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Can Utility-Weighted Health-Related Quality-of-Life Estimates Capture Health Effects of Quality Improvement for Depression?

Publication Abstract

Sherbourne, C.D., J. Unutzer, Michael Schoenbaum, N. Duan, L.A. Lenert, R. Sturm, and K.B. Wells. 2001. "Can Utility-Weighted Health-Related Quality-of-Life Estimates Capture Health Effects of Quality Improvement for Depression?" Medical Care, 39(11): 1246-1259.

BACKGROUND. Utility methods that are responsive to changes in desirable outcomes are needed for cost-effectiveness (CE) analyses and to help in decisions about resource allocation. OBJECTIVES. Evaluated is the responsiveness of different methods that assign utility weights to subsets of SF-36 items to average improvements in health resulting from quality improvement (QI) interventions for depression. DESIGN. A group level, randomized, control trial in 46 primary care clinics in six managed care organizations. Clinics were randomized to one of two QI interventions or usual care. SUBJECTS. One thousand one hundred thirty-six patients with current depressive symptoms and either 12-month, lifetime, or no depressive disorder identified through screening 27,332 consecutive patients. MEASURES. Utility weighted SF-12 or SF-36 measures, probable depression, and physical and mental health-related quality of life scores. RESULTS. Several utility-weighted measures showed increases in utility values for patients in one of the interventions, relative to usual care, that paralleled the improved health effects for depression and emotional well being. However, QALY gains were small. Directly elicited utility values showed a paradoxical result of lower utility during the first year of the study for intervention patients relative to controls. CONCLUSIONS. The results raise concerns about the use of direct single-item utility measures or utility measures derived from generic health status measures in effectiveness studies for depression. Choice of measure may lead to different conclusions about the benefit and CE of treatment. Utility measures that capture the mental health and non-health outcomes associated with treatment for depression are needed.

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