Literature DB >> 15569883

Cost-utility analysis studies of depression management: a systematic review.

Paul A Pirraglia1, Allison B Rosen, Richard C Hermann, Natalia V Olchanski, Peter Neumann.   

Abstract

OBJECTIVE: Depression is common, costly, treatable, and a major influence on quality of life. Cost-utility analysis combines costs with quantity and quality of life into a metric that is meaningful for studies of interventions or care strategies and is directly comparable to measures in other such studies. The objectives of this study were to identify published cost-utility analyses of depression screening, pharmacologic treatment, nonpharmacologic therapy, and care management; to summarize the results of these studies in an accessible format; to examine the analytic methods employed; and to identify areas in the depression literature that merit cost-utility analysis.
METHOD: The authors selected articles regarding cost-utility analysis of depression management from the Harvard Center for Risk Analysis Cost-Effectiveness Registry. Characteristics of the publications, including study methods and analysis, were examined. Cost-utility ratios for interventions were arranged in a league table.
RESULTS: Of the 539 cost-utility analyses in the registry, nine (1.7%) were of depression management. Methods for determining utilities and the source of the data varied. Markov models or cohort simulations were the most common analytic techniques. Pharmacologic interventions generally had lower costs per quality-adjusted life year than nonpharmacologic interventions. Psychotherapy alone, care management alone, and psychotherapy plus care management all had lower costs per quality-adjusted life year than usual care. Depression screening and treatment appeared to fall within the cost-utility ranges accepted for common nonpsychiatric medical conditions.
CONCLUSIONS: There is a paucity of literature on cost-utility analysis of depression management. High-quality cost-utility analysis should be considered for further research in depression management.

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Year:  2004        PMID: 15569883     DOI: 10.1176/appi.ajp.161.12.2155

Source DB:  PubMed          Journal:  Am J Psychiatry        ISSN: 0002-953X            Impact factor:   18.112


  22 in total

1.  Do ultra-short screening instruments accurately detect depression in primary care? A pooled analysis and meta-analysis of 22 studies.

Authors:  Alex J Mitchell; James C Coyne
Journal:  Br J Gen Pract       Date:  2007-02       Impact factor: 5.386

2.  Oleptro™ (trazodone hydrochloride) extended-release tablets.

Authors: 
Journal:  P T       Date:  2011-02

3.  Establishment of an animal model of depression contagion.

Authors:  Matthew Boyko; Ruslan Kutz; Julia Grinshpun; Vladislav Zvenigorodsky; Shaun E Gruenbaum; Benjamin F Gruenbaum; Evgeni Brotfain; Yoram Shapira; Alexander Zlotnik
Journal:  Behav Brain Res       Date:  2014-12-15       Impact factor: 3.332

Review 4.  Depression care for the elderly: reducing barriers to evidence-based practice.

Authors:  Kathleen Ell
Journal:  Home Health Care Serv Q       Date:  2006

5.  How might yoga help depression? A neurobiological perspective.

Authors:  Patricia Anne Kinser; Lisa Elane Goehler; Ann Gill Taylor
Journal:  Explore (NY)       Date:  2012 Mar-Apr       Impact factor: 1.775

6.  A New Method for Inducing a Depression-Like Behavior in Rats.

Authors:  Vladimir Zeldetz; Dmitry Natanel; Matthew Boyko; Alexander Zlotnik; Honore N Shiyntum; Julia Grinshpun; Dmitry Frank; Ruslan Kuts; Evgeni Brotfain; Jochanan Peiser
Journal:  J Vis Exp       Date:  2018-02-22       Impact factor: 1.355

7.  Personality traits and health-related quality of life in patients with mood and anxiety disorders.

Authors:  Annemieke van Straten; Pim Cuijpers; Florence J van Zuuren; Niels Smits; Marianne Donker
Journal:  Qual Life Res       Date:  2006-10-11       Impact factor: 4.147

Review 8.  The estimation of utility weights in cost-utility analysis for mental disorders: a systematic review.

Authors:  Michael Sonntag; Hans-Helmut König; Alexander Konnopka
Journal:  Pharmacoeconomics       Date:  2013-12       Impact factor: 4.981

9.  Are depressive symptoms associated with cancer screening and cancer stage at diagnosis among postmenopausal women? The Women's Health Initiative observational cohort.

Authors:  Arpita Aggarwal; Karen Freund; Alicia Sato; Lucille L Adams-Campbell; Ana Maria Lopez; Lawrence S Lessin; Judith Ockene; Robert B Wallace; Carla D Williams; Denise E Bonds
Journal:  J Womens Health (Larchmt)       Date:  2008-10       Impact factor: 2.681

10.  Cough up for just a cup of coffee: Pharmacoeconomics of depression.

Authors:  G Swaminath
Journal:  Indian J Psychiatry       Date:  2008-01       Impact factor: 1.759

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