Research Abstract Depression is the single largest health care burden in the world, with no other illness accounting for even half its burden. Recently, the World Bank, WHO, Grand Challenges of Canada, and NIMH highlighted the crippling economic costs of unaddressed depression and the need to scale up depression care globally. In Vietnam, we found collaborative care effective and conducted a clustered randomized control trial (RCT) that has shown large effect sizes for a Multicomponent Collaborative Care Model for Depression (MCCD), in which depression care was task-shifted to primary care providers in local community health clinics and supported by mobile psychiatrists. While the benefits of collaborative care for depression are well-established, the most appropriate and effective implementation strategies for scaling up this model have not been identified. To address this need, our R01 proposal will build on our team's previous work on the MCCD and leverage current policy initiatives related to depression care in Vietnam?Grand Challenges of Canada, GCC, funding, which includes 80% matched funds supported by the Vietnamese health care system to support establishing a Center of Excellence at Danang Psychiatric Hospital and scaling up another NIMH R34 Depression program (LIFE- DM)?to identify implementation models most likely to lead to successful implementation and sustainment of effective services in low-resource settings. We will partner with local and national community and government organizations to conduct an RCT comparing effectiveness of three implementation models: (a) usual implementation (UI), which typically includes one workshop and toolkit; (b) enhanced supervision (ES; includes model UI); and (c) community-engaged learning collaborative (CELC; includes ES). According to the RE-AIM Implementation Evaluation framework, to have a population-level impact, an EBI must be adopted by providers, reach a large proportion of the targeted patient population, be implemented with fidelity, effectively improve outcomes, and be maintained after research funds are withdrawn. Thus, we will assess implementation outcomes at the organizational, provider, and patient levels based on this framework, assess organizational and provider factors associated with successful implementation, and measure the incremental cost-effectiveness of each implementation strategy. Doing this can guide policy decisions on best strategies to support scale-up of collaborative care models for depression and other EBIs. This comprehensive and rigorous implementation effectiveness study will contribute to our understanding of the added value of using a CELC strategy over and above the best practice in training (ES), which has not been done even in high-income countries. This timely evaluation of an depression care task-shifting will provide much needed knowledge about what implementation strategies and factors promote adoption, delivery, and sustainment of high-quality depression care in low-resource settings where limited mental health human resources are available, thus addressing global priority knowledge gaps in implementation science and mental health research.

Public Health Relevance

Our R01's mission is to identify effective implementation strategies for task-shifting depression care in low- resource settings where limited mental health resources exist, which will support NIMH's mission to close the treatment gap, understand implementation mechanisms, and improve global mental health capacity.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH112630-01A1
Application #
9531167
Study Section
Dissemination and Implementation Research in Health Study Section (DIRH)
Program Officer
Brouwers, Pim
Project Start
2019-07-01
Project End
2023-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Graduate School of Public Health and Health Policy
Department
Public Health & Prev Medicine
Type
Graduate Schools
DUNS #
079683257
City
New York
State
NY
Country
United States
Zip Code
10027