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Letters

The Economic Value Of Medical Technology

In their Sep/Oct 01 paper, David Cutler and Mark McClellan conclude that improvements to medical technology are worth the costs they incur. The authors’ methods of analysis and forms of argument are problematic and therefore weaken their conclusion.

Their argument relies on their assumption that the value per year of life saved is $100,000. There is, however, no general agreement upon the level of this or other thresholds; large variation exists among acceptable cost-effectiveness thresholds.¹ If the study had used the more conservative threshold of $50,000 per (quality-adjusted) life year (QALY) gained, the cost of many technologies would have been too high to permit justification.²(A quick glance at a cost-effectiveness league table such as the one by the Harvard Center for Risk Analysis identifies such technologies.)³ The paper fails to protect the reader from a fallacy of division—the assumption that if medical technology is "worth it" as a whole, then each technology is also worth it.

It was thus imperative for the authors to arrive at a reliable determination of society’s willingness to pay. Determining this willingness would require deriving the value of a life year for each condition independently; a uniform value of a life year implies a utilitarian approach to resource allocation that has been rejected in many surveys.

The paper also has several methodological shortcomings. For example, when evaluating selective serotonin reuptake inhibitors (SSRIs) and cataract treatment, the authors analyze only one setting, comparing treatment to no treatment. To avoid a selection bias, one must consider all major settings in which the technology is used. In the case of SSRIs this not only includes situations in which a substitution for other treatments such as tricyclic antidepressants has occurred, but also situations where SSRIs have led to an overdiagnosis and overtreatment of depression.

Finally, it is unacceptable to justify major biases and non-adherence to conventions with the notion that conclusions would not change in the light of more detailed analysis. Taking again SSRIs as an example, the paper assumes a maximum of $1,000 for direct treatment costs of depression; this figure is at most half of the cost calculated by Gregory Simon and colleagues.⁴ The authors also did not consider the consequences of not treating depression, which could include hospital admissions

Afschin Gandjour

University of Cologne, Cologne, Germany

NOTES

 

1. N.A. Azimi and H.G. Welch, "The Effectiveness of Cost-Effectiveness Analysis in Containing Costs," Journal of General Internal Medicine 13, no. 10 (1998): 664–669.[Medline]
2. T.T. Lee et al., "Cost-Effectiveness of Screening for Carotid Stenosis in Asymptomatic Persons," Annals of Internal Medicine 126, no. 5 (1997): 337–346[Abstract/Free Full Text]; P. Salzmann et al., "Cost-Effectiveness of Extending Screening Mammography Guidelines to Include Women 40 to 49 Years of Age," Annals of Internal Medicine 127, no. 11 (1997): 955–965[Abstract/Free Full Text]; K.J. Smith and M.S. Roberts, "The Cost-Effectiveness of Sildenafil," Annals of Internal Medicine 132, no. 12 (2000): 933–937[Abstract/Free Full Text]; and D.L. Patrick et al., "Economic Evaluation of Aquatic Exercise for Persons with Osteoarthritis," Medical Care 39, no. 5 (2001): 413–424.[Medline]
3. Harvard Center for Risk Analysis, The CUA Data Base: Standardizing the Methods and Practices of Cost-Effectiveness Analysis, <www.hsph.harvard.edu/organizations/hcra/cuadatabase/intro.html> (6 November 2001).
4. G.E. Simon et al., "Initial Antidepressant Choice in Primary Care. Effectiveness and Cost of Fluoxetine vs. Tricyclic Antidepressants," Journal of the American Medical Association 275, no. 24 (1996): 1897.1902.

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