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J Ment Health Policy Econ. 2012 Dec;15(4):171-8.

Assessing the comparative-effectiveness of antidepressants commonly prescribed for depression in the US Medicare population.

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Department of Health Policy and Management, University of Pittsburgh, Pittsburgh, PA 15261, USA.



Depression is among the most common chronic illnesses in the US elderly Medicare population, affecting approximately 11.5% of beneficiaries with estimated costs of about USD 65 billion annually. Patients with depression are typically treated with antidepressants - most commonly the Selective Serotonin Reuptake Inhibitors (SSRIs). SSRIs vary substantially in their costs, side effect profiles and convenience of use. All these factors might affect medication adherence and subsequently down-stream medical costs.


To assess the comparative-effectiveness of three antidepressants (escitalopram, citalopram, sertraline) commonly-prescribed for depression in Medicare.


We used pharmacy and medical claims data for a 5 percent national random sample of Medicare beneficiaries who were diagnosed with depression in 2008 and followed until 12/31/2009. Key measures included drug spending, medication adherence to antidepressants, down-stream non-drug medical costs at three levels: all, psychiatric and depression related costs. Three methods were conducted to test robustness: generalized linear regression (GLM), propensity score matching, and an instrumental variables (IV) approach. For the instrumental variables approach, we used a two-stage residual inclusion model, using geographic variation in the use of the various drugs as instruments. Specifically, we calculated the ratio of the number of individuals who used each drug to the total number of individuals using any antidepressants at the 306 Dartmouth hospital-referral regions.


The regression and the propensity score matching method each showed that patients using escitalopram had significantly worse adherence, higher drug costs, and higher medical costs than patients using either citalopram or sertraline. However, our IV analysis yielded different results. While drug costs remained significantly higher for escitalopram patients, we found that escitalopram users had lower non-drug medical spending than patients who used citalopram, which was enough to offset the higher drug costs. The instrumental variables results also suggested that sertraline users had lower non-drug medical costs than citalopram users. The differences between sertraline and escitalopram were not statistically significant for medical spending, but sertraline users had lower drug costs and better adherence than escitalopram users.


The IV method yielded somewhat different results than the GLM regressions and the propensity score matching methods. Once we controlled for selection bias using the instrumental variables, we found that escitalopram is actually associated with lower medical spending. One interpretation is that the IV approach mitigates selection biases due to unobserved factors that are not controlled in regular regressions. However, one conclusion remains the same: in every model, we found that sertraline was at least as cost-effective as or more cost-effective than the other drugs.


Potential unobserved factors affecting the choice of three antidepressants are possible.


All methods indicated that sertraline is the most cost-effective drug to treat depression. Substantial savings to Medicare could be realized by using more cost-effective antidepressants such as sertraline.


Geographic variation in the use of prescription drugs has been underutilized as an instrumental variable in comparative-effectiveness research. Our study demonstrates that it can help to control for selection biases in observational data.

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