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Published Online: 1 September 1999

A Community Study of Depression Treatment and Employment Earnings

Abstract

OBJECTIVE: Although treatment for major depression has been shown to reduce the costs of lost earnings resulting from lost work days, research has not demonstrated whether the reduction fully offsets the costs of treatment for the disorder. METHODS: A statewide cohort of community residents with recent major depression, dysthymia, or substantial depressive symptoms was recruited and interviewed at baseline and at six-month and 12-month follow-ups. The cost of lost earnings was measured by lost work days multiplied by subjects' wage rates. Cost of treatment for depression was approximated using charges abstracted from provider and insurance records. Net economic cost, defined as the sum of changes in lost earnings and depression treatment costs, was examined in multiple regression analyses. RESULTS: After the analyses controlled for sociodemographic characteristics, baseline severity of depression, and comorbidity, no statistically significant effect of depression treatment on net economic cost was found. This finding suggests that the cost of depression treatment was fully offset by savings from reduction in lost work days. Results from sensitivity analyses in multiple alternative scenarios support the same conclusion. CONCLUSIONS: The finding of a full offset of depression treatment cost is conservative because other benefits, such as reduced pain and suffering and increased productivity while at work, were not included in the analyses. Employers who bear the cost from lost work days should encourage their employees with depressive disorders to seek treatment, even if it means paying for the entire treatment cost. Self-employed individuals with depression also will benefit even if they pay for the treatment costs themselves.

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Go to Psychiatric Services
Go to Psychiatric Services
Psychiatric Services
Pages: 1209 - 1213
PubMed: 10478909

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Published online: 1 September 1999
Published in print: September 1999

Authors

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Mingliang Zhang, Ph.D.
Kathryn M. Rost, Ph.D.
John C. Fortney, Ph.D.
G. Richard Smith, M.D.

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