“When extrapolated to the over 33.6 million admissions to U.S. hospitals each year, the results of the study in Colorado and Utah imply that at least 44,000 Americans die each year as a result of medical errors. The results of the New York study suggest that the number may be as high as 98,000. Still, even using the lower estimate, it would make medical errors the 8th-leading cause of death in the nation, exceeding motor vehicle accidents (43,458), breast cancer (42,297), and AIDS (16,516).”

So stated the opening paragraphs of “To Err is Human: Building a Safer Health System (2000),” a report published by The Institute of Medicine in Washington, and understandably, the alarming figures prompted both then President Clinton and Senator Arlen Spector to introduce initiatives dealing with patient safety and medical errors. No doubt, patient safety is an important issue, but even so, taking a closer look at the numbers, it appears as if this may be an example of the end justifying the means.

To begin with, the figures 44,000 and 98,000 are simply estimates made from extrapolation. Without some basic understanding of the makeup of the sample (size, distribution, etc.) and consequently the associated margins of error, the results of such a technique can be next to meaningless.

Second, the actual figures are only for a single year. To report them as a yearly death rate is itself misleading. Without figures from previous years, it is impossible to know whether the error rate is improving or getting worse. Moreover, in strictly statistical terms, there is little meaning in comparing such an estimate to the death rates for motor vehicle accidents, breast cancer, and AIDS, where the figures are based on total count of reported incidences and therefore have a much greater precision and smaller margin of error.

At the same time, however, no one would argue the necessity to reduce the number of deaths caused by preventable errors. As a result, when it comes to figures like these, the general sense seems to be that while the numbers maybe wrong, the message isn’t, in view of which the public is more willing to overlook a few statistical inaccuracies.

More Lies, Damned Lies