Study setting
This was a national-level study involving all the facilities, irrespective of level, that are accredited to provide paediatric and adolescent HIV care and treatment services. These facilities are supported (technically) by sixteen implementing partners.
Study Population
All CALHIV (0–19 years) that were in HIV care and treatment at all ART accredited facilities in Uganda by March 2021 were included in the study. The CALHIV on ART were disaggregated by age-bands (< 3 years, 3–9 years, 10–14 years, and 15–19 years). This facilitated age-specific analysis and interventions.
Operational Definition Of Art Optimization
ART optimization in this case referred to initiating or transitioning CALHIV on either an integrase strand transfer inhibitor (DTG) or a protease inhibitor (LPV/r) as the anchor drug. ART optimization thus meant expanding both the initiation on an InSTI (DTG) or PI (LPVr) as the anchor drug for the newly enrolled and the transition from an NNRTI to an InSTI as the anchor drug for the children and adolescents already in care.
Optimization Process
Preparatory phase
The ART optimization foundational work began with a comprehensive and systematic preparatory process in June 2020. MOH – AIDS Control Program and AIDS development partners (ADPs) held planning meetings, and these scheduled the national roll out of paediatric and adolescent ART optimization, managed the supply chain and reviewed training materials required for surging the paediatric and adolescent ART optimization.
To forecast and plan the supply chain, MOH triangulated data on number of CALHIV using the district health information software version 2 (DHIS-2) (which is the national reporting system) with the numbers in the Web-based ART ordering system (WAOS) to estimate the number of children who needed ART optimization. This estimate was used to plan, forecast, and procure ARVs for the ART optimization process.
Next, MOH supported by ADPs developed tools that established clear mechanisms to firstly identify and then monitor the optimization progress for CALHIV eligible for optimization. These included: curricula, job-aids, and standard operating procedures (SOPs). Then, an ART optimization checklist and an action-oriented line listing tool were also developed. CALHIV optimization stickers were procured along with viral load test eligibility stickers to aid identification of eligible CALHIV.
Implementation Phase
MOH, through a traditional hierarchical approach, trained national trainers who in turn trained regional trainers. The regional trainers who trained district-based teams and the district-based teams trained the frontline facility workers on paediatric and adolescent ART optimization. Capacity of front-line health workers to initiate or transition CALHIV to optimal ART regimens was built through on job training using the revised curricula, SOPs, and job-aides. The use of the ART optimization checklist, the line listing tool and the stickers was demonstrated and emphasized.
The frontline health workers, with support from the implementing partners, used the checklist and line-list tool and line listed all CALHIV eligible for ART optimization in June 2020. The line lists were shared with the central team at MOH to allow monitoring of the national progress on ART optimization and follow up of those who had not yet transitioned. Paediatric optimization stickers were placed on the eligible CALHIV’s charts and this eased identification of eligible children for either a viral load test or for ART optimization by health workers. Due to COVID-19 movement restrictions, innovations such as community ART distribution and viral load bleeding for testing were employed to reach CALHIV due for optimization or a viral load test that could not access the health facilities.
To ensure fidelity to implementation, MOH integrated ART optimization indicators in the routine support supervisions. ART optimization of CALHIV was still ongoing at the time of writing this manuscript.
Monitoring Phase
MOH developed specific indicators to monitor paediatric and adolescent ART optimization and the monitoring was done on a weekly basis throughout the implementation phase of the optimization process. MOH shared a standard reporting template with implementing partners (IPs) and these supported and collated data from health facilities to report progress on ART optimization in the weekly virtual (zoom) meeting convened by the MOH. Regions reported on: total number of CALHIV on ART, CALHIV on optimal regimens disaggregated by age-bands (< 3 years, 3–9 years, 10–14 years, and 15–19 years) and gender, ARV stock at hand in the region, and challenges faced during the ART optimization process. During these meetings, MOH with ADPs provided possible solutions to the challenges to the optimization process.
Secondly, continuous quality improvement (CQI) activities were critical to CALHIV ART optimization. CQI activities aimed at improved viral load suppression in CALHIV inadvertently led to activities targeting transition to optimal regimens.
Thirdly, active stock monitoring and management was critical since stock outs of the optimal ARV regimens would have hampered the entire process. Stock monitoring for each region was done weekly in the meetings and mitigation measures were taken timely for facilities/ regions that were running out of stock. Measures included stock replenishment from the warehouses or re-distribution from facilities that were overstocked.
Data Management And Statistical Analysis
To assess the progress on ART optimization by March 2021, we developed an Excel template with ART optimization indicators and these included: CALHIV on NNRTIs (non-optimal ARV regimen) disaggregated by age (< 3 years, 3–9 years, 10–14 years, and 15–19 years), CALHIV on DTG or LPV/r (optimal ARV regimens) also disaggregated by similar age-bands, adolescents on non-optimal and adolescents on optimal ARV regimens disaggregated by gender and age (10–14 years and 15–19 years), and challenges faced during the process of ART optimization.
This template was shared with implementing partners in all regions in Uganda. These in turn distributed the template to all health facilities (HC II at parish level, HC III at sub-county level, HC IV at county level, general hospitals at district level, Centers of excellence (for HIV care and treatment), regional referral hospitals at regional level and National Referral Hospitals). These were also disaggregated as either government owned, private not for profit and private for profit. The IPs collated data from each of the health facilities in the region and shared the filled template with MOH. We also obtained earlier data on ART optimization since June 2019 from the strategic information unit of the AIDS Control Program at MOH.
Data on viral load suppression for all CALHIV during January 2018 to March 2021 was obtained from the Central Public Health Laboratories (CPHL). All data from all regions was collated in Microsoft Excel and we used Microsoft Excel and StatsDirect version 3.0 for analyses.
Analysis
Sample characteristics of CALHIV in the study were presented as proportions. We also calculated the proportions of children and adolescents on the different anchor regimens and compared these in the different age bands, by the different levels of health facility, and by ownership status of the health levels. We determined statistical significance between optimization of adolescent boys and girls using odd ratios and the associated P-values.
A line graph was used to describe the trend of optimization for the period June 2019 to March 2021.
Finally, we used line graphs again to describe trends of viral load suppression in children and adolescents during January 2018 to March 2021 and used the equation of the line to estimate the annual change in viral load suppression following the paediatric and adolescent ART optimization.