Primary Care and Specialty Pay Across Countries

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The OECD published data last month showing the relative pay of PCPs and specialists across 14 countries.   The US had the highest relative pay for primary care physicians, while the Netherlands had the highest relative pay for specialists (with the US in a close second.)  Most countries had less disparity between the multiplier of PCP pay to average wage and that of specialist to average wage.   Note that this report counts pediatricians and probably many internists as specialists - so it understates the income disparities.  Here is a link to the full report.

The US is not the only country with a lot of new technology (But ours is more expensive!)

One of the students from our class this fall, Elad Sharon, writes from his journey on a public health school trip to India:


I have been impressed by the number of MRI's here.  I suspect that there are more MRI's in the Indian state of Kerala than in Canada (similar populations, but vastly different incomes, of course).  It seems that the Indian health system is also enamored of technology, and cost-cutting strategies focus on reducing unnecessary tests and unnecessary care.  Insurance schemes are rudimentary at best, and generally organized by government unions or even, in one case, a cancer hospital.  Definitely, eye-opening.  Labor costs are ridiculously cheap, but the needs are immense.  Non-Resident Indians (NRI's) distort the market generally, and may actually inadvertently fund the technology development.


 Many countries have far more MRI scanners than the United States on a population basis.  For instance, Japan has 40 MRIs per million population, and the US has 26.5.  (Canada has only 6.2).  The difference is that MRIs in India (not part of the OECD study) cost 5000-7000 rupees ($102-$140), whereas MRIs cost Massachusetts health plans a median of $700 , and the “list price” is probably twice that. 

Some Indian provinces have high supply of MRIs, but their cost per unit is quite low. The US has a trifecta - the combination of high supply, high utilization, and high prices.  





WSJ op-ed assails comparative effectiveness research

The January 20 Wall Street Journal included an op-ed from the American Enterprise Institute decrying the potential for a government-funded comparative effectiveness institute.

In this opinion piece, Scott Gottlieb suggests that such a government-funded comparative effectiveness institute
(1) Will not save money
(2) Will use poor scientific methods
(3) Would do research that would be effectively done by the private sector if only the FDA would allow private companies to publicize their comparative effectiveness findings.

My response:
(1) Here are the CBO comments from December, 2007.

Generating additional information about comparative effectiveness and making corresponding changes in incentives would seem likely to reduce health care spending over time—potentially to a significant degree. The precise impact, however, depends on several factors and is difficult to predict. Given the time necessary to conduct the research, to alter incentives in a manner reflecting the results, and to affect behavior through those changes, any potential for substantial cost savings from new research would probably take a decade or more to materialize. Even so, generating additional information comparing treatments would tend to reduce federal health spending somewhat in the near term—but that effect may not be large enough to offset the full costs of conducting the research over that same time period

(2) There is some thought that we might have to settle for research that wouldn’t merit publication in the New England Journal. Question – isn’t some information even if imperfect better than the current state of utter lack of information?

(3) The CBO points out that private parties just don’t have the right incentives to do good comparative effectiveness research. Pharmaceutical and device makers are not likely to be impartial enough (Here’s an example. This article showing that a medicine was ineffective was published in Annals of Internal Medicine 8 years after the completion of data collection. The publication was delayed until long after fluconazole, the drug in question, lost its patent protection). . On the payer side, there is no single health plan (except perhaps Medicare) representing enough of the market to take on this cost.

Comparative effectiveness research is expensive and takes a long time. The UK's National Institute of Clinical Effectiveness faces serious opposition to its efforts to restrict coverage to more cost-effective therapies. (See my previous post on this issue). Doing good comparative effectiveness research could help allocate precious (and not limitless) resources. This research won't happen without government participation, and probably won't have much impact as long as government payers are prohibited from using this information in coverage decisions. I believe we should fund this research through the Agency for Health Research and Quality, and governmental and nongovernmental payers should be able to use this information when designing coverage.

Thanks to Ben Geisler from our class for sending me a link to this article.

Genomic Medicine: Impact on Overall Medical Cost

From an op-ed in the Boston Globe last month by Michael Leavitt (HHS Sec in last administration) and Professor Raju Kucherlapati of Harvard Medical School:  

A woman with atrial fibrillation, a heart condition, is prescribed the widely used blood-thinning drug warfarin. A $350 genetic test is performed, looking for variations in two specific genes that affect the body's metabolism and response to the drug. Combined with other factors, the test indicates a proper dosage range for her. Thus, with a test that looks at her genetic profile, she is prevented from suffering uncontrolled bleeding or life-threatening blood clots and risk of stroke that can accompany the use of this powerful drug...

In the case of warfarin, for example, adverse events related to dosage problems make this drug a leading cause of drug-related emergency room episodes. More accurate dosing, enabled by a relatively low-cost genetic test, might save as much as $1 billion per year while delivering better-quality care and better health.

[The] decision model evaluated the cost-effectiveness of genotype-guided warfarin dosing for patients with nonvalvular atrial fibrillation and found that for the standard base case (a 69-year-old man with no contraindications to warfarin therapy and the current cost of genotyping of about $400), genotype-guided dosing costs $170 000 more per quality-adjusted life-year gained than standard warfarin dosing.

What's the truth?

The diagnostic and pharmaceutical companies right now price based on the value of a new product.  If society has decided that it is willing to pay $50,000 per Quality Adjusted Life Year (QALY), it's not likely that many vendors will sell their new products at a price that would allow us to gain incremental benefit AND also save money.

The good news is that prices tend to come down over time -- and come down faster and further if there are competitors.  The bad news is that some of our leaders are counting on cost-SAVING from new technology, which is not likely to be realized quickly with our current economic model.

The Impact of United Healthcare Settlement on Health Care Costs

Last week, New York Attorney General Andrew Cuomo announced that he had reached a settlement with United Health Group.   The insurer, which owns software company Ingenix, created the industry standard database which determines how much patients with PPO health plans will be reimbursed when they see "out of network" physicians.  Physician groups have long alleged that this database understates usual and customary fees, and have complained that the insurer has a conflict of interest since it benefits from a low fee schedule.  United agreed to pay  $50 million to help establish a university-run organization to establish an independent database, and admitted no wrongdoing.  Separately, United settled a class action suit over underreimbursement for $350 million. 

Here is how this works.  If I have a PPO and see a physician out of plan and she bills me $500, my insurer will check the Ingenix database. It that database suggests an appropriate price of $200 -- my health plan will only reimburse me 70% of $200 - leaving me with an effective bill of $360.   (Most out of plan benefits also have hefty deductibles - and if I paid the full $360, only $140 of this would be counted toward meeting the deductible.)

This is good consumer protection - since those with insurance usually thought they were purchasing coverage for 70% of the charge, not less than a third!  But how will this impact the cost of medical care? Like many things, it depends.

If providers successfully collected the entire billed fee from patients in this instance, this settlement will have no impact on aggregate cost - but merely shift that cost from out-of-pocket to health plan cost.   Health plans would have to raise their rates, but this would be offset by less consumer health spending.  

If providers routinely wrote off a portion of the consumer bill, though, this settlement would raise the overall cost of health care.  Many providers might add that they need to collect high fees from some payers to subsidize the care they deliver to others who cannot possibly afford to pay full freight.  This includes patients without insurance, and patients insured through state Medicaid programs that often use very low fee for service rates. 

This highlights an underlying problem.   There is a vast difference between billed charge, allowed charge, and actual payment. This difference disadvantages those without insurance coverage, and makes the actual cost of health care very opaque.   

Immunizations and Medical Costs

There has been a lot in the news recently about immunization.  An infectious disease researcher just published a book about the myth that MMR (measles mumps rubella) vaccine causes autism. (Multiple studies have failed to show a connection, but it’s not possible to design a study that absolutely positively proves the lack of a relationship).  This issue has even been covered by  NPR’s This American Life (approximately minute 22 of broadcast) – and the emphasis has been on preventable disease suffered because parents refuse to immunize their children against contagious childhood diseases.  “Herd immunity” is most important, so when children do not receive immunizations, the risk for other children (including those too young for vaccines) increases. 


I’d like to bring up another issue – not as important as the 10 month old covered with measles pox – but important nonetheless.  There are few medical interventions that actually save money.  For instance, doing incremental mammograms is a good idea,  but each additional “quality adjusted life year”(QALY) costs about $58,000 in the health care system.   (Non-Harvard link here) 


Immunizations are the exception to this rule – one of the few medical interventions which both saves money and improves care.   It’s estimated that every $1 spent on an MMR vaccine prevents $21 in medical cost.  (Non-Harvard Link Here)

That’s not the only reason we should aggressively vaccinate our children. But in a society seeking value from the health care system, there are few value propositions as compelling as pediatric immunizations. 

Medical Service Trip To Guatemala -- A bit off-topic

I’ve been in Guatemala for the last week on a medical service trip, delivering health care to Mayans in three highland villages.  I’ll be blogging about managing health care costs over the next few days, but I wanted to share my experience briefly first.


The Guatemala trip was arranged by the Tufts University chapter of the Timmy Foundation, which works to establish sustainable health care in developing countries.  The Timmy Foundation is currently active in Ecuador and Guatemala, and has chapters at 8 colleges.  The Foundation has medical “brigades” from different schools every two months to each site, and its trips include college students and volunteer physicians and pharmacists. It always partners with a local organization to make the efforts sustainable.   In Guatemala, Timmy partners with Pop Wuj, a Spanish language immersion cooperative school that runs health clinics, sponsors scholarships for promising indigenous children, and has other development projects. One current project provides wood stoves to Mayan families, to allow them to cook in their houses without open fires.  This can lower the incidence of asthma and other lung diseases.


We saw patients in the villages of Buena Vista, Xeabaj, Pacaxcoj and in the city of Quetzeltenango, also known as Xela.  Two of these communities had no running water, and one had no electricity.  In some of the communities, few patients spoke Spanish, so we had translation from English to Spanish to Quiché back to Spanish and finally to English.


The Tufts Timmy Foundation Chapter raised about $20,000 which will help Pop Wuj employ a permanent physician and a coordinator to provide care between visits of college students and volunteer clinicians.  Our trip included 20 undergraduate students, four physicians and a pharmacist. The students were hyperorganized, great translaters, and incredibly perceptive – I enjoyed learning from them.  Over a quarter of the group got traveler’s diarrhea during the trip – I’m fondly calling the trip “Sunshine, Service and Cipro.”


A few observations:

1)  The three villages had little access to medical care, but they needed basic necessities, especially running water even more than western-style medical care.  I felt like our fluoride treatments for kids from ages 5-12 and our antiparasitic treatments for all villagers might have been our most important contribution.  Prevention is much more effective than our medical care. 

2)  Dental hygiene is terrible in the villages; many women in their early 20s had such bad teeth that they had trouble eating.  In the US, stressed Medicaid programs often cut dental benefits first – my Guatemala experiences reminds me of the importance of access to dental care and fluoride.

3)  Candy and prepared food is available just about everywhere – and is cheap compared to fresh food.  Soda (with sugar or corn syrup) is also omnipresent, while clean water is difficult to find.   There is good evidence that poor food choices are a cause of increased morbidity in impoverished neighborhoods in the US as well. 

4)  US efforts to protect intellectual property through the Central American Free Trade Agreement (CAFTA) have delayed the introduction of generic drugs in Guatemala.   (See Replogel, Lancet Volume 363, Issue 9421, 15 May 2004, Pages 1612-1613). Of note, the US government denies that CAFTA will have that effect. 

5)  I think a lot about uncertainty in medical care, and how far we go in diagnostic testing to eliminate all uncertainty here in the US. We often use too many laboratory tests and too many imaging studies in an effort to get all the answers we can, even when those answers don’t change care.  In Guatemala, the only diagnostic tests our medical brigade had to offer were our physical examinations, urinalysis, and glucometer blood sugars.   Obviously that’s clinically bad – I wanted to know the thyroid status of a woman on thyroid replacement, the HbAICs of diabetics, and I saw a woman with a thyroid nodule that I would have wanted to ultrasound to be sure it was a cyst. This trip helps remind me of the importance of having good access to laboratory and imaging capability.  But while we need more capability in highland mountain villages in Guatemala, we still need to figure out how to consume fewer resources in the US.


If you’re interested in seeing pictures of our Guatemala trip, they are at this URL.


Thanks for reading on – I’ll be catching up on managing health care costs over the next few days.


A Warning that Decreasing Variation Might Not Save As Many Dollars as We Hope

There is a food fight between researchers at Dartmouth and an economist at Wharton in the early December Health Affairs web edition.   The Dartmouth researchers have reviewed small area variation in Medicare claims data, and concluded that the states and regions with the highest cost also have lower quality.  Extrapolations show that if the lower efficiency areas could match the efficiency of the higher efficiency areas, we would need fewer physicians (by far) and we could save 30% (or more) of our health care bill.  This allows health care policy experts to conclude that we can save enough in health care to provide coverage for all Americans with no incremental cost.  

Katherine Baicker (now of Harvard School of Public Health) and Amitabh Chandra wrote a classic article in 2004 showing an inverse relationship between Medicare cost and quality. The more Medicare spends (think Louisiana and Florida), the worse the statewide quality scores are.   I’ve used their impressive graphics in my lectures, and I’ve seen them in many other talks.   I'm reproducing this correlation below , as pictured in the Cooper paper with explicit notice of different geographies which shows clustering of states by region.  If this is hard to read, double click on it to enlarge the graphic. 


Richard Cooper, a professor at Wharton, has made two pretty effective counter-arguments.  The first is that Medicare spending is often substantially different than non-Medicare spending state-by-state.  For instance, in Mississippi (a high Medicare cost state), 25% of Medicare beneficiaries are disabled, compared to only 10% in North Dakota (a low Medicare cost state).  Turns out that total cost of care in Mississippi is actually relatively LOW – because the non-Medicare payers are paying poorly.  Frankly, high Medicare costs might be a marker in the South for low non-Medicare spending, which is itself associated with the socioeconomic profile that is associated with lower apparent health care quality.


Below is Cooper's graphic showing a proportional relationship between non-Medicare spending and quality - with a slope inverse to that for Medicare spending. 

Cooper’s second point is that by his estimation low quality states consistently have low numbers of physicians – both primary care physicians and specialists.  They might have a worse primary care to specialist ratio – but they still have fewer specialists per capita.  He therefore argues against the assertion that substituting primary care physicians for specialists will necessarily lower costs or raise quality. 


All the analyses of primary care vs. specialists are confounded by rural vs. urban (few specialists in rural states), and the fact that primary care often considers only those trained in family medicine.  Family medicine represents a substantial portion of primary care in the Pacific Northwest and the Midwest – but a very small portion of overall primary care in most of New England.


There are a total of six articles in this series – and a wonkish argument about the validity of multiple regression analysis vs.  isolated correlations.  I went into this set of articles convinced of the Dartmouth Atlas argument that “more is less.”   I finished reading the articles feeling dubious about Cooper’s argument that “more is more,” but feeling far less confident that we can save as many dollars through decrease in variation than we all would hope.