Regional Variation in Medicare Spending and Risk Adjustment

What is the key driver of regional variation in Medicare spending? According to a paper by Reschovsky Hadley, and Romano (2013), the answer is regional variation in patient health.

Two key casemix adjustment methods—controlling for patient conditions obtained from diagnoses on claims and expenditures of those at the end of life—were evaluated. We failed to find evidence of bias in the former approach attributable to area differences in physician diagnostic patterns, as others have found, and found that the assumption underpinning the latter approach—that persons close to death are equally sick across areas—cannot be supported. Diagnosis-based approaches are more appropriate when current rather than prior year diagnoses are used. Population health likely explains more than 75% to 85% of cost variations across fixed sets of areas.

The leaders of the Dartmouth Atlas series of papers disagrees. They believe that patients in areas that practice more intensive medicine will receive more medical care, which leads to more claims and thus more diagnosis codes to be used in their risk adjustment model. They write

In this case, the authors’ use of the HCC billing codes would falsely “explain” the more aggressive cardiologist’s behavior as the consequence of poor health status, rather than attributing it correctly to intensive physician behavior.

Their response also cites an IOM study that says:

Although a non-trivial amount of geographic variation can be explained by specific demographic and, potentially, health status variables, a substantial amount of variation remains unexplained.


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