Information Sets

Faulty Sampling

A recent article in the NYT, “Weighing Medical Costs of End-of-Life Care” by Reed Abelson, uses the cases of two hospitals, UCLA and the May Clinic, to discuss the issue of how to provide cost effective medical care:

[C]ritics in the Obama administration and elsewhere who talk about how much money the nation wastes on needless tests and futile procedures. They like to note that U.C.L.A. is perennially near the top of widely cited data, compiled by researchers at Dartmouth, ranking medical centers that spend the most on end-of-life care but seem to have no better results than hospitals spending much less…

According to Dartmouth, Medicare pays about $50,000 during a patient’s last six months of care by U.C.L.A., where patients may be seen by dozens of different specialists and spend weeks in the hospital before they die. By contrast, the figure is about $25,000 at the Mayo Clinic in Rochester, Minn., where doctors closely coordinate care, are slow to bring in specialists and aim to avoid expensive treatments that offer little or no benefit to a patient…

According to Dartmouth, Medicare pays about $50,000 during a patient’s last six months of care by U.C.L.A., where patients may be seen by dozens of different specialists and spend weeks in the hospital before they die. By contrast, the figure is about $25,000 at the Mayo Clinic in Rochester, Minn., where doctors closely coordinate care, are slow to bring in specialists and aim to avoid expensive treatments that offer little or no benefit to a patient…By some estimates, the country could save $700 billion a year if hospitals like U.C.L.A. behaved more like Mayo. High medical bills for Medicare patients’ final year of life account for about a quarter of the program’s total spending. Under the House health care legislation pending in Congress, hospitals providing more cost-effective care would be rewarded, while hospitals identified as high-cost centers might even be penalized, perhaps receiving lower payments from the government...

[T]he Dartmouth end-of-life analysis … considers only the costs of treating patients who have died. Remarkably, it pays no attention to the ones who survive … The Dartmouth analysis prompted [another] study [by UCLA affiliates] of why some hospitals spent so much more on dying patients than others and what they got from their efforts … What they found seemed to contradict the Dartmouth thesis. The hospital that spent the most on heart failure patients had one-third fewer deaths after six months of an initial hospital stay … When looking at all patients hospitalized for heart failure, for example, the variation in use of resources was 27 to 44 percent lower than when they looked at only the patients who died...

[UCLA affiliates also noted] that there are also fundamental socioeconomic differences between patients in the poorer sections of Los Angeles and those in the Mayo Clinic’s small and solidly middle-class hometown of Rochester, Minn. … [and] health care costs are significantly higher in areas of poverty…

“Sometimes more medical care is better … but the question is when.”

The discussion in the article highlights two critical errors, confusing information sets and comparing disparate samples, which frequently pop up in data analyses, and which serve to muddle, if not completely invalidate, the analyses’ reported results.