The purpose of this study was to estimate the incremental cost-effectiveness of a depression quality improvement intervention in a representative sample of patients from community primary care practices. This article provides a unique contribution to the cost-effectiveness of depression treatment literature for 2 reasons. First, the QALYs used in this analysis are derived from a generic HRQL instrument, the SF-36, as recommended by the Panel on Cost-Effectiveness in Health and Medicine.16
In contrast, other depression CE analyses were based on utility weights assigned to depression-specific outcomes,34,35,38–40
or based solely on depression-specific outcomes such as successfully treated cases41
or clinician ratings of improvement.42
Second, the QALYs used in this analysis are based on a total of 9,000 possible SF-36 health states.24
In contrast, the depression treatment CE analysis that used the SF-12 as a generic HRQL measure limited itself to only 6 SF-12 depression-specific health states.27
Among patients beginning a new treatment episode, the mean incremental QALY saved in the main analysis was 0.041, which is in the range considered clinically significant for patients with chronic physical health problems.43
The main analysis mean CE ratio was $15,463, which is less than (more favorable than) the commonly used CE thresholds of $20,000 and $50,000 per QALY.44,45
In sensitivity analyses, the range of CE ratios was from $11,341 to $19,976 per QALY. All of the sensitivity analyses except the worst-case scenario resulted in CE ratios less than the more conservative CE ratio threshold of $20,000 per QALY.46
The consistency of these results supports the robustness of the model. In addition, we would expect the intervention costs to decrease as more patients receive the intervention, because the marginal cost of the intervention (cost of treating an additional subject) would be less than the average intervention cost used to calculate the above CE ratios.
Our estimates of the incremental cost-effectiveness of the depression intervention versus usual care for depression are consistent with previous estimates of the cost-effectiveness of depression interventions. The following CE ratios are adjusted to 2000 dollars to facilitate comparison with the results of our study. Lave et al. reported CE ratios for a nortriptyline protocol versus usual care in primary care settings of $10,632 to $17,857 per QALY and higher ratios for interpersonal psychotherapy versus usual care.38
Simon et al. reported a CE ratio of $22,748 per QALY for a depression management program for high utilizers of medical care.35
Schoenbaum et al. reported a CE ratio range of $10,143 to $22,986 per QALY for a Partners in Care quality improvement cognitive therapy intervention.27
In addition, our main analysis mean CE ratio ($15,463 per QALY) indicates that this intervention is a good or better healthcare “value” compared to other commonly implemented primary care interventions. For example, CE ratios (adjusted to 2000 U.S. dollars) for some common primary care interventions include: $2,271 for pneumonococcal vaccine for the elderly; $8,313 for smoking cessation counseling; $14,015 for treatment of severe hypertension in men; $28,552 for treatment of mild hypertension in men; and $36,428 for chronic obstructive pulmonary disease rehabilitation.47
Compared to these primary care CE ratios, the value of this primary care depression intervention is similar to that of the treatment of severe hypertension.
Although patients came from community primary care practices across the country, the health outcomes achieved by this brief intervention need to be replicated with a broader range of physicians and ethnically diverse patients to determine if the observed incremental QALYs are generalizeable to other health care settings. The advantages of converting the SF-36 to QALYs include the combination of physical and mental health symptoms and functioning from a well-validated and commonly used health status measure into a single quality-adjusted score as recommended for use in health care economic analyses.16,48
A limitation of this SF-36 to QALY conversion model is the unrepresentative and relatively small British sample from which the SF-36 quality-adjustment weights were derived; however, available evidence suggests that these factors should not introduce substantial bias into the analysis.49,50
An additional limitation of this SF-36 to QALY conversion model could be that the health-related quality-of-life data do not include all the relevant domains of depression symptoms and treatment. An alternative approach is to collect utility weights for current health from each subject over time. However, this approach may limit generalizability.
We recognize that patients do not provide perfect estimates of health care utilization; however, the use of administrative data to capture service use was not feasible, because such data did not exist for uninsured participants, and insured participants were enrolled in 65 different health plans. Previous methodological research for 6-month self-report of healthcare utilization found no associations between patient sociodemographic or health indicators and self-report health care utilization discrepancies.51
In addition, we found no preintervention differences in health care costs (see ). Therefore, we had no reason to expect differential underreporting in the enhanced and usual care patients. We also did not account for all possible health care costs because we did not include diagnostic testing, nonpsychotropic medications, and inpatient service use. While the skewed cost distribution potentially reduced our ability to draw definitive conclusions about how the intervention affected costs, it was encouraging that when we repeated the analyses without the 2 highest- and 2 lowest-cost subjects, the overall results were unchanged, i.e., the mean CE ratio was less than $20,000 per QALY. We also recognize that the accuracy of the results may have been affected by missing data. To address this problem, we used nonresponse weights to account for the probability of enrollment and attrition over time; however, we cannot know the full extent to which this adjustment was successful.52
In summary, this study presents a CE analysis of a primary care depression intervention using a quality-adjusted generic effectiveness measure. The mean incremental CE ratio for this primary care depression intervention is very cost-effective relative to commonly delivered primary care interventions and commonly used CE ratio thresholds. On the basis of these results, this intervention should be implemented for depressed primary care patients beginning a new treatment episode.