The Incidental Economist

Temperature, Human Health, and Adaptation: A Review of the Empirical Literature, by Olivier Deschenes  (The National Bureau of Economic Research)

This paper presents a survey of the empirical literature studying the relationship between health outcomes, temperature, and adaptation to temperature extremes. The objective of the paper is to highlight the many remaining gaps in the empirical literature and to provide guidelines for improving the current Integrated Assessment Model (IAM) literature that seeks to incorporate human health and adaptation in its framework. I begin by presenting the conceptual and methodological issues associated with the measurement of the effect of temperature extremes on health, and the role of adaptation in possibly muting these effects. The main conclusion that emerges from the literature is that despite the wide variety of data sets and settings most studies find that temperature extremes lead to significant reductions in health, generally measured with excess mortality. Regarding the role of adaptation in mitigating the effects of extreme temperature on health, the available knowledge is limited, in part due to the lack of real-world data on measures of adaptation behaviors. Finally, the paper discusses the implications of the currently available evidence for assessments of potential human health impacts of global climate change.

Early Impact of the Affordable Care Act on Health Insurance Coverage of Young Adults, by Joel C. Cantor, Alan C. Monheit, Derek DeLia and Kristen Lloyd (Health Services Research)

Research Objective. To evaluate one of the first implemented provisions of the Patient Protection and Affordable Care Act (ACA), which permits young adults up to age 26 to enroll as dependents on a parent’s private health plan. Nearly one-in-three young adults lacked coverage before the ACA.

Study Design, Methods, and Data. Data from the Current Population Survey 2005–2011 are used to estimate linear probability models within a difference-in-differences framework to estimate how the ACA affected coverage of eligible young adults compared to slightly older adults. Multivariate models control for individual characteristics, economic trends, and prior state-dependent coverage laws.

Principal Findings. This ACA provision led to a rapid and substantial increase in the share of young adults with dependent coverage and a reduction in their uninsured rate in the early months of implementation. Models accounting for prior state dependent expansions suggest greater policy impact in 2010 among young adults who were also eligible under a state law.

Conclusions and Implications. ACA-dependent coverage expansion represents a rare public policy success in the effort to cover the uninsured. Still, this policy may have later unintended consequences for premiums for alternative forms of coverage and employer-offered rates for young adult workers.

Slowing Medicare Spending Growth: Reaching for Common Ground, by Michael E. Chernew, Richard G. Frank, and Stephen T. Parente (The American Journal of Managed Care)

The Overuse of Diagnostic Imaging and the Choosing Wisely Initiative, by Vijay M. Rao and David C. Levin (Annals of Internal Medicine)

Ethics of Commercial Screening Tests, by Erik A. Wallace, John H. Schumann and Steven E. Weinberger (Annals of Internal Medicine)

@afrakt

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Austin is out of town, I believe, so I’m taking it on myself to ARGH for him.

The NEJM has published a piece entitled, “What Business Are We In? The Emergence of Health as the Business of Health Care,” that’s getting a fair amount of press. It makes the argument that the health care industry should be more focused on the outcome people want – “health” – and less on the mechanism by which the industry currently tries to achieve that outcome.

However, this paragraph caught my eye (emphasis mine):

None of this evidence suggests that health care is not an important determinant of health or that it’s not among the most easily modifiable determinants. After all, we have established systems to support the writing of prescriptions and the performance of surgery or imaging but have found no easy way to cure poverty or relieve racial residential segregation. But the evidence does suggest that health care as conventionally delivered explains only a small amount — perhaps 10% — of premature deaths as compared with other factors, including social context, environmental influences, and personal behavior.4 If health care is only a small part of what determines health, perhaps organizations in the business of delivering health need to expand their offerings

NO! No, no no, no, no!

This factoid is commonly cited. But readers of the blog will know that Austin has thoroughly debunked it. He started here, when he followed up on the McGinnis study cited in the NEJM piece. It turned out that the “10%” number came from expert opinions. So Austin wrote:

Still, it seems to me there is no good reason to accept the 10% figure at the top of the left-hand side of the infographic. I’d like to know more how it got there. I’d like to hear the best argument as to why it’s correct.

Because Austin cares about, you know, facts, he followed up here. He found more citations that went nowhere, and “unpublished research”. He said:

It seems like folks want to say that 10% of our health is due to the health system (or access to it) without actually being able to point to anything substantial to back it up. Maybe my readers with super Google skills can track this down. I’m not saying there’s nothing to this 10% figure. I’m saying we shouldn’t have much confidence in it unless and until we can see the research that supports it. Where is it, and why didn’t the Bipartisan Policy Center track this down and cite a source that has some actual work behind it?

Excellent questions. Still, he wasn’t done, and wrote a piece at the AcademyHealth blog. You should go check it out. It was incredibly exhaustive, far more so than anything else I’ve seen. His conclusions:

There are other papers one could read on these topics, but this is all I had time for and/or could get in full text. From these, it looks like reasonable figures are 40% of reduction in cardiovascular mortality are due to medical care, while 66% or more of reductions in infant mortality are due to medical care. Therefore, I think Cutler’s ballpark of 50% of longevity due to medical care is reasonable.

When people want to discount the importance of access or minimize the problem of being uninsured, they say that it doesn’t matter anyway. They cite the 10% number to dismiss the actual value of getting health care. But it’s not true. Health care has much more value than that.

It’s not all that matters. Even at 50%, that means there’s lots of other stuff that affects mortality as well. But here at TIE we like to argue from evidence. The “fact” that only 10% of longevity gains are gue to health care is a zombie idea. It needs to die.

@aaronecarroll

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Judge Posner of the 7th Circuit Court of Appeals is the greatest living judge not on the Supreme Court. Generally considered a conservative, he isn’t afraid to attack error no matter the provenance. Take, for example, his recent review of a book by Justice Scalia and Bryan Garner. Posner eviscerates this book and its authors.  I agree with Brian Leiter, who says it would “finish the career” of any garden-variety academic author who wasn’t a Supreme Court Justice with life tenure. A sample, almost calling them out for academic fraud:

How many readers of Scalia and Garner’s massive tome will do what I have done—read the opinions cited in their footnotes and discover that in discussing the opinions they give distorted impressions of how judges actually interpret legal texts?

Posner’s review is titled The Incoherence of Antonin Scalia.  It appeared in The New Republic.  Judge Posner concludes:

Justice Scalia has called himself in print a “faint-hearted originalist.” It seems he means the adjective at least as sincerely as he means the noun.

What is going on here? Taking Judge Posner at face value, he is a conservative who is deeply troubled by the duplicity in Justice Scalia’s writings. The Court would be a dramatically different place if Posner had served there the last twenty six years.

@koutterson

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I finally finished the two good books I was reading. The first, Daniel Kahneman’s Thinking, Fast and Slow, has received extensive review and comment elsewhere. I don’t feel like adding a whole lot more to the discussion. My minor quibble: it was too long. But that’s true of most books, in my view. Still, you should read it.

I highlighted a lot of passages on my electronic copy. Here are two good ones from close to the end, both relevant to the current political and policy debate. (I’ll let you connect the dots.) The bold is mine.

First, on the price of freedom:

Freedom is not a contested value; all the participants in the debate are in favor of it. But life is more complex for behavioral economists than for true believers in human rationality. No behavioral economist favors a state that will force its citizens to eat a balanced diet and to watch only television programs that are good for the soul. For behavioral economists, however, freedom has a cost, which is borne by individuals who make bad choices, and by a society that feels obligated to help them. The decision of whether or not to protect individuals against their mistakes therefore presents a dilemma for behavioral economists. The economists of the Chicago school do not face that problem, because rational agents do not make mistakes. For adherence of this school, freedom is free of charge.

Next, on the value of organizations:

Organizations are better than individuals when it comes to avoiding errors, because they naturally think more slowly and have the power to impose orderly procedures. Organizations can institute and enforce the application of useful checklists, as well as more elaborate exercises, such as reference-class forecasting and the premortem. At least in part by providing a distinctive vocabulary, organizations can also encourage a culture in which people watch out for one another as they approach minefields. Whatever else it produces, an organization is a factory that manufactures judgments and decisions. Every factory must have ways to ensure the quality of its products in the initial design, in fabrication, and in final inspection. The corresponding stages in the production of decisions are the framing of the problem to be solved, the collection of relevant information leading to a decision, and reflection and review.

The other book I just completed is Michael Hochman’s 50 Studies Every Doctor Should Know: The Key Studies that Form the Foundation of Evidence Based Medicine. (See also the website 50studies.com.) This was very close to the book I want to read. If only it had interleaved chapters that explained the basics of the subject areas it covered (the basics of diabetes, the basics of cardiovascular disease, etc.) then it’d be perfect. And, in that case, it could be called “50 Studies that Every Health Services, Health Economics, and Health Policy Researcher or Wonk Should Know.”

You can still use the book in that capacity, but you have to do a lot of looking up of words and concepts yourself, some of which I did. I highly recommend it. Why don’t more social scientists and policy scholars (and journalists!) study the rudiments of evidence-based medicine? Why is this not considered required knowledge? Beats me. Seems like a huge oversight, one you can begin to correct by reading this book.

@afrakt

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How would President Obama and Mitt Romney each prefer to handle the tax treatment of health insurance premiums? Are their views different or the same? If you can’t answer those questions, check out my latest post on the JAMA blog in which I explain and then grade the candidates’ plans.

@afrakt

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I said I’d post this next week. I lied. Sorry. Here it is.

Two excellent sources on this question are the 2008 CBO report* and the 2009 paper by Smith, Newhouse, and Freeland. I made the following chart from the information in each, averaging the ranges of estimates they report.

Comments:

• None of the studies attribute any spending growth to increases in defensive medicine or supplier induced demand.
• Smith et al. (2009) doesn’t attribute any spending growth to changes in administrative costs.
• Smith et al. (2009) covers a time range about 20 years later than the other two studies.
• In all studies, technology is a large factor; only in Smith et al. (2009) does income growth dominate it. Does this reflect a shift over time in relative importance of causal factors or just differences in methodology?
• Income and technology interact. As wealth grows, so does the ability to afford more rapid technological change. Health care is now a large enough sector that its growth substantially helps fuel that of the wider economy.
• Health care spending can be decomposed into prices and quantities. Both play a role in encouraging or discouraging technology. All other things being equal, being able to charge (or be reimbursed) a high (or growing) price would encourage technology. Volume plays a role if there are economies of scale.

*Smith et al. (2000) and Cutler (1995) are cited in the CBO report. Follow the link for the full references.

@afrakt

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Sorry. I have to post this again:

I was watching the Republican convention last night, and I was struck by how every single person speaking claimed to have come from nothing. Do no politicians ever come from the middle or upper class? Everyone struggled, everyone had hard times. The Romney’s ate a lot of tuna and pasta, and had a desk that was a door on two sawhorses. Paul Ryan waited tables, washed dishes, and mowed lawns. You’d never know that both came from prominent families with many connections.

This struck me because I’m just as guilty of this practice. When my kids complain about not getting one thing or another, I often fall back on the old “I had it so much worse when I was a kid” routine. When my oldest complains about his friends going to Europe, I tell him how I didn’t even get on my first plane until I was in fifth grade. When my middle child complains about the temperature in the house, I tell him we didn’t even have central air when I was growing up. When my youngest complains about not having a TV in the car, I tell her about the unbelievable lemons my parents drove when I was a kid.

Yes, my children have it much better than I did when I was their age. My dad made a shockingly little amount of money as a resident and a fellow. But… come on. I went to private school for twelve years before spending an embarrassingly large amount of money on college and medical school. I lived in moderate to large houses in nice suburban neighborhoods. I didn’t drive a Mercedes when I turned 16, but we did have a vehicle that was considered “mine”.

I was never hungry. I never worried that the power might go off. I had an unlimited supply of books. And I had a safety net in the form of family that was inviolable.

It’s tempting to try and make every tale into a hard luck one. We all want to believe we came from meager beginnings to where we are today. It’s the American Dream. It’s a story that sells.

There sometimes seems to be a lack of perspective out there. We all like to think we built what we have from nothing without recognizing that “nothing” isn’t even in many of our vocabularies. I think of this when I write about doctors complaining about “making ends meet“. I think about this when I read stories about how people in Manhattan complain about living on half a million dollars. I think about this when I read stories of people making $200,000 complaining about how hard it is.

And I think about it – and feel guilty – when I see myself saying similar things to my children.

I think we’d all do better, myself included, if we recognized how good we actually had it. We’d be more honest if we recognized that being worse off is relative, and that there are many for whom “struggling” has actual meaning. I think we’d do better by the next generation by teaching them that safety nets – in all forms – have value, even if they only provide you the safety and love to give you the space to better yourself.

I also think that we would do better by paying the debt of that safety net forward instead of imagining that it’s making people complacent. It didn’t do that for us.

Some of us are as ambitious as we’d like to be. That’s not the same as being as ambitious as you have to be. There’s a difference.

UPDATE:

Guess I wasn’t the only one who felt this way:

@aaronecarroll

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The California Healthcare Foundation claims that the federal government spent half its revenue on health care in 2010. Is it true? Well, no.

The report says that in 2010, the federal government spent $742.7 billion on health care and that 34% (or $252.1 billion) of this was Medicare. Already I am skeptical of this number because I know from reading Trustees and CBO reports that Medicare spending is about $500 billion.

The report also says that when it counts government revenue, it excludes payments for social insurance. I guess that excludes payroll tax receipts for Social Security and Medicare. But that’s a lot of revenue, some of which is earmarked for health care.

Turning to a different source, usgovernmentrevenue.com, which compiles data from official government sources, I find that total federal health care spending in 2010 was $846.8 billion (Medicare at $457.8 billion) and revenue was $2,162.7 billion. Dividing, I find that the federal government spent 39% of its revenue on health care.

Just in case it isn’t clear, government revenue excludes debt. Either way you slice it, we’re financing a lot of what the government does with debt, and a huge amount is going to health care. Still, I find the claim that half of 2010 federal government revenue was spent on health care dubious. The facts are frightening enough. No need to cook the books* to make them seem more so.

* Perhaps there are good arguments for why CHF’s spending numbers seem too low and for excluding social insurance tax revenue from revenue, but I don’t know what those could be.

@afrakt

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The only time I had lunch with Jon Gruber he told me the biggest problem in policy debates is a lack of clear understanding of the counterfactual. Since then, I’ve been paying more attention, and he’s right that it is not well understood. Since I used the concept repeatedly in the comments on a post earlier today, I thought I should probably explain what I (and Gruber) mean.

When you want to know the causal effect of an intervention (policy change, medical treatment, whatever) on something, you need to compare two states of the world: the world in which the intervention occurred and the world in which it did not. The latter is the counterfactual world. Since most of us only get to live in one world (most of the time), observing the counterfactual is a rather tricky thing to do. Of course, there are various worthy techniques.

One technique that is usually pretty bad, but is probably the most common one people’s minds seem to turn to, is a comparison of the world after the intervention to the world before it, a pre-post analysis (with the “pre” serving as the counterfactual, a stand in for how the world would be in the absence of intervention). Quick, what would happen if we offered tax subsidies for cell phone purchases? The natural presumption is that cell phone sales would go up, and I am sure they would. But, they’re probably going up anyway. So a pre-post comparison of annual sales figures would not reveal the true effect of the policy. There’s an underlying trend that has to be accounted for.

What we really want to know is how the world is different due to the intervention and only the intervention. A randomized controlled (or experimental) design is the  gold standard approach. The assumption in that case is that, statistically, the two parts of the world (the treatment group and the control group — the counterfactual) are similar enough in all respects other than the intervention that comparing them gives you the true effect of the intervention. You’ve constructed a plausible counterfactual world. Good trick!

Sometimes we don’t have the luxury of an experimental design. In that case, we have to exploit something special about the world, like the intervention only occurred to people in this region but not that region and we can control for all the meaningful differences between the regions. Suffice it to say, this requires some assumptions (that you’ve controlled for all the meaningful differences), as do other approaches. Still, often this is the best we can do.

The most important point is that almost nobody is explicit about this in policy debates, even when the policy is crucially important. Will health reform cause employers to drop coverage or not? Well, we only have one world. The counterfactual needs to be constructed. It can’t simply be assumed to be the pre-reform world, because employers have been dropping coverage for years. There’s a trend. Other things may change (the economy, the nature of the labor market, etc.), so we’d want to control for those. And so forth.

This is worth thinking about. Next time you’re involved in a policy debate, ask your opponent, what (s)he is taking as the counterfactual? If (s)he doesn’t even know what you’re talking about, you’ve already won, even if (s)he won’t admit it.

@afrakt

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I want to add a quick note to Sarah Kliff’s coverage of Alex Wayne’s piece on the doctor shortage. Specifically this (emphasis mine):

Medical schools are holding back on further expansion because the number of applicants for residencies already exceeds the available positions, according to the National Resident Matching Program, a 60-year-old Washington-based nonprofit that oversees the program.

While it is true that the overall number of applicants exceeds the available positions, there are a number of things hidden in there worth noting.

First of all, this is less true in some specialties than others. If you’re going for a very competitive specialty (think dermatology), then yes, there are many more people than spots. But in less competitive specialties (think pediatrics), that’s not necessarily the case. And, yes, I’m a pediatrician.

Second, there are also sometimes fewer American applicants than there are positions. Many foreign-educated students apply for residency positions in the US, and get them. I’m not saying this is a bad thing, but we sometimes have fewer medical students in the US than you’d think, too.

Moreover, there are unfilled residency spots almost every year. That’s because while lots and lots of people may be willing to train in NYC, far fewer students may be willing to train in Indiana. And, yes, I live in Indiana. Complaining that we don’t have enough residency spots in the US when there are open slots available is like complaining you can’t go to college because you only applied to top tier schools and didn’t get in. There were 1100 unfilled first year residency slots in the US in 2012.

I actually still agree that we likely need to train more physicians, and will need more slots. But the issue is more nuanced than many think.

Actual data here: http://www.nrmp.org/data/resultsanddata2012.pdf

@aaronecarroll

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