Doctors’ Decision-Making: Regression Proof?

By Kate Greenwood
[Cross-posted at Health Reform Watch]

As I have blogged about before, last year, in Kaiser v. Pfizer, the First Circuit joined the handful of courts to have approved a causal chain of injury running from a pharmaceutical company’s fraudulent promotion, through the prescribing decisions of thousands of individual physicians, to the prescriptions for which a third-party payer paid.  To establish but-for causation in the case, Kaiser submitted an expert report and testimony from Dr. Meredith Rosenthal, a health economist at the Harvard School of Public Health. Dr. Rosenthal conducted a regression analysis to determine the portion of physicians’ prescribing of the drug Neurontin that was caused by the defendant’s fraudulent promotion, arriving at percentages ranged from 99.4% of prescriptions for bipolar disorder to 27.9% of prescriptions for migraine.

Pfizer argued that Dr. Rosenthal’s regression analysis should not have been admitted (and at least suggested that such an analysis should never be admitted in a third-party payer case) because regression analysis could not “take into account the patient-specific, idiosyncratic decisions of individual prescribing physicians.” Dr. Rosenthal’s report, the company argued, “merely demonstrated ‘correlation’ and not ‘causation.’”  The First Circuit disagreed, upholding the lower court’s determination that the challenged evidence was admissible under Federal Rule of Evidence 702, because “regression analysis is a well-recognized and scientifically valid approach to understanding statistical data” and because it “fit” the facts of the case.

Eric Alexander, a partner at Reed Smith, made a similar argument to Pfizer’s when he critiqued a decision issued in July in a third-party payer case in the Eastern District of Pennsylvania. Writing at the Drug and Device Law blog, Alexander criticized the court for failing to address “the fundamental—to us—issue of whether an economist [Dr. Rosenthal was the plaintiff’s expert in that case, too] can ever determine why prescriptions were written.”  Alexander points out that “[t]o get to millions of dollars of revenue from prescriptions, many physicians have to prescribe the drug to many patients[,]” and those physicians can “pretty much do what they want[.]” Economists, Alexander argues, should not be allowed to by-pass this complexity and simply “assume” causation.

I would argue that, as idiosyncratic as physician decision-making may be, it is not uniquely so.  Read More