data, use and misuse -Sabermetrics: The Solution to the Health Care Crisis?

In the past decade, baseball has experienced a data-driven information revolution. Numbers-crunchers now routinely use statistics to put better teams on the field for less money. Our overpriced, underperforming health care system needs a similar revolution.

Billy Beane, Newt Gingrich, and John Kerry, “How to Take American Health Care From Worst to First,” New York Times, October 24, 2008

When we talk about the health care crisis, my wife often comments “ No one seems to know what’s going on, or what to do about it.”

Well, Loretta, I have news for you.

Billy Beane, a baseball guru believed to be responsible for the success of the Tampa Bay Rays and other low-paid, high performing teams; Newt Gingrich, the all-knowing, all-feeling conservative commentator: and Senator John Kerry, a liberal who knows a thing or two, about health care, says the answer to our health care problem is sabermetrics.

Sabermetrics in Baseball

Sabermetrics? Yes, sabermetrics, the use of obscure statistics to predict and improve performance, even among unknown players. It’s the numbers not the names that count. In the case of baseball, sabermetrics is made up of such things as WHIP (walks and hits per inning), VOPR (value over replacement player), or runs created – a number derived from the formula ( (hits + walks X total bases)/ (at bats + walks).

In baseball, the beauty of sabermetics is you can predict what to do, what risks to take, what players to draft, what line-up to use at much lower costs per player with superior results.

Sabermetrics in Health Care

In health care, our trio of non-medical experts explain, you can use sabermetrics to pick the right doctor, and identify clinical approaches that work statistically, based on mega-analyses of mega- studies rather than on informed opinion, personal observation, or tradition.

I would disagree Beane, Gingrich, and Kerry, on one point. There is nothing “obscure” about the information doctors could collect to improve care. It is well known, for example, about the data needed to avoid vascular complications in the metabolically related diseases of hypertension, hyperlipidemias, diabetes, health disease, and stroke – which cause roughly 50% of deaths in America.. Once you know a patient’s blood pressure, total cholesterol, HDL and LDL cholesterol, and Hemoglobin A-1C, you can treat the patients accordingly and cut deaths from vascular complications dramatically.

Access to Evidence-Based Data

Our health system, the three baseball aficionados argue, would be much better and much cheaper if doctors had “better access to concise, evidence-based medical information.” No question of that. The cost of routinely bringing this data to patients’ side isn’t mentioned, nor is how we’re going to pay for it or what the savings might be.

The three amigos hasten to add,

“Evidence-based health care would not strip doctors of their decision-making authority nor replace their expertise. Instead, data and evidence should complement a lifetime of experience, so that doctors can deliver the best quality care at the lowest possible cost.”

The operative word here is “should.” But what about doctors who take exception to the rules and who decides to treat the patient as an individual rather than a statistic? People, after all, die or get well as unique individuals not as statistics. And what about the thesis of “personalized medicine, “ which says different people with different genomes respond differently no matter what clinical studies show abut the “average” patient?

Abandoning Tradition for Data

But I digress. It may be true that dispassionate neutral data can complement a manager’s or baseball executive’s judgment as is the case with the Tampa Bay Rays and produce superior results at a lower cost.

And it may be,

“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.”

That’s The Direction We’re Headed.

The sabermetric crowd is at the gates of clinical care, waving Health 2.0 banners, crying out for a National Institute of Comparative Effectiveness, calling for Pay-For-Performance, insisting that widespread EMR installation will cut costs, and heralding the glories of predictive modeling. And health care enterprises like the Cochran Collaboration, Kaiser-Permanente, and Intermountain Healthcare has shown impressive results.

A systems approach to treating disease may improve care based on statistical evidence, but will it save money? After all, doctors will have to order more tests to collect the right data. And preventing early deaths will prolong life which will result on spending more on treating the elderly. But in health care, it’s not about saving money. It’s about the right thing to do.

Still

Still, after the collapse of our financial system, with the failure of a vast array of financial geeks bearing algorithmic rifts, I’m dubious about data-engineering. And after the failure of managed care, with its huge data depositories, to control clinical behavior and improve quality.I remain skeptical.

I suppose care can be reduced to a numbers game. But as a patient, I would rather not be reduced to a number – or a set of numbers. Information technologies are always ahead of their interpretation or implementation. And hope of what might work may be beyond the scope of data.