The Limits of Comparative Effectiveness Research
July 12, 2011
Public and private payers for health care hope to use comparative effectiveness research (CER) to cut costs without reducing quality of care. CER measures the effects of different drugs or other treatments on a population with the goal of finding out which ones produce the greatest benefits for the most patients. The potential short-term savings are significant, say Tomas J. Philipson of the University of Chicago and Eric Sun of Stanford University.
- For example, antipsychotic drugs represent one of the largest and fastest-growing expenses for Medicaid.
- In 2005, a CER analysis of antipsychotic drugs found little difference between the effectiveness of older, cheaper antipsychotics and that of more expensive "second-generation" drugs.
- Philipson and Sun determined that if reimbursement policies had been changed in response and Medicaid had stopped paying for the more costly drugs, it would have saved $1.2 billion out of the $5.5 billion that it spent on these medications in 2005.
- However, the consequences of this policy shift would have been worse mental health for many thousands of people, resulting in higher costs to society that would equal or outweigh any savings in Medicaid costs.
How can it be that, when a CER study shows no difference between two drugs, limiting coverage for the more expensive drug could actually increase costs? The answer is that in most CER studies, it is the drug or treatment with the larger average effect on an entire population that wins.
- First, individuals differ from one another and from population averages. Therefore, what may be on average a "winning" therapy may simply not work for a large number of patients.
- The second reason is the variance in dependence in patient responses across therapies.
Source: Tomas J. Philipson and Eric Sun, "Blue Pill or Red Pill: The Limits of Comparative Effectiveness Research," Manhattan Institute, June 2011.
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