Literature DB >> 11606878

Can utility-weighted health-related quality-of-life estimates capture health effects of quality improvement for depression?

C Donald Sherbourne1, J Unützer, M Schoenbaum, N Duan, L A Lenert, R Sturm, K B Wells.   

Abstract

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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Year:  2001        PMID: 11606878     DOI: 10.1097/00005650-200111000-00011

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  15 in total

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Journal:  Qual Life Res       Date:  2012-03-06       Impact factor: 4.147

2.  Measuring preferences for cost-utility analysis: how choice of method may influence decision-making.

Authors:  Christine M McDonough; Anna N A Tosteson
Journal:  Pharmacoeconomics       Date:  2007       Impact factor: 4.981

3.  A longitudinal comparison of 5 preference-weighted health state classification systems in persons with intervertebral disk herniation.

Authors:  Christine M McDonough; Tor D Tosteson; Anna N A Tosteson; Alan M Jette; Margaret R Grove; James N Weinstein
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4.  Health-related quality of life changes associated with buprenorphine treatment for opioid dependence.

Authors:  Dennis W Raisch; Heather M Campbell; David A Garnand; Mark A Jones; Mike R Sather; Rupali Naik; Walter Ling
Journal:  Qual Life Res       Date:  2011-10-11       Impact factor: 4.147

5.  Evidence on the longitudinal construct validity of major generic and utility measures of health-related quality of life in teens with depression.

Authors:  John F Dickerson; David H Feeny; Gregory N Clarke; Alex L MacMillan; Frances L Lynch
Journal:  Qual Life Res       Date:  2017-11-17       Impact factor: 4.147

6.  Predicting EQ-5D-US and SF-6D societal health state values from the Osteoporosis Assessment Questionnaire.

Authors:  C M McDonough; M R Grove; A D Elledge; A N A Tosteson
Journal:  Osteoporos Int       Date:  2011-04-12       Impact factor: 4.507

7.  Predicting SF-6D utility scores from the neck disability index and numeric rating scales for neck and arm pain.

Authors:  Leah Y Carreon; Paul A Anderson; Christine M McDonough; Mladen Djurasovic; Steven D Glassman
Journal:  Spine (Phila Pa 1976)       Date:  2011-03-15       Impact factor: 3.468

8.  How bad is depression? Preference score estimates from depressed patients and the general population.

Authors:  Jeffrey M Pyne; John C Fortney; Shanti Tripathi; David Feeny; Peter Ubel; John Brazier
Journal:  Health Serv Res       Date:  2009-04-21       Impact factor: 3.402

9.  Converting the SF-12 into the EQ-5D: an empirical comparison of methodologies.

Authors:  Ling-Hsiang Chuang; Paul Kind
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

10.  Predicting SF-6D utility scores from the Oswestry disability index and numeric rating scales for back and leg pain.

Authors:  Leah Y Carreon; Steven D Glassman; Christine M McDonough; Raja Rampersaud; Sigurd Berven; Michael Shainline
Journal:  Spine (Phila Pa 1976)       Date:  2009-09-01       Impact factor: 3.468

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