Implementation Science Using Proctorʼs Framework and an Adaptation of the Multiphase Optimization Strategy: Optimizing a Financial Incentive Intervention for HIV Treatment Adherence in Tanzania

2019 
BACKGROUND: Ambitious targets have been set to end the HIV epidemic by 2030. Such targets assume that tools to end HIV exist and are successfully being deployed across populations, albeit unequally. Implementation science approaches are needed to understand the drivers of disparities and how to bring effective interventions to those most in need. We describe a hybrid implementation science approach, adapting a strategy to facilitate retention and viral suppression (VS) among people living with HIV/AIDS in Tanzania. METHODS/DESIGN: We used Proctor framework and the multiphase optimization strategy to optimize a cash transfer to improve antiretroviral therapy adherence and VS among people living with HIV/AIDS in Tanzania. This involved 3 trials. The first trial tested the efficacy of cash and food assistance compared with the standard of care in improving antiretroviral therapy adherence among treatment initiators. Cash transfers were superior to the standard of care and noninferior, less expensive, and logistically simpler to implement compared with food. The second trial is dose-finding: identifying the optimal amount of cash for a 20% improvement in VS at 6 months. Before this, components were simplified to maximize reach, align with local policies, and reduce staff time. We assessed implementation science constructs to understand barriers to uptake and sustainability. Trial 3 is a cluster randomized controlled trial, testing the effectiveness of the optimized intervention in multiple settings. DISCUSSION/IMPLICATIONS: Our process illustrates the utility of applying multiple implementation science frameworks to arrive at an optimal implementation strategy to bridge the know-do gap with data to show efficacy and maximum potential for scalability and sustainability.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    35
    References
    3
    Citations
    NaN
    KQI
    []