Demography drives Medicare disparities

New research by the Brookings Institution suggests that socioeconomic factors can account for most of the geographical variation in Medicare spending.

These findings contradict previous research that claimed geographic differences in “practice styles” are the main reason for differences in Medicare spending.

Louise Sheiner, Brookings senior fellow and director of the Hutchins Center on Fiscal and Monetary Policy, says her research specifically challenges the Dartmouth Atlas of Health Care’s contention that medical practice styles – that is, “the extent and intensity of medical interventions” – are randomly distributed.

Her conclusions in “Why Geographic Variation in Health Care Spending Can’t Tell Us Much about the Efficiency or Quality of our Health Care System,” call into question “the claim that the U.S. could save up to $700 billion in health care waste and inefficiency if all providers were to emulate the practices of low-costs states.”

Sheiner employed a state-level approach in her research, in contrast to the individual-level approach used by Dartmouth researchers. This enabled her to determine that “states with similar demographic characteristics have similar levels of real beneficiary Medicare spending.”

“Thus, what the Dartmouth researchers have deemed as differences in ‘practice styles’ are not randomly distributed, but are instead closely linked to population characteristics,” she writes.

“States where Medicare spending is high are very different in multiple dimensions from states where Medicare spending is low. And thus it is difficult to isolate the effects of differences in health spending intensity from the effects of the differences in the underlying state characteristics.”

Nancy Foster, vice president for quality and patient safety policy at the American Hospital Association (AHA), says the Brookings findings “are consistent with what we are seeing as well.”

AHA conducted its own analysis of geographic variation in healthcare spending about 18 months ago.

“What we saw from gathering data from CDC and others who track differences in the health status of people across the country were patterns of disease that were consistent with the patterns of higher expenditures,” Foster said. “It was very clear to us that the incidents of diabetes, the incidents of tobacco use, the incidents of obesity, and a number of other conditions really did impact the number of healthcare services that people required.”

Foster says larger socio-demographic factors must be considered when assessing the quality of care offered by hospitals and other providers.

“When you think of virtually any outcome measure, the question should be, ‘Are there factors associated with the health status, or availability of health services or other community factors that will have an impact on this over and above what the hospital itself is able to do?’” she said.

AHA believes “there are some good starting places” for this approach, Foster said.

“When we look at readmissions rates, we think one can use census data to identify various factors that may be linked to an increased likelihood of a patient being readmitted. We have urged CMS [Centers for Medicare & Medicaid Services] to look at that,” she noted. “The same thing goes for measuring Medicare spending per beneficiary. We think that probably should be assessed for underlying socio-demographic factors that affect performance.”