"The opening deal"

I liked this quote from economist Karthik Muralidharan, which is pulled from a conversation at Ideas for India with Kaushik Basu of the World Bank:

My own take on what is happening in economics as a profession, talking to people in other disciplines, is that our fundamental weakness at some level is that because the touchstone of policy evaluation is the idea of a Pareto improvement (is someone better off and no one worse off) - effectively, economists do not question the justice of the initial positions. You kind of take the initial position as granted and say that conditional on this, how do I improve things on the margin.

Given vast inequalities in the opening deal of cards, so to speak, there is obviously a deep political need to create the space for more pro-poor policy. I think because the professional economists have abdicated that space to saying that it is a philosophical debate and we have really nothing to say, the rights-based movement that has created the political space for pro-poor policy has also then occupied the space of how to design it because they are the people who have created the political movement.

My own view on this is that because economists have kind of been seen as apologists for the status quo in many settings, we have lost the credibility to say that we are as pro-poor as you are, but conditional on these objectives there are much better ways to design it.

Lots on poverty policy, inequality, etc at the link.

Formalizing corruption: US medical system edition

Oh, corruption. It interferes with so many aspects of daily life, adding time to the simplest daily tasks, costing more money, and -- often the most frustrating aspect -- adding huge doses of uncertainty. That describes life in many low-income, high-corruption countries, leading to many a conversation with friends about comparisons with the United States and other wealthy countries. How did the US "solve" corruption? I've heard (and personally made) the argument that the US reduced corruption at least in part by formalizing it; by channeling the root of corruption, a sort of rent-seeking on a personal level, to rent-seeking on an institutional level. The US political and economic system has evolved such that some share of any wealth created is channeled into the pockets of a political and economic elite who benefit from the system and in turn reinforce it. That unproductively-channeled share of wealth is simultaneously a) probably smaller than the share of wealth lost to corruption in most developing countries, b) still large enough to head off -- along with the threat of more effective prosecution -- at least some more overt corruption, and c) still a major drain on society.

An example: Elisabeth Rosenthal profiles medical tourism in an impressive series in the New York Times. In part three of the series, an American named Michael Shopenn travels to Belgium to get a hip replacement. Why would he need to? Because health economics in the US is less a story of free markets and  more a story of political capture by medical interests, including technology and pharmaceutical companies, physicians' groups, and hospitals:

Generic or foreign-made joint implants have been kept out of the United States by trade policy, patents and an expensive Food and Drug Administration approval process that deters start-ups from entering the market. The “companies defend this turf ferociously,” said Dr. Peter M. Cram, a physician at the University of Iowa medical school who studies the costs of health care.

Though the five companies make similar models, each cultivates intense brand loyalty through financial ties to surgeons and the use of a different tool kit and operating system for the installation of its products; orthopedists typically stay with the system they learned on. The thousands of hospitals and clinics that purchase implants try to bargain for deep discounts from manufacturers, but they have limited leverage since each buys a relatively small quantity from any one company.

In addition, device makers typically require doctors’ groups and hospitals to sign nondisclosure agreements about prices, which means institutions do not know what their competitors are paying. This secrecy erodes bargaining power and has allowed a small industry of profit-taking middlemen to flourish: joint implant purchasing consultants, implant billing companies, joint brokers. There are as many as 13 layers of vendors between the physician and the patient for a hip replacement, according to Kate Willhite, a former executive director of the Manitowoc Surgery Center in Wisconsin.

If this system existed in another country we wouldn't hesitate to call it corrupt, and to note that it actively hurts consumers. It should be broken up by legislation for the public good, but instead it's protected by legislators who are lobbied by the industry and by doctors who receive kickbacks, implicit and explicit. Contrast that with the Belgian system:

His joint implant and surgery in Belgium were priced according to a different logic. Like many other countries, Belgium oversees major medical purchases, approving dozens of different types of implants from a selection of manufacturers, and determining the allowed wholesale price for each of them, for example. That price, which is published, currently averages about $3,000, depending on the model, and can be marked up by about $180 per implant. (The Belgian hospital paid about $4,000 for Mr. Shopenn’s high-end Zimmer implant at a time when American hospitals were paying an average of over $8,000 for the same model.)

“The manufacturers do not have the right to sell an implant at a higher rate,” said Philip Boussauw, director of human resources and administration at St. Rembert’s, the hospital where Mr. Shopenn had his surgery. Nonetheless, he said, there was “a lot of competition” among American joint manufacturers to work with Belgian hospitals. “I’m sure they are making money,” he added.

It's become a cliche to compare the US medical system to European ones, but those comparisons are made because it's hard to realize just how systematically corrupt -- and expensive, as a result -- the US system is without comparing it to ones that do a better job of channeling the natural profit-seeking goals of individuals and companies towards the public good. (For the history of how we got here, Paul Starr is a good place to start.)

The usual counterargument for protecting such large profit margins in the US is that they drive innovation, which is true but only to an extent. And for the implants industry that argument is much less compelling since many of the newer, "innovative" products have proved somewhere between no better and much worse in objective tests.

The Times piece is definitely worth a read. While I generally prefer the formalized corruption to the unformalized version, I'll probably share this article with friends -- in Nigeria, or Ethiopia, or wherever else the subject comes up next.

Advocates and scientists

A new book by The Idealist: Jeffrey Sachs and the Quest to End Poverty. The blurbs on Amazon are fascinating because they indicate that either the reviewers didn't actually read the book (which wouldn't be all that surprising) or that Munk's book paints a nuanced enough picture that readers can come away with very different views on what it actually proves. Here are two examples:

Amartya Sen: “Nina Munk’s book is an excellent – and moving – tribute to the vision and commitment of Jeffrey Sachs, as well as an enlightening account of how much can be achieved by reasoned determination.”

Robert Calderisi: "A powerful exposé of hubris run amok, drawing on touching accounts of real-life heroes fighting poverty on the front line."

The publisher's description seems to encompass both of those points of view: "The Idealist is the profound and moving story of what happens when the abstract theories of a brilliant, driven man meet the reality of human life." That sounds like a good read to me -- I look forward to reading when it comes out in September.

Munk's previous reporting strikes a similar tone. For example, here's an excerpt of her 2007 Vanity Fair profile of Sachs:

Leaving the region of Dertu, sitting in the back of an ancient Land Rover, I'm reminded of a meeting I had with Simon Bland, head of Britain's Department for International Development in Kenya. Referring to the Millennium Villages Project, and to Sachs in particular, Bland laid it out for me in plain terms: "I want to say, 'What concept are you trying to prove?' Because I know that if you spend enough money on each person in a village you will change their lives. If you put in enough resources—enough foreigners, technical assistance, and money—lives change. We know that. I've been doing it for years. I've lived and worked on and managed [development] projects.

"The problem is," he added, "when you walk away, what happens?"

Someone -- I think it was Chris Blattman, but I can't find the specific post -- wondered a while back whether too much attention has been given to the Millennium Villages Project. After all, the line of thinking goes, the MVP's have really just gotten more press and aren't that different from the many other projects with even less rigorous evaluation designs. That's certainly true: when journalists and aid bloggers debate the MVPs, part of what they're debating is Sachs himself because he's such a polarizing personality. If you really care about aid policy, and the uses of evidence in that policy, then that can all feel like an unhelpful distraction. Most aid efforts don't get book-length profiles, and the interest in Sachs' personality and persona will probably drive the interest in Munk's book.

But I also think the MVP debates have been healthy and interesting -- and ultimately deserving of most of the heat generated -- because they're about a central tension within aid and development, as well as other fields where research intersects with activism. If you think we already generally know what to do, then it makes sense to push forward with it at all costs. The naysayers who doubt you are unhelpful skeptics who are on some level ethically culpable for blocking good work. If you think the evidence is not yet in, then it makes more sense to function more like a scientist, collecting the evidence needed to make good decisions in the longer term. The naysayers opposing the scientists are then utopian advocates who throw millions at unproven projects. I've seen a similar tension within the field of public health, between those who see themselves primarily as advocates and those who see themselves as scientists, and I'm sure it exists elsewhere as well.

That is, of course, a caricature -- few people fall completely on one side of the advocates vs. scientists divide. But I think the caricature is a useful one for framing arguments. The fundamental disagreement is usually not about whether evidence should be used to inform efforts to end poverty or improve health or advance any other goal. Instead, the disagreement is often over what the current state of knowledge is. And on that note, if you harbor any doubts on where Sachs has positioned himself on that spectrum here's the beginning of Munk's 2007 profile:

In the respected opinion of Jeffrey David Sachs.... the problem of extreme poverty can be solved. In fact, the problem can be solved "easily." "We have enough on the planet to make sure, easily, that people aren't dying of their poverty. That's the basic truth," he tells me firmly, without a doubt.

...To Sachs, the end of poverty justifies the means. By hook or by crook, relentlessly, he has done more than anyone else to move the issue of global poverty into the mainstream—to force the developed world to consider his utopian thesis: with enough focus, enough determination, and, especially, enough money, extreme poverty can finally be eradicated.

Once, when I asked what kept him going at this frenzied pace, he snapped back, "If you haven't noticed, people are dying. It's an emergency."

----

via Gabriel Demombynes.

If you're new to the Millennium Villages debate, here's some background reading: a recent piece in Foreign Policy by Paul Starobin, and some good posts by Chris Blattman (one, two, three), this gem from Owen Barder, and Michael Clemens.

"Redefining global health delivery"

Jim Yong Kim, Paul Farmer, and Michael Porter wrote a piece called "Redefining global health delivery" for the Lancet in May. The abstract:

Initiatives to address the unmet needs of those facing both poverty and serious illness have expanded significantly over the past decade. But many of them are designed in an ad-hoc manner to address one health problem among many; they are too rarely assessed; best practices spread slowly. When assessments of delivery do occur, they are often narrow studies of the cost-effectiveness of a single intervention rather than the complex set of them required todeliver value to patients and their families. We propose a framework for global health-care delivery and evaluation by considering efforts to introduce HIV/AIDS care to resource-poor settings. The framework introduces the notion of care delivery value chains that apply a systems-level analysis to the complex processes and interventions that must occur, across a health-care system and over time, to deliver high-value care for patients with HIV/AIDS and cooccurring conditions, from tuberculosis to malnutrition. To deliver value, vertical or stand-alone projects must be integrated into shared delivery infrastructure so that personnel and facilities are used wisely and economies of scale reaped. Two other integrative processes are necessary for delivering and assessing value in global health: one is the alignment of delivery with local context by incorporating knowledge of both barriers to good outcomes (from poor nutrition to a lack of water and sanitation) and broader social and economic determinants of health and wellbeing (jobs, housing, physical infrastructure). The second is the use of effective investments in care delivery to promote equitable economic development, especially for those struggling against poverty and high burdens of disease. We close by reporting our own shared experience of seeking to move towards a science of delivery by harnessing research and training to understand and improve care delivery.

I think the overall thrust of the piece is something that is widely agreed upon by global health policy wonks, but I like that they lay out a more specific framework for thinking with this sort of systems approach. But, I'd love to see some more detail on putting it into practice on a national or subnational level.

Someone should study this: Addis housing edition

Attention development economists and any other researchers who have an interest in urban or housing policy in low-income countries: My office in Addis has about 25 folks working in it, and we have a daily lunch pool where we pay in 400 birr a month (about 22 USD) to cover costs and all get to eat Ethiopian food for lunch every day. It's been a great way to get to know my coworkers -- my work is often more solitary: editing, writing, and analyzing data -- and an even better way to learn about a whole variety of issues in Ethiopia.

addis construction

The conversation is typically in Amharic and mine is quite limited, so I'm lucky if I can figure out the topic being discussed.  [I usually know if they're talking about work because so many NGO-speak words aren't translated, for example: "amharic amharic amharic Health Systems Strengthening amharic amharic..."] But folks will of course translate things as needed.  One observation is that certain topics affect their daily lives a lot, and thus come up over and over again at lunch.

One subject that has come up repeatedly is housing. Middle class folks in Addis Ababa feel the housing shortage very acutely. Based on our conversations it seems the major limitation is in getting credit to buy or build a house.

The biggest source of good housing so far has been government-constructed condominiums, for which you pay a certain (I'm not sure how much) percentage down and then make payments over the years. (The government will soon launch a new "40/60 scheme" to which many folks are looking forward, in which anyone who can make a 40% down payment on a house will get a government mortgage for the remaining 60%.)

When my coworkers first mentioned that the government will offer the next round of condominiums by a public lottery, my thought was "that will solve someone's identification problem!" A large number of people -- many thousands -- have registered for the government lottery. I believe you have to meet a certain wealth or income threshold (i.e., be able to make the down payment), but after that condo eligibility will be determined randomly. I think that -- especially if someone organizes the study prior to the lottery -- this could yield very useful results on the impact of urban housing policy.

How (and how much) do individuals and families benefit from access to better housing? Are there changes in earnings, savings, investments? Health outcomes? Children's health and educational outcomes? How does it affect political attitudes or other life choices? It could also be an opportunity to study migration between different neighborhoods, amongst many other things.

A Google Scholar search for Ethiopia housing lottery turns up several mentions, but (in my very quick read) no evaluations taking advantage of the randomization. (I can't access this recent article in an engineering journal, but from the abstract assume that it's talking about a different kind of evaluation.) So, someone have at it? It's just not that often that large public policy schemes are randomized.

Still #1

Pop quiz: what's the leading killer of children under five? Before I answer, some background: my impression is that many if not most public health students and professionals don't really get politics. And specifically, they don't get how an issue being unsexy or just boring politics can results in lousy public policy. I was discussing this shortcoming recently over dinner in Addis with someone who used to work in public health but wasn't formally trained in it. I observed, and they concurred, that students who go to public health schools (or at least Hopkins, where this shortcoming may be more pronounced) are mostly there to get technical training so that they can work within the public health industry, and that more politically astute students probably go for some other sort of graduate training, rather than concentrating on epidemiology or the like.

The end result is that you get cadres of folks with lots of knowledge about relative disease burden and how to implement disease control programs, but who don't really get why that knowledge isn't acted upon. On the other hand, a lot of the more politically savvy folks who are in a position to, say, set the relative priority of diseases in global health programming -- may not know much about the diseases themselves. Or, maybe more likely, they do the best job they can to get the most money possible for programs that are both good for public health and politically popular.  But if not all diseases are equally "popular" this can result in skewed policy priorities.

Now, the answer to that pop quiz: the leading killer of kids under 5 is.... [drumroll]...  pneumonia!

If you already knew the answer to that question, I bet you either a) have public health training, or b) learned it due to recent, concerted efforts to raise pneumonia's public profile. On this blog the former is probably true (after all I have a post category called "methodological quibbles"), but today I want to highlight the latter efforts.

To date, most of the political class and policymakers get the pop quiz wrong, and badly so. At Hopkins' school of public health I took and enjoyed Orin Levine's vaccine policy class. (Incidentally, Orin just started a new gig with the Gates Foundation -- congrats!) In that class and elsewhere I've heard Orin tell the story of quizzing folks on Capitol Hill and elsewhere in DC about the top three causes of death for children under five and time and again getting the answer "AIDS, TB and malaria."

Those three diseases likely pop to mind because of the Global Fund, and because a lot of US funding for global health has been directed at them. And, to be fair, they're huge public health problems and the metric of under-five mortality isn't where AIDS hits hardest. But the real answer is pneumonia, diarrhea, and malnutrition. (Or malaria for #3 -- it depends in part on whether you count malnutrition as a separate cause  or a contributor to other causes). The end result of this lack of awareness -- and the prior lack of a domestic lobby -- of pneumonia is that it gets underfunded in US global health efforts.

So, how to improve pneumonia's profile? Today, November 12th, is the 4th annual World Pneumonia Day, and I think that's a great start. I'm not normally one to celebrate every national or international "Day" for some causes, but for the aforementioned reasons I think this one is extremely important. You can follow the #WPD2012 hashtag on Twitter, or find other ways to participate on WPD's act page. While they do encourage donations to the GAVI Alliance, you'll notice that most of the actions are centered around raising awareness. I think that makes a lot of sense. In fact, just by reading this blog post you've already participated -- though of course I hope you'll do more.

I think politically-savvy efforts like World Pneumonia Day are especially important because they bridge a gap between the technical and policy experts. Precisely because so many people on both sides (the somewhat-false-but-still-helpful dichotomy of public health technical experts vs. political operatives) mostly interact with like-minded folks, we badly need campaigns like this to popularize simple facts within policy circles.

If your reaction to this post -- and to another day dedicated to a good cause -- is to feel a bit jaded, please recognize that you and your friends are exactly the sorts of people the World Pneumonia Day organizers are hoping to reach. At the very least, mention pneumonia today on Twitter or Facebook, or with your policy friends the next time health comes up.

---

Full disclosure: while at Hopkins I did a (very small) bit of paid work for IVAC, one of the WPD organizers, re: social media strategies for World Pneumonia Day, but I'm no longer formally involved. 

Obesity pessimism

I posted before on the massive increase in obesity in the US over the last couple decades, trying to understand the why of the phenomenal change for the worse. Seriously, take another look at those maps. A while back Matt Steinglass wrote a depressing piece in The Economist on the likelihood of the US turning this trend around:

I very much doubt America is going to do anything, as a matter of public health policy, that has any appreciable effect on obesity rates in the next couple of decades. It's not that it's impossible for governments to hold down obesity; France, which had rapidly rising childhood obesity early this century, instituted an aggressive set of public-health interventions including school-based food and exercise shifts, nurse assessments of overweight kids, visits to families where overweight kids were identified, and so forth. Their childhood obesity rates stabilised at a fraction of America's. The problem isn't that it's not possible; rather, it's that America is incapable of doing it.

America's national governing ideology is based almost entirely on the assertion of negative rights, with a few exceptions for positive rights and public goods such as universal elementary education, national defence and highways. But it's become increasingly clear over the past decade that the country simply doesn't have the political vocabulary that would allow it to institute effective national programmes to improve eating and exercise habits or culture. A country that can't think of a vision of public life beyond freedom of individual choice, including the individual choice to watch TV and eat a Big Mac, is not going to be able to craft public policies that encourage people to exercise and eat right. We're the fattest country on earth because that's what our political philosophy leads to. We ought to incorporate that into the way we see ourselves; it's certainly the way other countries see us.

On the other hand, it's notable that states where the public has a somewhat broader conception of the public interest, as in the north-east and west, tend to have lower obesity rates.

This reminds me that a classmate asked me a while back about my impression of Michelle Obama's Let's Move campaign. I responded that my impression is positive, and that every little bit helps... but that the scale of the problem is so vast that I find it hard seeing any real, measurable impact from a program like Let's Move. To really turn obesity around we'd need a major rethinking of huge swathes of social and political reality: our massive subsidization of unhealthy foods over healthy ones (through a number of indirect mechanisms), our massive subsidization of unhealthy lifestyles by supporting cars and suburbanization rather than walking and urban density, and so on and so forth. And, as Steinglass notes, the places with the greatest obesity rates are the least likely to implement such change.

Bad pharma

Ben Goldacre, author of the truly excellent Bad Science, has a new book coming out in January, titled Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients Goldacre published the foreword to the book on his blog here. The point of the book is summed up in one powerful (if long) paragraph. He says this (emphasis added):

So to be clear, this whole book is about meticulously defending every assertion in the paragraph that follows.

Drugs are tested by the people who manufacture them, in poorly designed trials, on hopelessly small numbers of weird, unrepresentative patients, and analysed using techniques which are flawed by design, in such a way that they exaggerate the benefits of treatments. Unsurprisingly, these trials tend to produce results that favour the manufacturer. When trials throw up results that companies don’t like, they are perfectly entitled to hide them from doctors and patients, so we only ever see a distorted picture of any drug’s true effects. Regulators see most of the trial data, but only from early on in its life, and even then they don’t give this data to doctors or patients, or even to other parts of government. This distorted evidence is then communicated and applied in a distorted fashion. In their forty years of practice after leaving medical school, doctors hear about what works through ad hoc oral traditions, from sales reps, colleagues or journals. But those colleagues can be in the pay of drug companies – often undisclosed – and the journals are too. And so are the patient groups. And finally, academic papers, which everyone thinks of as objective, are often covertly planned and written by people who work directly for the companies, without disclosure. Sometimes whole academic journals are even owned outright by one drug company. Aside from all this, for several of the most important and enduring problems in medicine, we have no idea what the best treatment is, because it’s not in anyone’s financial interest to conduct any trials at all. These are ongoing problems, and although people have claimed to fix many of them, for the most part, they have failed; so all these problems persist, but worse than ever, because now people can pretend that everything is fine after all.

If that's not compelling enough already, here's a TED talk on the subject of the new book:

Why we should lie about the weather (and maybe more)

Nate Silver (who else?) has written a great piece on weather prediction -- "The Weatherman is Not a Moron" (NYT) -- that covers both the proliferation of data in weather forecasting, and why the quantity of data alone isn't enough. What intrigued me though was a section at the end about how to communicate the inevitable uncertainty in forecasts:

...Unfortunately, this cautious message can be undercut by private-sector forecasters. Catering to the demands of viewers can mean intentionally running the risk of making forecasts less accurate. For many years, the Weather Channel avoided forecasting an exact 50 percent chance of rain, which might seem wishy-washy to consumers. Instead, it rounded up to 60 or down to 40. In what may be the worst-kept secret in the business, numerous commercial weather forecasts are also biased toward forecasting more precipitation than will actually occur. (In the business, this is known as the wet bias.) For years, when the Weather Channel said there was a 20 percent chance of rain, it actually rained only about 5 percent of the time.

People don’t mind when a forecaster predicts rain and it turns out to be a nice day. But if it rains when it isn’t supposed to, they curse the weatherman for ruining their picnic. “If the forecast was objective, if it has zero bias in precipitation,” Bruce Rose, a former vice president for the Weather Channel, said, “we’d probably be in trouble.”

My thought when reading this was that there are actually two different reasons why you might want to systematically adjust reported percentages ((ie, fib a bit) when trying to communicate the likelihood of bad weather.

But first, an aside on what public health folks typically talk about when they talk about communicating uncertainty: I've heard a lot (in classes, in blogs, and in Bad Science, for example) about reporting absolute risks rather than relative risks, and about avoiding other ways of communicating risks that generally mislead. What people don't usually discuss is whether the point estimates themselves should ever be adjusted; rather, we concentrate on how to best communicate whatever the actual values are.

Now, back to weather. The first reason you might want to adjust the reported probability of rain is that people are rain averse: they care more strongly about getting rained on when it wasn't predicted than vice versa. It may be perfectly reasonable for people to feel this way, and so why not cater to their desires? This is the reason described in the excerpt from Silver's article above.

Another way to describe this bias is that most people would prefer to minimize Type II Error (false negatives) at the expense of having more Type I error (false positives), at least when it comes to rain. Obviously you could take this too far -- reporting rain every single day would completely eliminate Type II error, but it would also make forecasts worthless. Likewise, with big events like hurricanes the costs of Type I errors (wholesale evacuations, cancelled conventions, etc) become much greater, so this adjustment would be more problematic as the cost of false positives increases. But generally speaking, the so-called "wet bias" of adjusting all rain prediction probabilities upwards might be a good way to increase the general satisfaction of a rain-averse general public.

The second reason one might want to adjust the reported probability of rain -- or some other event -- is that people are generally bad at understanding probabilities. Luckily though, people tend to be bad about estimating probabilities in surprisingly systematic ways! Kahneman's excellent (if too long) book Thinking, Fast and Slow covers this at length. The best summary of these biases that I could find through a quick Google search was from Lee Merkhofer Consulting:

 Studies show that people make systematic errors when estimating how likely uncertain events are. As shown in [the graph below], likely outcomes (above 40%) are typically estimated to be less probable than they really are. And, outcomes that are quite unlikely are typically estimated to be more probable than they are. Furthermore, people often behave as if extremely unlikely, but still possible outcomes have no chance whatsoever of occurring.

The graph from that link is a helpful if somewhat stylized visualization of the same biases:

In other words, people think that likely events (in the 30-99% range) are less likely to occur than they are in reality, that unlike events (in the 1-30% range) are more likely to occur than they are in reality, and extremely unlikely events (very close to 0%) won't happen at all.

My recollection is that these biases can be a bit different depending on whether the predicted event is bad (getting hit by lightning) or good (winning the lottery), and that the familiarity of the event also plays a role. Regardless, with something like weather, where most events are within the realm of lived experience and most of the probabilities lie within a reasonable range, the average bias could probably be measured pretty reliably.

So what do we do with this knowledge? Think about it this way: we want to increase the accuracy of communication, but there are two different points in the communications process where you can measure accuracy. You can care about how accurately the information is communicated from the source, or how well the information is received. If you care about the latter, and you know that people have systematic and thus predictable biases in perceiving the probability that something will happen, why not adjust the numbers you communicate so that the message -- as received by the audience -- is accurate?

Now, some made up numbers: Let's say the real chance of rain is 60%, as predicted by the best computer models. You might adjust that up to 70% if that's the reported risk that makes people perceive a 60% objective probability (again, see the graph above). You might then adjust that percentage up to 80% to account for rain aversion/wet bias.

Here I think it's important to distinguish between technical and popular communication channels: if you're sharing raw data about the weather or talking to a group of meteorologists or epidemiologists then you might take one approach, whereas another approach makes sense for communicating with a lay public. For folks who just tune in to the evening news to get tomorrow's weather forecast, you want the message they receive to be as close to reality as possible. If you insist on reporting the 'real' numbers, you actually draw your audience further from understanding reality than if you fudged them a bit.

The major and obvious downside to this approach is that people know this is happening, it won't work, or they'll be mad that you lied -- even though you were only lying to better communicate the truth! One possible way of getting around this is to describe the numbers as something other than percentages; using some made-up index that sounds enough like it to convince the layperson, while also being open to detailed examination by those who are interested.

For instance, we all the heat index and wind chill aren't the same as temperature, but rather represent just how hot or cold the weather actually feels. Likewise, we could report some like "Rain Risk" or "Rain Risk Index" that accounts for known biases in risk perception and rain aversion. The weather man would report a Rain Risk of 80%, while the actual probability of rain is just 60%. This would give us more useful information for the recipients, while also maintaining technical honesty and some level of transparency.

I care a lot more about health than about the weather, but I think predicting rain is a useful device for talking about the same issues of probability perception in health for several reasons. First off, the probabilities in rain forecasting are much more within the realm of human experience than the rare probabilities that come up so often in epidemiology. Secondly, the ethical stakes feel a bit lower when writing about lying about the weather rather than, say, suggesting physicians should systematically mislead their patients, even if the crucial and ultimate aim of the adjustment is to better inform them.

I'm not saying we should walk back all the progress we've made in terms of letting patients and physicians make decisions together, rather than the latter withholding information and paternalistically making decisions for patients based on the physician's preferences rather than the patient's. (That would be silly in part because physicians share their patients' biases.) The idea here is to come up with better measures of uncertainty -- call it adjusted risk or risk indexes or weighted probabilities or whatever -- that help us bypass humans' systematic flaws in understanding uncertainty.

In short: maybe we should lie to better tell the truth. But be honest about it.

When randomization is strategic

Here's a quote from Tom Yates on his blog Sick Populations about a speech he heard by Rachel Glennerster of J-PAL:

Glennerster pointed out that the evaluation of PROGRESA, a conditional cash transfer programme in Mexico and perhaps the most famous example of randomised evaluation in social policy, was instigated by a Government who knew they were going to lose the next election. It was a way to safeguard their programme. They knew the next Government would find it hard to stop the trial once it was started and were confident the evaluation would show benefit, again making it hard for the next Government to drop the programme. Randomisation can be politically advantageous.

I think I read this about Progresa / Oportunidades before but had forgotten it, and thus it's worth re-sharing. The way in which Progresa was randomized (different areas were stepped into the program, so there was a cohort of folks who got it later than others, but all the high need areas got it within a few years) made this more politically feasible as well. I think this situation, in which a government institutes a study of a program to keep it alive through subsequent changes of government, will probably be a less common tactic than its opposite, in which a government designs an evaluation of a popular program that a) it thinks doesn't work, b) it wants to cut, and c) the public otherwise likes, just to prove that it should be cut -- but only time will tell.

Aid, paternalism, and skepticism

Bill Easterly, the ex-blogger who just can't stop, writes about a conversation he had with GiveWell, a charity reviewer/giving guide that relies heavily on rigorous evidence to pick programs to invest in. I've been meaning to write about GiveWell's approach -- which I generally think is excellent. Easterly, of course, is an aid skeptic in general and a critic of planned, technocratic solutions in particular. Here's an excerpt from his notes on his conversation with GiveWell:

...a lot of things that people think will benefit poor people (such as improved cookstoves to reduce indoor smoke, deworming drugs, bed nets and water purification tablets) {are things} that poor people are unwilling to buy for even a few pennies. The philanthropy community’s answer to this is “we have to give them away for free because otherwise the take-up rates will drop.” The philosophy behind this is that poor people are irrational. That could be the right answer, but I think that we should do more research on the topic. Another explanation is that the people do know what they’re doing and that they rationally do not want what aid givers are offering. This is a message that people in the aid world are not getting.

Later, in the full transcript, he adds this:

We should try harder to figure out why people don’t buy health goods, instead of jumping to the conclusion that they are irrational.

Also:

It's easy to catch people doing irrational things. But it's remarkable how fast and unconsciously people get things right, solving really complex problems at lightning speed.

I'm with Easterly, up to a point: aid and development institutions need much better feedback loops, but are unlikely to develop them for reasons rooted in their nature and funding. The examples of bad aid he cites are often horrendous. But I think this critique is limited, especially on health, where the RCTs and all other sorts of evidence really do show that we can have massive impact -- reducing suffering and death on an epic scale -- with known interventions. [Also, a caution: the notes above are just notes and may have been worded differently if they were a polished, final product -- but I think they're still revealing.]

Elsewhere Easterly has been more positive about the likelihood of benefits from health aid/programs in particular, so I find it quite curious that his examples above of things that poor people don't always price rationally are all health-related. Instead, in the excerpts above he falls back on that great foundational argument of economists: if people are rational, why have all this top-down institutional interference? Well, I couldn't help contrasting that argument with this quote highlighted by another economist, Tyler Cowen, at Marginal Revolution:

Just half of those given a prescription to prevent heart disease actually adhere to refilling their medications, researchers find in the Journal of American Medicine. That lack of compliance, they estimate, results in 113,00 deaths annually.

Let that sink in for a moment. Residents of a wealthy country, the United States, do something very, very stupid. All of the RCTs show that taking these medicines will make them live longer, but people fail to overcome the barriers at hand to take something that is proven to make them live longer. As a consequence they die by the hundreds of thousands every single year. Humans may make remarkably fast unconscious decisions correctly in some spheres, sure, but it's hard to look at this result and see any way in which it makes much sense.

Now think about inserting Easterly's argument against paternalism (he doesn't specifically call it that here, but has done so elsewhere) in philanthropy here: if people in the US really want to live, why don't they take these medicines? Who are we to say they're irrational? That's one answer, but maybe we don't understand their preferences and should avoid top-down solutions until we have more research.

reductio ad absurdum? Maybe. On the one hand, we do need more research on many things, including medication up-take in high- and low-income countries. On the other hand, aid skepticism that goes far enough to be against proven health interventions just because people don't always value those interventions rationally seems to line up a good deal with the sort of anti-paternalism-above-all streak in conservatism that opposes government intervention in pretty much every area. Maybe it's a good policy to try out some nudge-y (libertarian paternalism, if you will) policies to encourage people to take their medicine, or require people to have health insurance they would not choose to buy on their own.

Do you want to live longer? I bet you do, and it's safe to assume that people in low-income countries do as well. Do you always do exactly what will help you do so? Of course not: observe the obesity pandemic. Do poor people really want to suffer from worms or have their children die from diarrhea? Again, of course not. While poor people in low-income countries aren't always willing to invest a lot of time or pay a lot of money for things that would clearly help them stay alive for longer, that shouldn't be surprising to us. Why? Because the exact same thing is true of rich people in wealthy countries.

People everywhere -- rich and poor -- make dumb decisions all the time, often because those decisions are easier in the moment due to our many irrational cognitive and behavioral tics. Those seemingly dumb decisions usually reveal the non-optimal decision-making environments in which we live, but you still think we could overcome those things to choose interventions that are very clearly beneficial. But we don't always. The result is that sometimes people in low-income countries might not pay out of pocket for deworming medicine or bednets, and sometimes people in high-income countries don't take their medicine -- these are different sides of the same coin.

Now, to a more general discussion of aid skepticism: I agree with Easterly (in the same post) that aid skeptics are a "feature of the system" that ultimately make it more robust. But it's an iterative process that is often frustrating in the moment for those who are implementing or advocating for specific programs (in my case, health) because we see the skeptics as going too far. I'm probably one of the more skeptical implementers out there -- I think the majority of aid programs probably do more harm than good, and chose to work in health in part because I think that is less true in this sector than in others. I like to think that I apply just the right dose of skepticism to aid skepticism itself, wringing out a bit of cynicism to leave the practical core.

I also think that there are clear wins, supported by the evidence, especially in health, and thus that Easterly goes too far here. Why does he? Because his aid skepticism isn't simply pragmatic, but also rooted in an ideological opposition to all top-down programs. That's a nice way to put it, one that I think he might even agree with. But ultimately that leads to a place where you end up lumping things together that are not the same, and I'll argue that that does some harm. Here are two examples of aid, both more or less from Easterly's post:

  • Giving away medicines or bednets free, because otherwise people don't choose to invest in them; and,
  • A World Bank project in Uganda that "ended up burning down farmers’ homes and crops and driving the farmers off the land."

These are a both, in one sense, paternalistic, top-down programs, because they are based on the assumption that sometimes people don't choose to do what is best for themselves. But are they the same otherwise? I'd argue no. One might argue that they come from the same place, and an institution that funds the first will inevitably mess up and do the latter -- but I don't buy that strong form of aid skepticism. And being able to lump the apparently good program and the obviously bad together is what makes Easterly's rhetorical stance powerful.

If you so desire, you could label these two approaches as weak coercion and strong coercion. They are both coercive in the sense that they reshape the situations in which people live to help achieve an outcome that someone -- a planner, if you will -- has decided is better. All philanthropy and much public policy is coercive in this sense, and those who are ideologically opposed to it have a hard time seeing the difference. But to many of us, it's really only the latter, obvious harm that we dislike, whereas free medicines don't seem all that bad. I think that's why aid skeptics like Easterly group these two together, because they know we'll be repulsed by the strong form. But when they argue that all these policies are ultimately the same because they ignore people's preferences (as demonstrated by their willingness to pay for health goods, for example), the argument doesn't sit right with a broader audience. And then ultimately it gets ignored, because these things only really look the same if you look at them through certain ideological lenses.

That's why I wish Easterly would take a more pragmatic approach to aid skepticism; such a form might harp on the truly coercive aspects without lumping them in with the mildly paternalistic. Condemning the truly bad things is very necessary, and folks "on the inside' of the aid-industrial complex aren't generally well-positioned to make those arguments publicly. However, I think people sometimes need a bit of the latter policies, the mildly paternalistic ones like giving away medicines and nudging people's behavior -- in high- and low-income countries alike. Why? Because we're generally the same everywhere, doing what's easiest in a given situation rather than what we might choose were the circumstances different. Having skeptics on the outside where they can rail against wrongs is incredibly important, but they must also be careful to yell at the right things lest they be ignored altogether by those who don't share their ideological priors.

Our future selves will mock this (I hope)

Smiling people holding hands. Walking on the beach. Inexplicable doves flying through blue skies. Terrible side effects discussed cheerily by a honey-voiced narrator.... That's right, this post is about direct-to-consumer pharmaceutical advertising. Niam Hardimh, writing at Crooked Timber, shares one of the odd things about living in the US -- for those who aren't used to our TV:

One thing that is striking, compared with European TV, is what is advertised and how. In particular,  I don’t think you see ads for prescription medicines in Europe, certainly not in Ireland or the UK. They seem to be all over American TV.

I am particularly struck by the way these ads are made. The visuals  typically show someone having a happy and trouble-free life while using these drugs, overlaid with soothing music and a reassuringly bland voice-over. But clearly the US FDA requires advertisers to include all the small print in their ads as well.

Do you read all the known downsides of the medicines you take? Don’t...

It's easy to become habituated to these since they're everywhere, but it hasn't always been that way, and in most places it still isn't -- the US and New Zealand are the only two countries that allow direct advertising of drugs. Here's an exemplary ad for Vioxx, which was pulled off the market because it caused health problems (which Merck systematically lied about):

Ice skating. A minor celebrity. Inspiring music. They even note that "Vioxx specifically targets the Cox2 enzyme." How many Americans can even define what an enzyme is? I'm sure consumers are more likely to remember that than the mentioned side effects ("bleeding can occur without warning")... Other lovely examples include this other ad for Vioxx, and one for Zocor.

For more examples and some background on how the ads came to be, check out "Sick of pharmaceutical ads: here's why they won't go away" on io9.

Obesity in the US

One of my classmates whose primary interest is not health policy posted this graph on Facebook, saying "This is stunning... so much so in fact that I'm a bit skeptical of its accuracy." The graph compares obesity rates by state in 1994 vs. 2008, and unfortunately it is both terrifying and accurate. (I can't find the original source of this particular infographic, but the data is the same as on this CDC page.)

I think those of who study or work in public health have seen variations on these graphs so many times that they've lost some of their shock value. But this truly is an incredible shift in population health in a frighteningly short period of time. In 1994 every state had an adult population that was less than 20% obese, and many were less than 15% obese. A mere 14 years later, Colorado is the only state under 20%, and quite a few have rates over 30% -- these were completely unheard of before.

I did a quick literature search, trying to understand what causal factors might be responsible for such a rapid shift. It's a huge and challenging question, so maybe it should be unsurprising that I didn't find an article that really stood out as the best. Still, here are three articles that I found helpful:

1. Specifically looking at childhood obesity in the US (which is different from the rates highlighted in the map above, but related): "Childhood Obesity: Trends and Potential Causes" by Anderson and Butcher (JStor PDF, ungated PDF). Their intro:

The increase in childhood obesity over the past several decades, together with the associated health problems and costs, is raising grave concern among health care professionals, policy experts, children's advocates, and parents. Patricia Anderson and Kristin Butcher document trends in children's obesity and examine the possible underlying causes of the obesity epidemic.

They begin by reviewing research on energy intake, energy expenditure, and "energy balance," noting that children who eat more "empty calories" and expend fewer calories through physical activity are more likely to be obese than other children. Next they ask what has changed in children's environment over the past three decades to upset this energy balance equation. In particular, they examine changes in the food market, in the built environment, in schools and child care settings, and in the role of parents-paying attention to the timing of these changes.

Among the changes that affect children'se nergy intake are the increasing availability of energy dense, high-calorie foods and drinkst hroughs chools. Changes in the family, particularly increasing dual-career or single-parent working families, may also have increased demand for food away from home or pre-prepared foods. A host of factors have also contributed to reductions in energy expenditure. In particular, children today seem less likely to walk to school and to be traveling more in cars than they were during the early 1970s, perhaps because of changes in the built environment. Finally, children spend more time viewing television and using computers.

Anderson and Butcher find no one factor that has led to increases in children's obesity. Rather, many complementary changes have simultaneously increased children's energy intake and decreased their energy expenditure. The challenge in formulating policies to address children's obesity is to learn how best to change the environment that affects children's energy balance.

2. On global trends: "The global obesity pandemic: shaped by global drivers and local environments" by Swinburn et al. (Here's the PDF from Science Direct and an ungated PDF for those not at universities.) Summary:

The simultaneous increases in obesity in almost all countries seem to be driven mainly by changes in the global food system, which is producing more processed, affordable, and effectively marketed food than ever before. This passive overconsumption of energy leading to obesity is a predictable outcome of market economies predicated on consumption-based growth. The global food system drivers interact with local environmental factors to create a wide variation in obesity prevalence between populations.

Within populations, the interactions between environmental and individual factors, including genetic makeup, explain variability in body size between individuals. However, even with this individual variation, the epidemic has predictable patterns in subpopulations. In low-income countries, obesity mostly affects middle-aged adults (especially women) from wealthy, urban environments; whereas in high-income countries it affects both sexes and all ages, but is disproportionately greater in disadvantaged groups.

Unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures. This absence increases the urgency for evidence-creating policy action, with a priority on reduction of the supply-side drivers.

3. Finally, on methodological differences and where the trends are heading: "Obesity Prevalence in the United States — Up, Down, or Sideways?" (NEJM, ungated PDF). Evidently there's some debate over whether rates are going up or have stabilized in the last few years, because different data sources say different things. Generally the NHANES data (in which people are actually measured, rather than reporting their height and weight) is the best available (and that's what the maps above are made from). An excerpt:

One key reason for discrepancies among the estimates is a simple difference in data-collection methods. The most frequently quoted data sources are the NHANES studies of adults and children, the BRFSS for adults, and the CDC's Youth Risk Behavior Survey (YRBS)4 for high- school students. Although sampling strategies, response rates, age discrepancies, and the wording of survey questions may account for some variability, a major factor is that in calculating the BMI, the BRFSS and YRBS rely on respondents' self-reported heights and weights, whereas the NHANES collects measured (i.e., actual) heights and weights each year, albeit from a considerably smaller sample of the population. Since people often claim to be taller than they are and to weigh less than they actually do, we should not be surprised that obesity prevalence figures based on self-reported heights and weights are considerably lower than those based on measured data.

I would greatly appreciate any suggestions for what to read in the comments, especially links to work that tries to rigorously assess (rather than just hypothesize on) the relative import of various drivers of the increase in adult obesity.

Group vs. individual uses of data

Andrew Gelman notes that, on the subject of value-added assessments of teachers, "a skeptical consensus seems to have arisen..." How did we get here? Value-added assessments grew out of the push for more emphasis on measuring success through standardized tests in education -- simply looking at test scores isn't OK because some teachers are teaching in better schools or are teaching better-prepared students. The solution was to look at how teachers' students improve in comparison to other teachers' students. Wikipedia has a fairly good summary here.

Back in February New York City released (over the opposition of teachers' unions) the value-added scores of some 18,000 teachers. Here's coverage from the Times on the release and reactions.

Gary Rubinstein, an education blogger, has done some analysis of the data contained in the reports and published five posts so far: part 1, part 2, part 3, part 4, and part 5. He writes:

For sure the 'reformers' have won a battle and have unfairly humiliated thousands of teachers who got inaccurate poor ratings. But I am optimistic that this will be be looked at as one of the turning points in this fight. Up until now, independent researchers like me were unable to support all our claims about how crude a tool value-added metrics still are, though they have been around for nearly 20 years. But with the release of the data, I have been able to test many of my suspicions about value-added.

I suggest reading his analysis in full, or at least the first two parts.

For me one early take-away from this -- building off comments from Gelman and others -- is that an assessment might be a useful tool for improving education quality overall, while simultaneously being a very poor metric for individual performance. When you're looking at 18,000 teachers you might be able to learn what factors lead to test score improvement on average, and use that information to improve policies for teacher education, recruitment, training, and retention. But that doesn't mean one can necessarily use the same data to make high-stakes decisions about individual teachers.

On food deserts

Gina Kolata, writing for the New York Times, has sparked some debate with this article: "Studies Question the Pairing of Food Deserts and Obesity". In general I often wish that science reporting focused more on how the new studies fit in with the old, rather than just the (exciting) new ones. On first reading I noticed that one study is described as having explored the association of "the type of food within a mile and a half of their homes" with what people eat. This raised a little question mark in my mind, as I know that prior studies have often looked at distances much shorter than 1.5 miles, but it was mostly a vague hesitation. And if you didn't know that before reading the article, then you've missed a major difference between the old and new results (and one that could have been easily explained). Also, describing something as "an article of faith" when it's arguably something more like "the broad conclusion draw from most most prior research"... that certainly established an editorial tone from the beginning.

Intrigued, I sent the piece to a friend (and former public health classmate) who has work on food deserts, to get a more informed reaction. I'm sharing her thoughts here (with permission) because this is an area of research that I don't follow as closely, and her reactions helped me to situate this story in the broader literature:

1. This quote from the article is so good!

"It is always easy to advocate for more grocery stores,” said Kelly D. Brownell, director of Yale University’s Rudd Center for Food Policy and Obesity, who was not involved in the studies. “But if you are looking for what you hope will change obesity, healthy food access is probably just wishful thinking.”

The "unhealthy food environment" has a much bigger impact on diet than the "healthy food environment", but it's politically more viable to work from an advocacy standpoint than a regulatory standpoint. (On that point, you still have to worry about what food is available - you can't just take out small businesses in impoverished neighborhoods and not replace it with anything.)

2. The article is too eager to dismiss the health-food access relationship. There's good research out there, but there's constant difficulty with tightening methods/definitions and deciding what to control for. The thing that I think is really powerful about the "food desert" discourse is that it opens doors to talk about race, poverty, community, culture, and more. At the end of the day, grocery stores are good for low-income areas because they bring in money and raise property values. If the literature isn't perfect on health effects, I'm still willing to advocate for them.

3. I want to know more about the geography of the study that found that low-income areas had more grocery stores than high-income areas. Were they a mix of urban, peri-urban, and rural areas? Because that's a whole other bear. (Non-shocker shocker: rural areas have food deserts... rural poverty is still a problem!)

4. The article does a good job of pointing to how difficult it is to study this. Hopkins (and the Baltimore Food Czar) are doing some work with healthy food access scores for neighborhoods. This would take into account how many healthy food options there are (supermarkets, farmers' markets, arabers, tiendas) and how many unhealthy food options there are (fast food, carry out, corner stores).

5. The studies they cite are with kids, but the relationship between food insecurity (which is different, but related to food access) and obesity is only well-established among women. (This, itself, is not talked about enough.) The thinking is that kids are often "shielded" from the effects of food insecurity by their mothers, who eat a yo-yo diet depending on the amount of food in the house.

My friend also suggested the following articles for additional reading:

Name that quote

I'm reading Evolving Economics, a highly-regarded history of economic thought by Agnar Sandmo. I thought one tidbit early on was quite interesting: it comes in the course of a discussion of a once-common method of charging tolls based on the weight of carriages. Sandmo quotes an economist who recommended different rates for luxury versus other transport.

Thus, "...the indolence and vanity of the rich is made to contribute in a very easy manner to the relief of the poor, by rendering cheaper the transportation of heavy goods to all the different parts of the country."

Who said that? Answer below the fold...

Adam Smith, the patron saint of laissez-faire economists everywhere, in The Wealth of Nations no less. Sandmo comments, "This formulation is notable both for its substantial content and for the tone of its language, which leaves one with no doubt as to the author's sympathy and social concerns."

Fluoride in New Jersey

I saw this poster at a bus stop on campus a couple weeks ago:

If you can't read it, the title reads: "Stop the New Jersey Public Water Supply Fluoridation Act" and it goes on to say "Fluoride is a toxic chemical even in the smallest doses and when pumped into our water supply it is impossible to control the level of consumption." (emphasis added)

I took a picture but didn't think about it again until I saw this article on Friday: "In New Jersey, a Battle Over a Fluoridation Bill, and the Facts" (NYT) by Kate Zernike. I appreciate that she calls the fearmongering what it is -- a conspiracy theory:

While 72 percent of Americans get their water from public systems that add fluoride, just 14 percent of New Jersey residents do, placing the state next to last... A bill in the Legislature would change that, requiring all public water systems in New Jersey to add fluoride to the supply. But while the proposal has won support from a host of medical groups, it has proved unusually politically charged.

Similar bills have failed in the state since 2005, under pressure from the public utilities lobby and municipalities that argue that fluoridation costs too much, environmentalists who say it pollutes the water supply, and antifluoride activists who argue that it causes cancer, lowers I.Q. and amounts to government-forced medicine.

Public health officials argue that the evidence does not support any of those arguments — and to the contrary, that fluoridating the water is the single best weapon in fighting tooth decay, the most prevalent disease among children.

But they also say they are fighting a proliferation of misleading information. While conspiracy theories about fluoride in public water supplies have circulated since the early days of the John Birch Society, they now thrive online, where anyone, with a little help from Google, can suddenly become a medical authority.

The whole article is worth a read. I think it's a pretty good journalistic take on a charged issue that is a political controversy but not a scientific one. It gives some context as to why people are against it -- a few misleading studies amplified by word of mouth and the Internet -- but also emphasizes which side the evidence base (overwhelmingly) backs up.

Further, there are some echoes here of the anti-vaccine movement,  in that a move to reduce the threshold of acceptable fluoride levels  by HHS was taken to be an acknowledgment that the worst fears of the fluoridation foes were vindicated. That parallels how any mention of efforts to improve vaccine safety (a good thing) is misshapen by antivaccine activists into an acknowledgment that their theories have been vindicated. In short, I'm looking forward to Seth Mnookin's take on all this.

The US health care non-system

I spent much of yesterday thinking about the past, present, and future of the American health care system. I've largely chosen classes with an international or methodological focus so this was a bit of a departure from my normal fare. In one day I finished up some readings on health reform, wrote a brief paper speculating on what US healthcare will look like in 2030, attended a talk by Uwe Reinhardt largely based on this paper (PDF), and went to a three hour lecture on US health care (part of a class on the economics of the US welfare state). It's a mammoth subject, and there are many bloggers who write exclusively about domestic health policy -- the guys at the Incidental Economist have smart stuff to say on it every day. There's so much to be said and done even on the somewhat narrowed subject of the Affordable Care Act (ie, "ObamaCare").

But that's not what keeps popping into my head.What keeps getting reinforced is how our system really isn't a system at all, but a weird conglomeration of lots of different approaches for various fragments of our society that emerged for quirky historical and political reasons. I found this description -- from a report comparing various industrialized countries' systems -- humorously understated: "The U.S. does not have a 'health system,' but rather a variety of private and public institutions and programs that regulate, finance, and deliver care." (source)

Paul Starr's classic Social Transformation of American Medicine is a good start for trying to understand how we got to the 'variety' we have today.  The end result is that it doesn't serve very many people well at all. The US is a great place to get the most advanced care if you can afford it, but even then you're going to pay a lot more for it. For the non-wealthy the expenses are amplified and we end up rationing care by ability to pay. By pretty much every standard other than innovation (ie, including the delivery of that innovation to those who really need it, not just those who can pay) the US falls dreadfully short. We get poor life expectancy, magnified inequalities, and spending that's roughly twice as much per person as in any other wealthy country.

Ironically, whether the Affordable Care Act goes into effect in 2014 depends largely on whether Obama gets reelected, and whether Obama gets reelected or not depends largely on what the unemployment rate does between now and November. So the future of the US health system depends in a very real way on fluctuations in the economy over the next eight months, and no one really understand that well at all.

If you're just looking at the trajectory of the American health system the ACA is a major reform, even a fundamental one.  It will do (and has already started to do) a lot of good things, but I'm skeptical that it will do all that much to fix costs or shift our focus to public health ---prevention over treatment. There are a lot of good small fixes in there, but nothing revolutionary when you compare us to other countries.

And this is why I find domestic health policy profoundly depressing. It's why I've chosen to focus more on international health than domestic politics. In international health I think the prospects for witnessing and contributing to massive, heartening, orders-of-magnitude positive change in my professional lifetime are quite real. On US health policy, I'm less optimistic. My friend and classmate Jesse Singal wrote a description of the US health system -- in the context of astonishingly ridiculous remarks by some conservatives on contraception -- that I think about sums it up:  "...our medical system is an octopus riding a donkey riding a skateboard into a sadness quarry."

Platform evaluation

Cesar Victora,  Bob Black,  Ties Boerma, and Jennifer Bryce (three of the four are with the Hopkins Department of International Health and I took a course with Prof Bryce) wrote this article in The Lancet in January 2011: "Measuring impact in the Millennium Development Goal era and beyond: a new approach to large-scale effectiveness evaluations." The abstract:

Evaluation of large-scale programmes and initiatives aimed at improvement of health in countries of low and middle income needs a new approach. Traditional designs, which compare areas with and without a given programme, are no longer relevant at a time when many programmes are being scaled up in virtually every district in the world. We propose an evolution in evaluation design, a national platform approach that: uses the district as the unit of design and analysis; is based on continuous monitoring of different levels of indicators; gathers additional data before, during, and after the period to be assessed by multiple methods; uses several analytical techniques to deal with various data gaps and biases; and includes interim and summative evaluation analyses. This new approach will promote country ownership, transparency, and donor coordination while providing a rigorous comparison of the cost-effectiveness of different scale-up approaches.