Inge Petersen1, Christopher G Kemp1, Deepa Rao1, Bradley H Wagenaar1, Kenneth Sherr1, Merridy Grant1, Max Bachmann1, Ruanne V Barnabas1, Ntokozo Mntambo1, Sithabisile Gigaba1, André Van Rensburg1, Zamasomi Luvuno1, Ishmael Amarreh1, Lara Fairall1, Nikiwe N Hongo1, Arvin Bhana1. 1. Centre for Rural Health, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa (Petersen, Grant, Gigaba, Van Rensburg, Luvuno, Bhana); Department of Global Health (Kemp, Rao, Wagenaar, Sherr, Barnabas), Department of Psychiatry and Behavioral Sciences (Rao), Department of Epidemiology (Wagenaar), University of Washington, Seattle; Norwich Medical School, University of East Anglia, Norwich, Norfolk, United Kingdom (Bachmann); School of Applied Human Sciences, University of KwaZulu-Natal, Durban, South Africa (Mntambo, Gigaba); Center for Global Mental Health Research, National Institute of Mental Health, Bethesda, Maryland (Amarreh); Knowledge Translation Unit, University of Cape Town, Cape Town, South Africa, and King's Global Health Institute, King's College London, London (Fairall); Mental Health and Substance Abuse Directorate, KwaZulu-Natal Department of Health, Natalia, Pietermaritzburg, South Africa (Hongo); Health Systems Research Unit, South African Medical Research Council, Durban, South Africa (Bhana).
Abstract
BACKGROUND: People with chronic general medical conditions who have comorbid depression experience poorer health outcomes. This problem has received scant attention in low- and middle-income countries. The aim of the ongoing study reported here is to refine and promote the scale-up of an evidence-based task-sharing collaborative care model, the Mental Health Integration (MhINT) program, to treat patients with comorbid depression and chronic disease in primary health care settings in South Africa. METHODS: Adopting a learning-health-systems approach, this study uses an onsite, iterative observational implementation science design. Stage 1 comprises assessment of the original MhINT model under real-world conditions in an urban subdistrict in KwaZulu-Natal, South Africa, to inform refinement of the model and its implementation strategies. Stage 2 comprises assessment of the refined model across urban, semiurban, and rural contexts. In both stages, population-level effects are assessed by using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) evaluation framework with various sources of data, including secondary data collection and a patient cohort study (N=550). The Consolidated Framework for Implementation Research is used to understand contextual determinants of implementation success involving quantitative and qualitative interviews (stage 1, N=78; stage 2, N=282). RESULTS: The study results will help refine intervention components and implementation strategies to enable scale-up of the MhINT model for depression in South Africa. NEXT STEPS: Next steps include strengthening ongoing engagements with policy makers and managers, providing technical support for implementation, and building the capacity of policy makers and managers in implementation science to promote wider dissemination and sustainment of the intervention.
BACKGROUND: People with chronic general medical conditions who have comorbid depression experience poorer health outcomes. This problem has received scant attention in low- and middle-income countries. The aim of the ongoing study reported here is to refine and promote the scale-up of an evidence-based task-sharing collaborative care model, the Mental Health Integration (MhINT) program, to treat patients with comorbid depression and chronic disease in primary health care settings in South Africa. METHODS: Adopting a learning-health-systems approach, this study uses an onsite, iterative observational implementation science design. Stage 1 comprises assessment of the original MhINT model under real-world conditions in an urban subdistrict in KwaZulu-Natal, South Africa, to inform refinement of the model and its implementation strategies. Stage 2 comprises assessment of the refined model across urban, semiurban, and rural contexts. In both stages, population-level effects are assessed by using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) evaluation framework with various sources of data, including secondary data collection and a patient cohort study (N=550). The Consolidated Framework for Implementation Research is used to understand contextual determinants of implementation success involving quantitative and qualitative interviews (stage 1, N=78; stage 2, N=282). RESULTS: The study results will help refine intervention components and implementation strategies to enable scale-up of the MhINT model for depression in South Africa. NEXT STEPS: Next steps include strengthening ongoing engagements with policy makers and managers, providing technical support for implementation, and building the capacity of policy makers and managers in implementation science to promote wider dissemination and sustainment of the intervention.
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