CONTEXT: Although outreach and enhanced treatment interventions improve depression outcomes, uptake has been poor in part because purchasers lack information on their return on investment. OBJECTIVE: To estimate the costs and benefits of enhanced depression care for workers from the societal and employer-purchaser perspectives. DESIGN: Cost-effectiveness and cost-benefit analyses using state-transition Markov models. Simulated movements between health states were based on probabilities drawn from the clinical literature. PARTICIPANTS: Hypothetical cohort of 40-year-old workers. Intervention Enhanced depression care consisting of a depression screen and care management for those depressed vs usual care. MAIN OUTCOME MEASURES: Our base-case cost-effectiveness analysis was from the societal perspective; costs and quality-adjusted life-years were used to compute the incremental cost-effectiveness of the intervention relative to usual care. A secondary cost-benefit analysis from the employer's perspective tracked monetary costs and monetary benefits accruing to employers during a 5-year time horizon. RESULTS: From the societal perspective, screening and depression care management for workers result in an incremental cost-effectiveness ratio of $19 976 per quality-adjusted life-year relative to usual care. These results are consistent with recent primary care effectiveness trials and within the range for medical interventions usually covered by employer-sponsored insurance. From the employer's perspective, enhanced depression care yields a net cumulative benefit of $2895 after 5 years. In 1-way and probabilistic sensitivity analyses, these findings were robust to a variety of assumptions. CONCLUSION: If these results can be replicated in effectiveness trials directly assessing effects on work outcomes, they suggest that enhanced treatment quality programs for depression are cost-beneficial to purchasers.
CONTEXT: Although outreach and enhanced treatment interventions improve depression outcomes, uptake has been poor in part because purchasers lack information on their return on investment. OBJECTIVE: To estimate the costs and benefits of enhanced depression care for workers from the societal and employer-purchaser perspectives. DESIGN: Cost-effectiveness and cost-benefit analyses using state-transition Markov models. Simulated movements between health states were based on probabilities drawn from the clinical literature. PARTICIPANTS: Hypothetical cohort of 40-year-old workers. Intervention Enhanced depression care consisting of a depression screen and care management for those depressed vs usual care. MAIN OUTCOME MEASURES: Our base-case cost-effectiveness analysis was from the societal perspective; costs and quality-adjusted life-years were used to compute the incremental cost-effectiveness of the intervention relative to usual care. A secondary cost-benefit analysis from the employer's perspective tracked monetary costs and monetary benefits accruing to employers during a 5-year time horizon. RESULTS: From the societal perspective, screening and depression care management for workers result in an incremental cost-effectiveness ratio of $19 976 per quality-adjusted life-year relative to usual care. These results are consistent with recent primary care effectiveness trials and within the range for medical interventions usually covered by employer-sponsored insurance. From the employer's perspective, enhanced depression care yields a net cumulative benefit of $2895 after 5 years. In 1-way and probabilistic sensitivity analyses, these findings were robust to a variety of assumptions. CONCLUSION: If these results can be replicated in effectiveness trials directly assessing effects on work outcomes, they suggest that enhanced treatment quality programs for depression are cost-beneficial to purchasers.
Authors: Merida M Grant; Christopher Cannistraci; Steven D Hollon; John Gore; Richard Shelton Journal: J Psychiatr Res Date: 2011-01-26 Impact factor: 4.791
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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
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