking health insurance will occur post randomization. The authors do extensively discuss their control variables, and important to remember is the fact that most papers only control for variables which ended up doing something, a subset of all variables that were tried. The NHANES data the study was pulled from includes a staggering number of covariates.

---

While not an ironclad study, I found the paper itself vastly more compelling than the politifact analysis of it, which boils down to "Well, observational studies might be wrong because reasons".

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#187

Post by Fomite »

slurry wrote: post #138
aamar wrote: post #96

Earlier quoted context omitted.

> "1 in 1000 uninsured people die each year. It's not an exaggeration to say that due to the work we're doing here, 5,000-10,000 people will live to see the end of 2014." This probably a significant exaggeration. It is based on a 2009 study[1] which examined correlation, not causation. It did not control for many factors that may be relevant (e.g. smoking). The study expressed this in much more careful words: "Lack o…

Why would you blame the study authors for doing a correlation study? I know "CORRELATION IS NOT CAUSATION!!!" is the go-to takedown on the internet, but correlation studies actually can have significant value - otherwise peer-reviewed journals wouldn't publish them. I'm also skeptical of Politifact's competence to adjudicate public health scholarship.

Not only do they have significant value, but they're the only type of evidence you'll ever have for something like this - it's impossible, and almost certainly unethical - to run a randomized trial of keeping people from having health insurance.

Also, while "Correlation is not causation" is, as you mentioned, a tired canard on the internet, people often seem to forget that all things that do have a causal relationship with have some form of association. Association doesn't prove causation, but it's a damned fine first step, and miles above "guessing", which is what happens without evidence.

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#188

Post by Fomite »

DanielRibeiro wrote: post #142
vwinsyee wrote: post #74

Earlier quoted context omitted.

> correlation doesn't mean causation. As a statistician, I guess I should be happy that more people are aware of this. But I also think too many people are taking "correlation != causation" superficially. I mean, almost all of science is based on significant correlational findings, especially when the traditional way to prove causation (i.e. via randomized trial) is unethical (i.e. we can't randomly assign people to…

Please turn this into a blog post and submit it to HN. I'd love to see this comment about correlations see more attention ;)

I just submitted this: https://news.ycombinator.com/item?id=7317254 which is the CrossValidated (StackOverflow for stats) discussion of whether or not causation implies correlation.

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#189

Post by Fomite »

gizmo686 wrote: post #183
vwinsyee wrote: post #74

Earlier quoted context omitted.

> correlation doesn't mean causation. As a statistician, I guess I should be happy that more people are aware of this. But I also think too many people are taking "correlation != causation" superficially. I mean, almost all of science is based on significant correlational findings, especially when the traditional way to prove causation (i.e. via randomized trial) is unethical (i.e. we can't randomly assign people to…

All good points, but you also should consider the plausibility of it being a correlation. By this I mean that there seem to be clear candidates for a common cause between no insurance and high mortality, for example: income. Once you control for this, and other potential common causes, your case for causality becomes much stronger (or non-existent).

If you had read the paper linked above, you'd note they controlled for income.

Re: Obama's Trauma Team: Inside the Nightmare Launch of HealthCare.Gov

#190

Post by ekianjo »

Fomite wrote: post #187
slurry wrote: post #138

Earlier quoted context omitted.

Why would you blame the study authors for doing a correlation study? I know "CORRELATION IS NOT CAUSATION!!!" is the go-to takedown on the internet, but correlation studies actually can have significant value - otherwise peer-reviewed journals wouldn't publish them. I'm also skeptical of Politifact's competence to adjudicate public health scholarship.

Not only do they have significant value, but they're the only type of evidence you'll ever have for something like this - it's impossible, and almost certainly unethical - to run a randomized trial of keeping people from having health insurance. Also, while "Correlation is not causation" is, as you mentioned, a tired canard on the internet, people often seem to forget that all things that do have a causal relationshi…

Sorry, but no. 100 times no. Correlation is very often linked to a third factor or multiple factors which are not visible, nor measured in observational studies. Besides, let's not disregard the fact that correlation still has some good chance to be pure luck. Even correlation with 95% confidence statistical significance can be a random result in a non-nil number of times.

So, no, you never prove anything nor imply anything at all with correlation. You're still guessing.

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