Healthcare, Baseball, and Operations Research

The New York Times had an op-ed today about health care written by Billy Beane, Newt Gingrich, and John Kerry.  Billy is the general manager of the Oakland Athletics baseball team and is the primary subject of the book Moneyball, which looked at how a new look at statistics affects a baseball team’s decisions.  What a strange group of coauthors!  Gingrich and Kerry are politicians from the opposite sides of the political spectrum.  My wife (who pointed out the article to me) thought Gingrich and Kerry were strange coauthors:  add in Beane and you are verging on an alternative universe.

The authors argue that health care has got to take a better look at the data, just like baseball teams look at player data.

Remarkably, a doctor today can get more data on the starting third baseman on his fantasy baseball team than on the effectiveness of life-and-death medical procedures. Studies have shown that most health care is not based on clinical studies of what works best and what does not — be it a test, treatment, drug or technology. Instead, most care is based on informed opinion, personal observation or tradition.

They give a number of examples on what happens when people really look at data:

…a health care system that is driven by robust comparative clinical evidence will save lives and money. One success story is Cochrane Collaboration, a nonprofit group that evaluates medical research. Cochrane performs systematic, evidence-based reviews of medical literature. In 1992, a Cochrane review found that many women at risk of premature delivery were not getting corticosteroids, which improve the lung function of premature babies. Based on this evidence, the use of corticosteroids tripled. The result? A nearly 10 percentage point drop in the deaths of low-birth-weight babies and millions of dollars in savings by avoiding the costs of treating complications.

They conclude with a call for looking at the stats:

America’s health care system behaves like a hidebound, tradition-based ball club that chases after aging sluggers and plays by the old rules: we pay too much and get too little in return. To deliver better health care, we should learn from the successful teams that have adopted baseball’s new evidence-based methods. The best way to start improving quality and lowering costs is to study the stats.

The authors are clearly right.  There seems to be great value to looking at the statistics, and this is a necessary step towards rationalizing the system.  The key is making better decisions.  Some of these decisions seem pretty obvious.  But as the decision making gets more complicated, operations research comes into play.  To go back to the baseball analogy, Beane discovered that players with high “on-base percentage” were undervalued by the market, who were paying big money for sluggers (players who hit home runs) instead.  An obvious better decision is to buy up more of the undervalued players.  A more complicated decision would be to form a team that maximized overall output for a given budget constraint.  More complicated still would be forming a team relative to a budget constraint that was affected by team performance.  These more complicated decisions are not the result of a simple rule (“Buy high OBP players”) but rather the result of much more complicated models.

Managing health care, by its nature, requires complicated decision processes.  And that is where operations research comes in (and why I think OR in health care and medicine are two great areas for our field).

3 thoughts on “Healthcare, Baseball, and Operations Research”

  1. Some of the comments attached to the article merit a read as well. It becomes clear reading them that (1) evidence-based medicine (as the term is used here) is just a part of what is necessary to improve US healthcare; and (2) it is possible to mis-use “evidence-based medicine” as well.

    OR (even more than most science) cannot be conducted independent of context. The goals of the sponsoring agent matter. Insurance companies, patients, doctors, and public health officials are all likely to have quite different objectives and hence reach quite different decisions even when using the same data and even when the data is of the best possible quality.

  2. For those of you interested in a IT centric view of health care, I encourage you to read the GeekDoctor’s blog, The author, John Halamka, is CIO of CareGroup Health System, Dean of Technology at Harvard Medical School and an ER MD.

    From his recent open letter to the presidential candidates, “The U.S. spends 43 cents per capita on health-care IT, compared with $193 per capita in the U.K.”

    As someone who has been recently introduced to statistical analysis in US helath care, I find it amazing how the lack of electronic medical records impedes progress in improving US health care.

    New evidence requires new clinical studies which require time and lots of money. Wide adoption of electronic records would enable virtual studies and greatly increase the body of evidence in medical practice.

  3. As a veteran fantasy player and health care expert, I agree! If Tony Romo re-injures his pinky, I’ll know it in less than 5 minutes. If a client has a major medical claim, I may not know it at all.

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