Great Harvard Med Class Show Parody

As an intern, I get to work side by side with Harvard medical students. I have to say that they have all been very, very good in terms of their clinical knowledge and ability to efficiently get things done. No wonder I got rejected when I applied.

It turns out that Harvard med students are pretty funny, too. Check out this great parody of medical students' experiences while on their third year clinical rotations by members of the Class of 2014. I'm sure you'll recognize the Saturday Night Live short this is based on. (HT: the awesome and hilarious Camila Fabersunne).

Male Circumcision, HIV/AIDS and the "Real World"

This past week, PLoS Medicine put forth multi-piece expose (start with this lead/summary article) on medical male circumcision, its cost-effectiveness in combating HIV/AIDS and methods and challenges to scaling up this practice in Sub-Saharan Africa, where the epidemic is at its worst. The upshot of this series of papers was covered in a recent Scientific American piece (which quotes yours truly). To summarize, the argument is that medical male circumcision works (as demonstrated in three large randomized clinical trials, all conducted in Africa) and is cost-effective. Indeed, it may even be cost-saving, with high upfront costs that are easily recovered over a 10 year period. Challenges to scale-up include finding health care workers to carry out circumcisions (in a way that doesn't crowd-out provision of other important health care services), getting people to adopt the practice in a respectful, non-coercive yet effective way, especially in areas where there are strong traditional norms over circumcision, and dealing with any risk compensating behavior (if circumcised individuals think circumcision is protective, they may be more likely to engage in riskier sexual behaviors than they otherwise would - more on this in a later post).

Circumcision is one of those topics that seems to always bring with it a vociferous debate. Those opposed to the practice make their stance known quite vehemently. In my opinion, much of what is being spouted against medical male circumcision as a tool for HIV prevention is based on an incomplete understanding of the available evidence and already strong negative priors against the practice that are almost impossible to shift (for example, see this clip or refer to any of the comments to the aforementioned Scientific American article).

However, I think there is one oft-cited argument against medical male circumcision that is worth discussing further. In particular, opponents point to evidence from a 2009 UNAIDS study that uses recent survey data from 18 African countries and concludes that "there appears no clear pattern of association between male circumcision and HIV prevalence—in 8 of 18 countries with data, HIV prevalence is lower among circumcised men, while in the remaining 10 countries it is higher." This is contrast to the large randomized clinical trials mentioned above which show that circumcision reduces HIV rates by greater than 50%. The fact that the clinical trial results are not borne out in the sample survey data, opponents argue, means that circumcision does not work in "real world settings."

In a recent study, Brendan Maughan-Brown, Nicoli Nattrass, Jeremy Seekings, Alan Whiteside and I offer a different explanation for this differential set of findings. It has to do with the fact that the UNAIDS study looks at population that were circumcised in a multitude of settings (clinics, traditional healers) whereas the clinical trials focus on medical circumcision only. In practice, there great deal of heterogeneity in traditionally circumcising populations: some people do not have all of their foreskin removed, and others are circumcised several years after their peers. In our study population of blacks living in the Cape Town metro area, when we don't account for this heterogeneity, we find only a weak negative effect of circumcision on HIV positivity. However, once we "unpack" circumcision, we find that the practice actually has a strong negative association with the probability of testing HIV positive, provided it is done earlier and that there is complete removal of the foreskin.

These results suggest that the UNAIDS results may simply be due to measurement error. In a traditional setting, a circumcision is not a circumcision is not a circumcision. Treating every circumcised person the same introduces measurement error, and statistically it is well known that this would deflate the estimates of the impacts of the practice towards zero. So, the differential results between the UNAIDS findings and the randomized clinical trial findings is not that circumcision doesn't work in the real world. Rather, it is that we really need to understand better the heterogeneity in male circumcision and what can be done to ensure better outcomes for everyone involved.

Do Financial Incentives Induce Physicians to Provide More (Unnecessary) Care?

About two years ago, I posted something on my now non-existent Facebook account about how medical tests and treatments, especially those that are elective, are more likely to be offered if doctors are reimbursed well for them. My point was that there was a strong financial incentive to test and treat, even in cases where doing so would confer only little benefit to the patient's health, at best. A bunch of people (mainly physicians) responded on my wall pointing out how misguided I was. It was actually a bit more vociferous than this, but I digress.

Anyway, it turns out that I was right (in this case, NOT shocking). I just came across a great study by Joshua Gottleib, an economics job market candidate from Harvard. His study uses a natural experiment in physician incentives to examine whether payment drives care offered. Specifically, he takes advantage of a large scale policy change by Medicare in 1997. Previously, Medicare created different fee schedules for each of around 300 small geographic areas. This was done because production costs and other realities of providing a given service obviously varied across space. In 1997, they decided to coalesce these regions into 80 larger areas. For some smaller areas, there may have been large payouts for certain services which fell after 1997 because the average payout for their new larger group was lower. For others, it went the other way. In any case, comparing pre and post 1997 gives you a nice experiment as to what would happen to health services provision when payouts are changed for reasons other than local health outcomes or demand for care.

Whether you hold my priors or shared those of my misguided Facebook friends, the results remain astounding. Across all health services, Gottleib finds that "on average, a 2 percent increase in payment rates leads to a 5 percent increase in care provision per patient." Predictably the price response of services with an elective component (such as cataract surgery, colonoscopy and cardiac procedures - don't huff and puff, I said elective COMPONENT!) but not so much for things like dialysis or cancer care, where it is easy to identify who needs it and you need to do it no matter what. Furthermore, in addition to disproportionally adjusting the provision of relative intensive and elective treatments as reimbursements rise, physicians also invest in new technology to do so; this is beautifully illustrated by the examination of reimbursement rates and MRI purchases.

So what's the upshot of all this? Is this a good thing? Probably not. Despite scaling up technology, Gottleib is unable to find any impacts on health outcomes or mortality among cardiac patients (for which he explored more deeply the relationship between payouts and treatment). Furthermore, he asserts that "that changes in physician pro fit margins can explain up to one third of the growth in health spending over recent decades."

Ultimately, some good lessons here. First, if we are interested in bring down costs and increasing health care efficiency, we need to pay for things that actually help maintain and increase health. Second, we can't rely on physicians do be the gatekeepers of rising costs as it is clear that, given incentives, they may not always behave in a way that actually improves health outcomes (thankfully, for cases like fractures, cancer or end-stage renal disease treatment, docs aren't sensitive to prices and do the right thing clinically). Finally, we need to stop universally and blindly lauding the US health care system as a bastion of health care technology if that technology does little to improve outcomes.

Infections and IQ

A well known fact about our world is that there are great disparities in average IQ scores across countries. In the past, some have tried to argue that this pattern be explained by innate differences in cognition across populations - some people are just innately smarter than others. Others have tried to attribute these to cultural factors. However, genetics and culture are likely not driving these differences in any meaningful sense. After all, another stylized fact is that average IQ scores have been going up markedly, within one or two generations, within any given country. These changes, also known as the Flynn Effect after the researcher who painstakingly documented them, speak against the genes story because they occurred far more quickly than one would expect from population-wide changes in the distribution of cognition-determining genes. The have occured too quickly to be explained by paradigm shifting social changes, as well.

So what gives? Enter Chris Eppig, a researcher at the University of New Mexico. In a recent piece in The Scientific American , he proposes that cross-country differences in IQ, as well as changes in IQ rates within a country over time, can be explained by exposure to infectious diseases early in life. The story goes something like this: infections early in life require energy to fight off. Energy during this age is primarily used for brain development (in infancy, it is thought that over 80% of calories are allocated to neurologic development). So if energy is diverted to fend off infections, it can't be used to develop cognitive endowments, and afflicted infants and children end up becoming adults that do poorly on IQ tests.

In the piece, Eppig cites some of his work linking infectious disease death rates in countries to average IQ scores. His models control for country income and a few other important macroeconomic variables. His evidence, while not proof of a causal relationship, is certainly provocative. So provocative in fact that I ended up trying to build a stronger causal story between early childhood infections and later life cognitive outcomes. In a recent paper (cited in the above Scientific American article), I examine the impact of early life exposure to malaria on later life performance on a visual IQ test. I use a large-scale malaria eradication program in Mexico (1957) as a quasi-experiment to prove causality. Basically, I find that individuals born in states with high rates of malaria prior to eradication - the area that gained most from eradication - experienced large gains in IQ test scores after eradication relative those born in states with low pre-intervention malaria rates, areas that did not benefit as much from eradication (see this Marginal Revolution piece for a slightly differently worded explanation).

My paper also looks at the mechanisms linking infections and cognition. One possibility is the biological model described above - infections divert nutritional energy away from brain development. However, I also find evidence of a second possibility: parents respond to initial differences in cognition or health due to early life infections and invest in their children accordingly. In the Mexican data, children who were less afflicted by malaria thanks to the eradication program started school earlier than those who were more afflicted. Because a child's time is the domain of parental choice, this suggests that parents reinforce differences in the way their children are (- erhaps they feel that smarter children will be smarter adults, and so investments in their schooling will yield a higher rate of return - and that this can modulate the relationship between early life experiences and adulthood outcomes.

Good and Bad Epidemiology and Other Interesting Links

1. The incomparably intelligent and eloquent Sanjay Basu on how doctor house calls of the olden days could return - in the form of targeted efforts to reduce preventative disease and hospitalizations on the basis of cutting edge epidemiology.

2. A man after my own heart, Dr. Ben Goldacare, an evidence based medicine expert, rails against bad epidemiology studies (you know, the kind in the news that like say coffee is protective against cancer or something like this, only to be overturned 180 degrees two months later) in this entertaining TED talk. Some useful pointers about how to differentiate between junk and good research as well as a good summary of causal inference. (HT: Jeremy Green)

3. Apparently there is enough sense to go around for all of us.

4. Asif Mandvi of The Daily Show lampoons the Republican candidates position on science and scientific knowledge in this great clip. Its pretty funny, until you realize that the candidates are actually serious. Then its a little scary. (HT: Kim Kopecky)

5. How does the recession and being out of work influence our physical activity? And what are its implications for health? Gregory Colman and Dhaval Dave explore these issues in an interesting recent NBER working paper.

Discrimination in the Shadows

Two new papers looking at various aspects of discrimination in product and labor markets. The first, by Ian Ayres and coauthors, examines baseball card sales:

We investigate the impact of seller race in a field experiment involving baseball card auctions on eBay. Photographs showed the cards held by either a dark-skinned/African-American hand or a light-skinned/Caucasian hand. Cards held by African-American sellers sold for approximately 20% ($0.90) less than cards held by Caucasian sellers, and the race effect was more pronounced in sales of minority player cards. Our evidence of race differentials is important because the on-line environment is well controlled (with the absence of confounding tester effects) and because the results show that race effects can persist in a thick real-world market such as eBay.

The second looks at skilled immigrant labor in Canada. Canada, like many other first world countries, has made it a policy to strongly select for skilled immigrants to augment their workforce. Unfortunately, these immigrants do not do as well as one would hope in the labor market. Philip Oreopoulos explores this issue in greater depth:

Thousands of randomly manipulated resumes were sent in response to online job postings in Toronto to investigate why immigrants, allowed in based on skill, struggle in the labor market. The study finds substantial discrimination across a variety of occupations towards applicants with foreign experience or those with Indian, Pakistani, Chinese, and Greek names compared with English names. Listing language fluency, multinational firm experience, education from highly selective schools, or active extracurricular activities had no diminishing effect. Recruiters justify this behavior based on language skill concerns but fail to fully account for offsetting features when listed.

While they speak for themselves, here are a few collective comments on these papers:
1. Both illustrate the power of audit studies, where researchers elicit real-time behavioral responses in the field to some often innocuous stimuli. Resume experiments have a long history in economics and sociology. The EBay thing is new, and quite innovative.
2. Audit studies give us an example of behavior, but can further be extended to think about mechanisms and policy. One reason I like the Oreopoulos paper is that his randomization involved an explicit countersignal to having an immigrant last name. Unfortuntately, it didn't work to reverse the discriminatory effect, but it is informative that signaling language skills failed. What would be nice is to further extend this, both to other policies, but also to a further elucidation of mechanisms. I think qualitative work could be very useful in this regard. (My colleagues and I did this in a paper about corruption).
3. Both of these studies reveal that taste-based or statistical discrimination is pretty deep seated, though it may lurk in the shadows. So what to do about this? Jumping from (2), I hope the next wave of experiments look at different sorts of policies. Are there other nudges that can be used to counteract these forces? Or will immigrants have their change from Shankaranarayan to Steve in order to get jobs?

Building Reflexes

So I am now a third of the way into my intern year in my internal medicine residency. The whole enterprise started off as a string of stress and self-doubt inducing thought after another: There is a lot to know and I don't think I'll ever know any of it...Wow, that senior resident is really smart. I'm never going to be that good...Dr. So and So is a great attending, I'm never quite going to get there...I've never done a thoracentesis before. What is I mess up?...What if I kill someone?

Of all of the above, a green intern seeing the sheer confidence and competence of the junior and senior residents was somehow the scariest. It was a mystery how someone could go with my fund of knowledge to their fund of knowledge in a year or two. I was convinced I was the imposter in my intern class, the one for whom the physician production process would fail.

Along these lines, as I've moved through intern year, I've learned three important things. All of these have served to keep me sane in the storm of self-doubt:

1. A scared intern is an intern who has an appropriate level of confidence, and therefore thinks harder and is quicker to ask for help. He/she is therefore a safe intern.
2. Every intern feels the same fear coming into residency.
3. The goals of intern year should be modest. Not, "I want to read everything become a master clinician after 1 month on an inpatient service" but "I want to develop quickly implementable algorithms for common clinical situations that will ensure that I am thorough and efficient."

This last aspect is what I call "reflex building." There is a set of clinical situations that interns and residents will face time and time again. Getting good at working up and troubleshooting those problems builds confidence, saves time and allows you to devote your precious tired brain to more intransigent clinical issues.

I remember my first call night where a gentleman became short of breath. I walked into the patient's room, following a frantic nurse, with a veneer of calm but with the insides of a rookie quarterback facing his first test against a wild, aggressive defense. Thoughts scattered, I correctly asked for a stat chest x-ray, ABG kit, had the angle of the bed increased, and called for stat labs. I listened to the chest and thought it sounded wet, and ordered a diuretic. Prior to all this, I paged the teaching senior resident on call.

It turns out I did alright, but I forgot to get an EKG. In my stressed state, I forgot to think about acute cardiac issues (like heart attacks) as precipitants for this new shortness of breath. Clearly, ruling out heart attacks is an absolute must. Luckily the nurses and the night senior all knew what to do and the EKG machine was in the room and humming before I'd even thought to call out for it. (The patient was not having a heart attack.)

Two months later, I was in the same situation. I walked in to the room, again with some outward swag, but this time with also with an organized work-up plan. I got all the tests I needed to get. It turned out the gentleman had missed his diuretic pill for two days. He sounded "wet" and I diuresed him. His EKG was fine and the patient got better quickly. I then had time to leave and deal with the four new admits that hit the floor all at once, then later check in on this patient before I handed off the service to the day team.

It was at that point I realized that I had actually learned a lot during intern year. At any given point in time, the marginal output of the physician production function is hard to observe. That is, at most points in your training, you are faced with such a huge knowledge base that the distance between you and the ideal always looks limitless – you don’t really feel like you are getting anywhere. However, in situations like the one I just described, or where a patient has new urinary retention, new chest pain, a new GI bleed, we've all now seen enough of these to know how to handle these problems efficiently and safely. It’s a great feeling to have these new clinical reflexes.

Some time later, I took on the roll of "running plans" in our inpatient service. Basically, our inpatient service has four interns that take on different roles every day. The "plan runner" goes through each of the twenty or so patients and decides what needs to be done for that day based on that mornings exam and labs, the previous nights events, and all the accruing data about the clinical course. The junior resident, who runs the team, watches over all of this and chimes in and teaches when necessary (which is a lot, early in the year). The first few times I ran plans I got a lot of much needed and much appreciated input from the junior ("Do you really want to do that? And have you thought about this?"). More recently, I’ve been hearing less from them. And I also have a better sense of the nuances the junior needs to know to run the team effectively - how to discharge patients, when not to get labs, how to deal with a difficult consult service. There was one moment, though brief, where I thought to myself “I think I can do that. I think I can be a good junior.”

That was a small, but important, victory.

Ultimately, perhaps the best lesson from all this is to trust in the production process. As our program director put it during orientation, "[The residency program has] been doing this for years. Sit back, put on your seat belt, and let us do our thing. You'll be fine."

Battling the Bulge

Some innovative social policy this week in Mexico, where the federal government been expressing some palpable alarm over rising obesity among children and adults. I'm sure that Mexico now is the fattest nation in the world and, if they aren't, they are right behind the US in this dubious regard. From a country that was worried about infectious disease deaths just a generation ago to one that is increasingly burdened by diabetes and heart disease comes a new social policy that aggressively seeks to reduce obesity in children by banning junk food, increase hours of physical education, and provide nutritional education in a school based setting. Only time will tell whether they can get people to substitute agua for refrescas, but I like where they are headed with this multi-pronged approach. I know there is some evidence that each of these interventions could provide positive benefits alone (see, for example, here), so perhaps there will be a bigger kick from all three together.

On our side of the border comes some new evidence that your neighborhood matters as far as obesity goes. A study in this week's New England Journal of Medicine finds that poor households randomized to receiving housing vouchers enabling them to move to nicer neighborhoods were significantly less likely to be obese and have elevated hemoglobin A1c levels (a marker of blood sugar content used to diagnose, and track response to treatment for, diabetes). This experiment validates a long-standing hunch that neighborhoods matter for obesity. The question now is what exactly matters, i.e., what is the mechanism behind this causal pathway? We obviously need to know this in order to design targeted policies? Is it that better neighborhoods have better designed streets that encourage walking? The presence of parks? Are there positive peer effects from health nuts? Better grocery stores and more healthy food options relative to junk food options? Better access to primary care docs? I'm awaiting the follow up study which tries to tease these different possibilities apart.

R.I.P Steve Jobs

"Your work is going to fill a large part of your life, and the only way to be truly satisfied is to do what you believe is great work. And the only way to do great work is to love what you do" - Jobs, during a 2005 commencement address.

Foreclosures and Health

Great paper by Janet Currie and Edral Tekin on the housing crisis and its impacts on health outcomes:

We investigate the relationship between foreclosure activity and the health of residents using zip code level longitudinal data. We focus on Arizona, California, Florida, and New Jersey, four states that have been among the hardest hit by the foreclosure crisis. We combine foreclosure data for 2005 to 2009 from RealtyTrac with data on emergency room visits and hospital discharges. Our zip code level quarterly data allow us to control for many potential confounding factors through the inclusion of fixed effects for each zip code as well as for each combination of county, quarter, and year. We find that an increase in the number of foreclosures is associated with increases in medical visits for mental health (anxiety and suicide attempts), for preventable conditions (such as hypertension), and for a broad array of physical complaints that are plausibly stress-related. They are not related to visits for cancer morbidity, which arguably should not respond as rapidly to stress. Foreclosures also have a zero or negative effect on elective procedures, as one might expect. Age specific results suggest that the foreclosure crisis is having its most harmful effects on individuals 20 to 49. We also find that larger effects for African-Americans and Hispanics than for whites, consistent with the perception that minorities have been particularly hard hit.

This study makes a few key contributions to the literature on economic vulnerability and health outcomes. First, it utilizes very detailed data that both enable precise estimates and a number of statistical techniques that can better address potential confounders. Second, the authors make great use of falsification tests. Basically, in theory you would expect stressful events to impact some diseases and not others (especially those that take time to evolve). The authors follow up this idea and actually demonstrate it in their data, which makes the results more believable.