Physician and journalist Atul Gawande (born 1965) spoke about US healthcare costs when he delivered the commencement address to this year’s graduates of Harvard Medical School.
Medical performance tends to follow a bell curve, with a wide gap between the best and the worst results for a given condition, depending on where people go for care. The costs follow a bell curve, as well, varying for similar patients by thirty to fifty per cent. But the interesting thing is: the curves do not match. The places that get the best results are not the most expensive places. Indeed, many are among the least expensive. This means there is hope—for if the best results required the highest costs, then rationing care would be the only choice. Instead, however, we can look to the top performers—the positive deviants—to understand how to provide what society most needs: better care at lower cost.
Atul Gawande, “Cowboys and Pit Crews“, News Desk blog, The New Yorker, 26 May 2011.
Dr Gawande is a frequent (though passive!) contributor to thought du jour. He is referring to measurement of costs at a point in time, but at different locations. This is done by comparing costs of standard procedures, such as normal childbirth, hip replacement, coronary bypass surgery, et cetera. Measuring changes in costs over time – price inflation – is generally thought to be much more difficult. Via Mark Thoma, here is a quote from an interview of Rochester University economist Mark Bils (born 1958), who studies “the intricacies of price measurement”.
When you look at healthcare expenditures, you see that inflation is extremely rapid, much more rapid than other inflation rates. But we have no idea what the inflation rates for health expenditures really are. We don’t know! You can’t measure quality of healthcare very well.
If I compare healthcare costs today versus in the year 1800, well, I could go out and buy a bunch of leeches today for almost nothing. And I could have the healthcare I had in 1800. If you had a certain condition and you had $10,000 to get treated at today’s health prices, or $10,000 to get treated at 1960s prices with 1960s technology, I don’t think it’s so obvious that people would want to go back in time to get their important health conditions dealt with. In that sense, you say, I don’t know if there’s inflation. It’s pretty hard to say that there’s been a lot of inflation over the long haul in healthcare.
Brent Meyer, “Interview with Mark Bils“, Forefront (Federal Reserve Bank of Cleveland), Spring 2011.
My favourite paper on this subject is an essay that Brookings economist Jack Triplett wrote, with the provocative title “Human Repair and Car Repair”. Triplett believes that measuring the real output of health care is conceptually not so difficult. The main problem is that statistical agencies devote few resources to this task.
Why is measuring health care output so hard? The medical economics literature contains a long list of intimidating and discouraging difficulties. In this paper, I propose to cut through this mostly defeatist list by posing what at first might seem a narrowly-focussed question: Why is health care different from any other analogous service, such as car repair? ….
Jack E. Triplett, “What’S Different About Health? Human Repair and Car Repair In National Accounts and in National Health Accounts“, Brookings Institute, 25 June 1999.
This is a long paper, well written, difficult to summarize, and worth reading. It was published as the first chapter (pp. 15-94) of Medical Care Output and Productivity, edited by David Cutler and Ernst Berndt (University of Chicago Press for the NBER, 2001).
Triplett recently wrote another, shorter essay for The Oxford Handbook of Health Economics.
[P]roductivity in the medical care sector has behaved very differently from other industries, even other services industries: Measured productivity growth in medical care has typically been negative. ….
Few industries have experienced more innovation, so medical care’s negative productivity growth is highly suspect. …. Data on inputs and outputs—indeed, economic data generally—for the health care sector are much less well developed than for many other sectors of the economy, which is bizarre considering the size of health care in most industrialized countries and the importance of the sector. ….
The National Health Accounts produced in many countries have become nearly irrelevant to the current policy debates on medical care costs because they show only who provides the money for health care (consumers, governments, insurance companies) and who gets it (hospitals, doctors, pharmaceutical companies). They do not show what is bought for health care expenditures—treatments for disease. ….
If expenditure growth is contained, is the effect to reduce medical care inflation? Or is it, instead, to reduce the growth of medical care services? We don’t really know. Only after determining this can we move to the next stage and ask whether the growth in the number of medical care services is worth it, a question that has too often been “answered” with a minimal amount of relevant data.
Improving the database for the analysis of medical care productivity deserves high priority. It deserves high priority, not so much because productivity analysis is necessarily that important, but because vital questions of health care policy demand exactly the same data.
Jack E. Triplett, “Health System Productivity“, ch 31 of The Oxford Handbook of Health Economics, edited by Sherry Glied and Peter C. Smith (Oxford University Press, 2011).
This is an excellent paper, but very concise. The link is to a November 2009 draft. I recommend reading it as an update to Tripett’s earlier paper.


