Starting With Curious

We just had the great fortune to spend 2 weeks vacationing in Argentina.  It represented a couple of first for us: first time in that country, and first time taking an entire two week vacation.  We thought it was pretty luxurious, and actually it was.  So we were struck by the number of travelers we met, from a range of other countries, who were in the midst of a 4, or 8, or 12 week trip.  Indeed, the only people we encountered who were on a shorter vacation than us was a couple from Philadelphia.  What were we doing wrong?

Some of the people were retired (although they indicated that they had done similarly long vacations when they were younger), but many were working age.  How do they pull this off, we wondered?  There seem to be a few factors:

1. Paid leave. Most industrialized countries provide much more generous paid leave, either by mandate or due to union leverage, than the US.  One of our guides, when asked whether Argentine workers get much vacation time, seemed shocked at the question.  “Of course, it’s in our constitution!  I mean, we may be Argentina, but it’s not like we’re in Africa or someplace like that.”
2. Culture. Americans work longer hours than most other industrialized countries (including all of Europe and Japan, though we are still outpaced by Singapore, South Korea, and Taiwan).  The difference in hours worked is greater than the difference in paid leave (i.e., we don’t even use the little we get), suggesting that some of it is due to a cultural reluctance to get away from our jobs.  In many industries, it’s almost a badge of pride to be “on” constantly.  We talked with several people who were taking extended leave without pay, something few Americans do (or are permitted to do).
3. Health care. Even if an American wanted to take unpaid leave for an extended trip, she would in many cases have a pause in employer-provided benefits, especially health insurance.  Paying for coverage while on unpaid leave is too much of a financial burden for most people.  This is not an issue for people from countries with government-provided health care, like Canada, the UK, France, Germany, Australia, New Zealand, Belgium, Denmark, Norway, Switzerland, Spain, the Netherlands, etc., etc.

Which leads me to two other points.  First, among the folks I had the opportunity to talk with were a doctor from Argentina and a nurse from England.  Both had wonderful things to say about their national health systems, including that fact that while people do often carry private insurance for things like a nicer room in the hospital, or a shorter wait for an imaging test, people are enormously satisfied with the quality of care.  “Everyone knows that the best doctors are the ones that work for the National Health Service.”

Second, when they talk about their “free” health care, of course we know that it is not free.  People pay either through their insurance premiums, or out of pocket costs, or taxes.   But while we might gag at the tax rates in places like Scandinavia, a recent study shows that, when you add it all up, public and private sources, the US actually has the second highest total social expenditures (largely health care, but also unemployment, retirement, disability, etc.), after France but ahead of those tax-and-spend Nordic countries.

Oh, and the wine in Argentina is terrific and cheap!

I am still on vacation, so Happy Thanksgiving…

When I was growing up, family meals were not an everyday event.  My mother, a nurse, often worked evenings, so those days we obviously couldn’t all eat together.  But we did make an effort to eat as a family on the other days.  Similarly, when we were raising our kids, despite my working shifts and both my wife and I traveling a fair amount for our jobs, we also placed a premium on eating together whenever possible.  That often meant having dinner 5:30 some days and 8:30 on others, but it seemed worth it.  After all, the demise of the family dinner has been cited as one important factor in the obesity epidemic, along with a host of other societal ills.

A new study in Pediatrics suggests that when it comes to risk of obesity, at least, not all family meals are created equal.  Researchers at the University of Minnesota, using a mixed-methods study including direct observation of 120 primarily low-income families, identified aspects of mealtime that were associated with obesity in the children.  While non-overweight children tended to have somewhat longer meals, and were more likely to eat in the kitchen or dining room vs. family room, the differences were small, and most meals were short (< 20 minutes), and the majority of both groups ate in a dining area.  More important were the family dynamics.  After adjusting for demographic factors (including parental BMI), the most important factors associated with child overweight or obesity were presence of positive interactions among family members (for example, enjoyment of each others’ company, warm interactions, positive reinforcement), and the absence of negative ones (hostility, lack of discipline, etc.).  Interestingly, very few food-specific dynamics were relevant.  Only moralizing about food – for example, “Eat what I gave you – other children are hungry and would be happy to have it” – was associated with the child’s weight; children who were hectored were more likely to be overweight.

Good information for those of us with families, or who are providing advice to families.  Michael Pollan, author of The Omnivore’s Dilemma and a proponent of better eating (for the sake of our own health as well as that of the planet, sums his advice up succinctly into 3 rules: “Eat food.  Not too much.  Mostly vegetables.”  To which we might add a fourth “Eat with people you like and get along with..”

Ask your doctor if you might be suffering from “restless legs syndrome.” Or “low testosterone,” or “social anxiety disorder.”  We’ve all seen the ads suggesting that our legs cramps or aging or shyness might instead represent a disorder with a name.  One that, not coincidentally, could be helped by a medication manufactured by the sponsor of the ad.  A medication for which you can ask your doctor for a prescription.  But while doctors like to complain about Big Pharma’s “diagnosis mongering,” what if we are also part of the problem?

“Overdiagnosis: How Our Compulsion for Diagnosis May Be Harming Children,” in the November issue of Pediatrics, raises this question.  The authors here are not referring to the kind of pseudo-disorders pedaled by industry.  By overdiagnosis they mean the discovery of a true abnormality, where the diagnosis does not benefit the patient.  This may include minor forms of a condition that would neither benefit from treatment nor be expected to progress to something more severe, or conditions for which treatment has been shown not to affect outcomes.  Think of low levels of elevated bilirubin in a newborn, asymptomatic skull fracture due to minor accidental trauma, or positive IgE blood test results indicating a response to food allergens in the absence of clinical symptoms.  None of these is treatable, and even knowing the diagnosis isn’t helpful in any way.  Yet physicians often perform – and sometimes parents request – tests for these and other diagnoses.

What is behind this drive for a diagnosis that doesn’t matter?  The article cites a few groups of factors.  One is industry influence.  There is no doubt that advertising does drive some demand.  (There is a reason pharma spent $4.5 billion on direct-to-consumer advertising in 2009, in addition to support for various disease advocacy groups, with varying degrees of legitimacy.)  Another is incentives in the current health care system.  For one thing, providers are often financially rewarded for unnecessary testing and care.  A review of pediatric quality measures also shows a marked bias toward indicators focused on underuse of resources rather than overuse.  Public perception that diagnosis is more precise than it really is, coupled with an intuitive sense that it must be better to detect disease, as another factor.  But the largest influence, according to the authors, is physicians themselves.  We have a culture of intolerance of uncertainty.  We hate not having an answer, something that is ingrained from the earliest days of medical education where students are encouraged to develop a lengthy list of potential diagnoses and then exhaustively eliminate them one by one until finally arriving at the right one.  “Defensive medicine” is frequently cited, but most of the research suggests that this plays at most a minor role.

Cost is the obvious downside.  But there are others.  There are potential adverse physical effects, if having a diagnosis leads to treatment that will not benefit and might harm the patient.  Sometimes the tests ordered in search of a diagnosis are themselves risky (procedures requiring anesthesia, for example, or radiation exposure).  There is also real psychological harm in carrying a diagnosis.  The newborn who is a little yellow and has a mildly elevated bilirubin gets a diagnosis of  “hyperbilirubinemia.”  A child with nonspecific symptoms who tests positive for antibodies to shellfish and eggs is now labeled as “food allergic.”  Numerous studies have documented the “vulnerable child syndrome” in such children.  It results in increased utilization of health care, overprotective parenting, and bullying, among other consequences.

There are several efforts – from professional societies and academic medical centers – targeted at both providers and lay people to increase awareness of the presence and problems of overdiagnosis.  Traditionally, academic medicine has probably been more of a cause, but is now trying to be part of the solution.

Ask your doctor if you might be suffering from “adiagnosticophobia.”

Say a coin is tossed 10 times, and each time it comes up heads.  What is the probability of heads on the next toss?  It might be tempting to say that the probability is low, since surely 11 heads in a row is extremely unlikely.  But the correct answer is 50%.

Or is it?  It turns out, it depends on what kind of statistics you rely on.

Mark Twain talked about three kinds of falsehood: lies, damned lies, and statistics.  What he didn’t point out is that there are actually different kinds of statistics, and they sometimes give different answers!  The traditional school, known as “frequentist” statistics, is based on the independence of events.  The chance of heads on any toss is completely unrelated to the prior results.  While the probability of 11 heads in a row is indeed extremely unlikely (about 1 in 2000), the chance of any one of those tosses being heads – even the last one after a string of other heads – is still 1 in 2.  Yet it still feels counterintuitive.  After all, I just saw 10 heads some up – how could there possibly be another?

An increasingly popular approach to statistics attempts to answer this.  Bayesian statistics, named for the Reverend Thomas Bayes¹, does not assume that the probability of an event is completely independent of prior events.  Instead, the expected probability of an event incorporates other known information, including other results up to that point.  In this case, if I am asked to estimate the chance of an 11^th head, I would look at the string of 10 heads in a row and reasonably wonder if perhaps this is not a fair coin.  The answer to that question, in turn, would be based on other information.  How well do I know the person tossing the coin?  Did I have a chance to examine it beforehand?  If there is good reason to believe that the coin may in fact be biased, then I would have to conclude that the probability of a head coming up on the next toss is indeed higher than 50%.  Which is what it feels like intuitively.

While frequentist statistics is what is most commonly taught, most of us in reality behave like Bayesians.  We don’t simply ignore the string of 10 heads as being irrelevant.  While a frequentist would assume the coin is fair, the Bayesian at least asks the question when confronted with evidence that it might not be.

This shouldn’t be an excuse for complete subjectivity.  A true Bayesian approach is just as analytic and quantitative as a frequentist one, and in practice can be more complicated.  But it does more closely mirror the way our minds actually work.  Most physicians are Bayesians when it comes to diagnostic decision-making.  Here’s an example.  I see a child with abdominal pain, and am concerned about appendicitis.  At first, all I know is the age and gender – say, an 11 year old boy.  I know that approximately 10% of all 11 year old boys who come to the ER for belly pain will have appendicitis.  That seems high enough to worry about, but not high enough to go ahead and remove his appendix just yet.  So I go ahead and examine him.  He has a Pediatric Appendicitis Score of 3.  According to the research, half of patients with appendicitis would have a score of at least 3, and only 17% of the patients without appendicitis have a score that high.  Using Bayes’ theorem (look it up if you want, but trust me on the math), I can revise my estimate for the probability of this patient of having appendicitis, knowing not only that he is an 11 year old boy, but an 11 year old boy with a PAS of 4.  His chance of appendicitis is no longer 10%, it is 25%, high enough that I should probably not just ignore it but do further tests.  Based on the results of those tests, I would again update my estimate of probability upward or downward.  On the other hand, with a score of 1, this boy’s chance goes from 10% to less than 2%, and I can reassure the family that we do not need to worry about it unless something changes.

This example illustrates something that may be surprising to non-medical professionals, who may think that tests can tell you whether someone does or does not have a disease.  This is almost never the case.  Every test can have false positive or false negative results.  They are simply one more piece of information that must be interpreted in light of what else we know.  A positive test generally increases the likelihood that someone has the condition we are checking for.  A good test will indicate a high enough probability to take action, while a not-so-good test leaves us sufficiently uncertain that we need more information.  And there are a lot of not-so-good tests out there.

Perhaps the biggest challenge to Bayesian analyses is the need for prior information.  Sometimes this might be based on good research or our own prior experience.  However, we must often make an educated guess.  In those cases, our judgment may be biased by many factors, including what I have previously referred to as availability bias (the tendency to be overly influenced by recent experience or information.)  A child comes to the emergency department with a fever.  His mother recently returned from Africa.  What is the chance the child has Ebola?  Your first reaction might be a small but measurable number, say, a 1% or even a 5% chance.  In reality, we know very little, for example, whether or not the mother has been in a part of Africa affected by Ebola, when she was there, and whether she has had any symptoms and could therefore have transmitted the disease to the child.  Based on what we do know, our highest possible estimate (assuming she had fever and that her travel was in the past 21 days) would be the number of known Ebola patients in Africa (about 10,000) divided by total population of Africa (a little over a billion), or 0.001%.  If we found out, for example, she had been in Guinea, we would change our estimate to a higher chance, while if she had been in South Africa it would be far lower.

And Mark Twain never heard of Ebola.

[1] An 18^th century Presbyterian minister in England.  The apochryphal story is that he developed his theorem in an effort to prove the existence of God.

A few years ago, when a poll was released showing that Congress’ approval rating was at an all-time low of 9%, several commentators pointed out that it was substantially lower than Stalin’s approval rating in Russia.  Which provides a little context around a recent study supported by the Robert Wood Johnson Foundation and reported in the New England Journal of Medicine.  It showed that in response to the question, “All things considered, doctors in [your country] can be trusted,” only 58% of Americans agreed.  This placed us 24^th of 29 countries surveyed, just above the former Stalinist countries of Bulgaria, Russia, and Poland.

Ouch.

This represents a significant decline from the 1960s.  It parallels a general distrust of the health care system (23% approval).  Interestingly, Americans are much more satisfied with their own doctor (ranked 3^rd internationally) than with doctors in general, which mirrors the pattern of opinions about Congress as a whole (low approval) vs. one’s own representative (much higher).  Why the growing distrust of the medical profession?  Some of it is undoubtedly reflective of a generalized trend away from traditional deference to authority.  (I have no data to support this, but I’d guess there is an erosion of trust in the Encyclopedia Britannica, too.)  There has also been a de-deification of physicians.  Think of the contrast between Dr. Welby and Dr. House.  But another clue may come from looking at the results broken down by income.  Americans with above-average income rated doctors’ trustworthiness higher than those with below-average incomes.  This pattern was not seen in other countries.  Another study in the same issue of NEJM showed that access to healthcare is also sharply lower for low-income Americans, another disparity not seen elsewhere in the world.

Unfair as it may be, it seems likely that as Americans face more barriers to care due to rising cost and our lack of universal coverage, they are taking it out on all those who are seen to be benefitting from the system, including, unfortunately, doctors.  This is exacerbated by stories like the one in the New York Times about the unexpected bill for $117,000 for an assistant surgeon, or one of my buddies getting an $18,000 bill for his wife’s cataract surgery from a doctor he had never heard of.  Unfortunately, we physicians are seen as no better than those Party leaders who benefitted under Communism.  Or – gasp – than Congress.

If we needed any more evidence that yes, cost matters to patients and families, a new study from Annals of Surgery should be a wake-up call.  Researchers from Primary Children’s Hospital in Utah approached the families of 100 children about to undergo surgery for acute appendicitis.  They were offered 2 options: the open procedure, or laparoscopic surgery.  Based on published evidence, they were told that the complication rates were similar, but that open appendectomy would result in a larger scar.  One half of the families were only given this clinical outcome information.  But the other half were also given information on the charges of the two different procedures: $2172 less for the open procedure.

We pediatric providers have long assumed that, when it comes to their children particularly for something serious or with potential lasting consequences, parents would always pick what was best.  Cost would be no object.  Well guess again.  In this study, among families not shown the charge information 35% of the time, while those who were aware of the charges chose the less expensive, bigger scar option 63% of the time.  Interestingly, this difference was independent of insurance type, deductible, or income.

I’m not suggesting that parents will take their kids to Walgreens for a heart transplant, or that many parents wouldn’t make extraordinary efforts to get what they think is best for their child.  But this study demonstrates that cost is a major factor.  When told the cost, they are willing to trade off some significant possible negatives – in this case, a larger permanent scar.  As one familiar member said, “Cost saving measures are a priority for me when it does not impact the safety of the patient.”  And this is an acute, potentially life-threatening condition, where the parents may weigh cost less due to the pressure of making a decision without time to really consider the alternatives or “comparison shop.”  Imagine how this might look for something completely elective like ear tubes.

A few important caveats.  First, the surgeons in this study could convincingly claim the complications would be expected to be similar because it would be the same team – surgeons, anesthesiologists, nurses, etc. – doing either procedure.  In the real world, parents need to choose between more dissimilar alternatives, such as a specialized children’s center with a full complement of sub-specialists vs. a lower volume community hospital with non-pediatric providers.  Second, parents were provided with the full cost of having the appendectomy: a bundled price for everything.  In reality, most people have a hard enough time finding out the price of each item or service used.  The move to price transparency can only work if hospitals and providers can show what the total cost to the family will be.  For example, our hospital has a reputation for being expensive, based on the price of some of our services.  But analyzing data reported to the state of Wisconsin, I was able to show that for children in the Milwaukee area, the least expensive average charge for an emergency department visit was at Children’s Hospital of Wisconsin!  I didn’t have the data to figure out why, but a very reasonable hypothesis based on other research on differences between general and pediatric EDs is that we do less testing and treatment than at other hospitals because of our greater expertise in dealing with children.  (I have long held that the key to being an excellent pediatric emergency physician is as much in knowing what not to do as what to do.)  Even if Children’s charges more (and I don’t know if this is actually true) for a CT scan of the head, a parent wanting to know the cost needs to understand that their child is far less likely to get one unnecessarily in our ED.

It’s all back to the value proposition.  People paying for health care – and increasingly that is families themselves – want a good outcome and good experience at a reasonable cost.  If we want to attract children to our hospital – and kids do deserve the best – we need to be able to demonstrate all parts of that value equation.  And what this Annals of Surgery study shows is that we can’t assume we know what parents will value.  Many of us would pay more for the smaller scar.  But what matters isn’t what we would do.  We can provide information, we can provide guidance; only the family can decide.

Farmers vs. ranchers.  Jets vs. Sharks.  Arabs vs. Israelis.  Bourgeoisie vs. proletariat.  Packer fans vs. Viking fans.  Examples of seemingly unbridgeable gulfs abound in literature and life.  It’s sometimes difficult to picture these groups even talking to each other, much less connecting.  In the 1990s, books like Men Are From Mars, Women Are From Venus, and You Just Don’t Understand, popularized the notion that, because men and women see and process the world so differently, it creates inherent barriers to effective communication.  While criticized in some circles for over-generalization and stereotyping, the research behind these books supports the idea that differences in life experience can undermine meaningful dialogue and relationship-building between people.

New evidence shows that this is particularly true about class background.  In a series of studies, Stephanie Cote and Michael Kraus showed that interaction between people of different socioeconomic status were marked by verbal and non-verbal indications of lower degrees of engagement and emotional connection.

Think about the implications.  Many in the healthcare professions are at least in the middle class, while a large number of our patients and families are significantly less advantaged.  Does this interfere with our ability to bond with them, to empathize?  At times we have to admit it does.  Who hasn’t heard (and at times made) disparaging comments about “frequent flyers,” patients who are “non-compliant,” folks abusing the system?  This happens all too often.  Yet by and large, even those of us near the top of the economic ladder show amazing cognitive and emotional connection to those we care for.  How do we do it?

The answer, I think, comes from some of the same studies.  When participants were asked to interact with others of different background, their engagement and connectedness increased when they were first asked to identify points of commonality.  We see this when people of widely varying status come together in fellowship in places of worship (shared faith), or sports leagues or clubs (shared interests), or life-threatening emergencies (shared mortality and fate).  For us, I believe it is the kids, our value of purpose.  We caregivers and providers on the one hand, and families on the other, share an interest first and foremost in the child.  It’s when we forget that commonality that we fail to make a real connection, moving from curious to judgmental.

One of my favorite books, The Lemon Tree, tells the story of a Palestinian and an Israeli who bond over a shared love of a piece of property.  It shouldn’t be hard for each of us to try to find that one piece of common ground when we deal with families or colleagues who may be from such different circumstances that connecting is a challenge.  Even Packer and Viking fans can agree about the Bears.

The results are in, and Wisconsin is the winner! The 2014 National Bike Challenge just ended, and our state edged out last year’s winner, Nebraska, with over 7800 participants (including 40 from Children’s Hospital!) pedaling 3.9 million miles, of which 70% were for recreation and 30% were for transport.  That’s 1.3 million miles of commuting and errands that might otherwise have required a car.  In Wisconsin alone, we kept 3.6 million pounds of carbon dioxide out of the atmosphere.

The environmental impact is one of many reasons I and others choose to try to get around as much as possible on two wheels.  Much of the year it’s just nice to be outside, and it can be a really relaxing way to unwind at the end of the day.  Of course, it’s also a good way to get in some exercise while also doing something useful (spoken like a true multi-tasker).  The Wisconsin contingent burned a collective 213 million calories cycling during the five months of the challenge.  Just think of all the deep fried cheese curds we could eat afterward….

People are catching on.  I’ve noticed the bike racks here at the hospital getting more and more full.  Nationally, miles driven are down, and the number of people bicycling to work increased in 85 of the 100 largest metro areas between 2000 and 2010.  According to the Guardian, not only are individual workers recognizing the benefits and switching, but businesses are finding that promoting cycling actually improves their bottom line.  Businesses with access to protected bike lanes (such as you find everywhere in Denmark and the Netherlands) have higher sales per parking spot (car vs. bike); real estate values are higher; and workers are healthier.

Some recent local developments could make the picture even brighter for cyclists.  The city of Milwaukee has been adding bike lanes, and Wauwatosa, as part of a comprehensive cycling and pedestrian plan, is adding high-visibility green bike lanes to North Ave.  And we are finally catching up, albeit slowly, with the bike-sharing trend in many cities.  Bublr, a Milwaukee bike share start-up, currently has 10 stations around the city, with plans to increase that to 100.  (Several locations on the Milwaukee Regional Medical Center campus and in the village of Wauwatosa are being considered.)

Yes, I know winter will be here before we know it (or want it), but there’s still plenty of fall days left.  (And don’t rule out winter commuting.)  Give it a try.  We don’t want those Cornhuskers to catch us.

There are two especially awkward phases of life for most physicians: adolescence and residency.  Both are sort of in-between states, where you are not quite what you left behind but not yet fully what you are moving toward.  Is a resident a learner or a worker?  Depends on who you ask, and the answer has changed over time.  For example, when I was a resident we belonged to a union (!) – the Committee of Interns and Residents (CIR).  Except the CIR wasn’t a true union, because we were considered students rather than employees, and therefore not able to unionize.  At the same time, we were able to continue to defer payments on student loans because we were still “in school.”  Since then, the National Labor Relations Board has ruled that residents are actually employees and therefore entitled to organize (the CIR is now affiliated with the SEIU), while the IRS has ruled similarly, and residents must begin making student loan payments.  Win some, lose some.

The uncertainty carries over to the issue of federal funding for graduate medical education.  Currently Medicare, Medicaid, Veteran’s Affairs, and the states pay approximately $16 billion annually to hospitals to offset the cost of having residents and fellows.  Part of that covers the salaries and benefits of the trainees (direct GME), while the majority offsets the additional costs associated with medical training (indirect GME), such as lower productivity for supervising physicians, additional testing ordered by trainees, etc.  (I should note that this generally does not include pediatric residents and fellows, as children’s hospitals do not treat Medicare patients.  A separate, much smaller [$265 million] stream of Children’s Hospital GME funding is available, but unlike the Medicare money, it must be approved annually during the budget process.)

The rationale for this funding is that the training of physicians benefits society.  Teaching hospitals would have no financial incentive to train physicians who can, after all, go work anywhere when they are done.  Therefore, government should help pay for ensuring a supply of trained medical professionals.

Buried in a recent Institute of Medicine report on the state of graduate medical education, a small but notable group of health economists questioned that rationale.  They argue that residents provide a greater economic benefit to their hospitals than the salaries they receive; therefore, government GME funding is simply a subsidy of those hospitals.  The fact that most hospitals actually have more residents than they get funding for (the number was capped in the 1990s) is evidence that the hospitals must see them as a good investment.

If true, this might argue for using that $16 billion for other purposes, as those economists urge.  However, as I’ve already indicated, it’s not all that clear cut.  It is true that residents provide work that is of benefit to the hospitals that employ them as well as to the attending physician staff.  But much of this work takes the form of documenting and performing other tasks that can be – and in non-teaching hospitals, is – done by nurses or advanced practice providers.  And it isn’t clear that the work done by a resident provides more value than what could be done by these others, as the economists imply.  For one thing, residents rotate to different areas of the hospital each month, and often between hospitals.  There is a constant learning curve that in most cases sharply limits the benefit of the work compared with what you would get with a stable staff.  Moreover, the ratio of useful work increases with years of residency, but once residents enter their last (and most “productive”) year of training and really hit their stride, they leave.  In simple economic terms, most hospitals would actually be better off hiring non-residents for those tasks.

I do believe there is a unique value to a hospital of having physicians-in-training.  It’s not, as these economists argue, cheap labor.  Rather, it takes the form of the academic, intellectually challenging and stimulating environment that residents create.  It’s part of the reason I and many of my colleagues have always wanted to be at a teaching hospital.  That, however, is difficult to quantify.  In the current health care environment, with ever greater economic pressure, hospitals may be less willing to invest in such an intangible benefit without the GME funding.

Also, while it may be partly coincidental, teaching hospitals tend to be the care provider of last resort in a community.  The mission of caring for everyone regardless of ability to pay tends to go hand in hand with the education mission.  Part of the indirect cost of a teaching program is the large percentage of patients for whom the actual costs of care are not covered (Medicare, Medicaid, uninsured).  Yes, it’s a subsidy, but not for the bottom line of the hospital.  It’s a subsidy of the safety net we provide, masked as a subsidy for training future physicians.

There are certainly improvements we can make in the way GME is paid for.  For example, the program could do a better job of prioritizing undersupplied primary care fields (including pediatrics).  But arguing that GME funding is a form of corporate welfare for hospitals, and that the costs of training residents should be left to the marketplace, is not going to get us more of the right kinds of doctors, or better care for patients.