McAllen Texas

 

Dangerous Assumptions in Health Reform

Attribution to :  DMCB, a brainy and literature-based resource by Jaan Sidorov

Is it time to review some of the basic tenents upon which the Accountable Care Act was passed?

Remember the Atul Gawande and McAllen Texas fracas? That New Yorker article captured the national spotlight and put a harsh glare on areas of the United States that had unexplained high rates of health care utilization. Dr. Gawande blamed the local culture of fee-for-service private practice, while the Disease Management Care Blog wondered if it was a statistical fluke and/or the burdens of a chronically ill population.

The article by Atul Gwande was published in the New Yorker Magazine and criticized by DMCB, other highly visible publications, duplicated, quoted, tweeted and distributed widely. The analytic gurus and health officials were suspicious that this analysis was flawed. Statistics can be mis-applied at times to prove anything you want, or innocently yield false results. In this case the goal of finding disparities in health costs was solely based upon Medicare's needs, and misinterpreted by all because it was restricted to billings to Medicare. Private insurer's and cash payments were left out of the data analyzed for the study.

McAllen Texas and Healthcare Utilization: A Function of Statistical Variation, Not Poor Policy

Not mentioned is that both communities are heavily influenced by demographics (high cohort of Latinos).

Some of the Affordable Care Act was based on this flawed study.

“It took a second look when that hapless locale was seized upon by Peter Orszag of the Office of Management and Budget (OMB), Consumer Reports and some notable blogs as the symbol for all that ails American healthcare. Commentators are accusing the ‘McAllens of this country’ of consciously and unconsciously economically ripping off the system with precious little quality to show for it.

Yet, the dubious DMCB (Disease Management Care Blog) and also Health Train Express at that time remained unexcited about Dr. Gawande’s faux discovery and disappointed that others haven’t considered the most likely cause of McAllen’s outlier status. Is there something really special about McAllen or is something else going on?

It took a while, but the Disease Management Care Blog finally caught up with this follow-up study on the contrast in health care costs between the Texas towns of McAllen and El Paso. “

It is the nature of our minds to believe there must be something “causing” outliers. In other words, there must be something about McAllen that attracted all those coins, right? The DMCB, in reading Dr. Gawande’s article, thinks that may be true in Miami (which is number 1 in the U.S), but it doesn’t think that's the case for McAllen as described in the New Yorker magazine article. The gumshoe M.D. reporting clearly shows the McAllen providers are mystified by their status. It’s not as though they planned to take advantage of the system. In fact, they didn’t. That’s because it’s all random.

This is important because most healthcare providers involved in quality improvement learned long ago that ‘identifying’ and then ‘managing’ outliers with targeted interventions is a poor way to promote overall system improvement. Outliers naturally regress to the mean over time and they're not the problem anyway. Rather, the trick is to reduce overall variation around the mean (reducing the standard deviation) and to move all providers toward a better average level of behavior. That’s a lot of complicated work that, frankly, isn’t as enthralling to editors or the readers of The New Yorker. It's too much work.

DMCB summarized,

“While popular media can be forgiven for using simplistic descriptions of extreme outlier anedotes to pander to a political agenda, the DMCB isn’t too sure about Dr. Gawande. However, the DMCB is most frightened by potential reaction of the OMB. Short of complete central planning for the entire health care system, random distributions of performance, expense, quality, claims, satisfaction and countless other measures around a mean will be unavoidable. Of all persons, Dr. Orszag should understand that outliers are an ironic certainty, not evidence of malfeasance. Most are anomalies, not proof of anything. They are, in short, interesting, but not lessons and certainly not the stuff of policy making. “

 

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