Implementation of point of care HIV viral load monitoring for people living with HIV in low- and middle-income countries: A systematic review on implementation research outcomes

Background Viral load monitoring has rapidly increased among people living with HIV(PLHIV) in low- and middle-income countries (LMICs), resulting in an increased laboratory workload. The use of innovative Point of Care (PoC) or near Point of Care (n)PoC HIV Viral Load (HIV VL) monitoring has enabled improved patient care, a reduction in laboratory workload, improved clinic retention and reduced turnaround time of results. However, implementation bottlenecks of such methods are uncertain, especially when PoC or (n)PoC is implemented in remote areas in low-volume clinics. Objectives The main aim of this study was to review implementation research outcomes of (n) PoC HIV VL monitoring for PLHIV in LMICs. Methods We qualitatively synthesised peer-reviewed papers to explore implementation research outcomes (IROs) of (n)PoC HIV VL monitoring. We identified studies published between January 2013 and June 2024. We used the IROs described by Proctor et al., which are acceptability, adoption, appropriateness, cost, feasibility, fidelity, penetration and sustainability. We searched using the following Mesh terms: Point of care testing, HIV, viral load, acceptability, patient acceptance of health care, adoption, facilities and services utilisation, appropriateness, cost, feasibility, fidelity, penetration, coverage, sustainability and continuity of patient care through PubMed, Cochrane and Scopus. The PRISMA diagram in the Fig 1 presents the selection process of included papers. Results Twenty studies reported implementation outcomes of PoC or (n)PoC HIV VL monitoring. Near PoC HIV VL monitoring using GeneXpert is considered acceptable to patients and healthcare providers. Point of care HIV VL monitoring using mPIMA was feasible as patients received the results the same day. From a health service provider’s perspective, PoC HIV VL monitoring was acceptable because it influenced patients to accept the illness and adhere to medication. Additionally, there was high testing coverage in routine PoC HIV VL monitoring centres. Fidelity was questionable in some settings due to (n)PoC HIV VL monitoring results not being delivered as intended. Additionally, we found in several studies that the (n)PoC costs are higher than standard of care test, USD 54.93 per test, at low testing volume clinics conducting 20VL tests per month compared to costs of USD 24.25 at high testing volume clinics conducting 100VL tests per month, while centralised testing costs USD 25.65 per test. However, costs are expected to be lower when (n)PoC HIV VL monitoring is scaled up and targeted for those at risk. Conclusion Implementation of PoC or (n)PoC testing for HIV viral load monitoring is acceptable and feasible and can reach a vast population. However, higher costs, limited fidelity, lower penetration and limited sustainability may hinder using (n)PoC testing in improving patient care and health outcomes. More knowledge and training should be implemented to overcome these challenges.