Comparative cost analysis of point-of-care versus laboratory-based testing to initiate and monitor HIV treatment in South Africa

南非艾滋病毒治疗启动和监测中,即时检测与实验室检测的成本比较分析

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Abstract

BACKGROUND: The number of people living with HIV (PLHIV) in need of treatment monitoring in low-and-middle-income countries has been rapidly expanding, placing an increasing burden on laboratories. Promising new point-of-care (POC) test have the potential to reduce laboratory workloads, but the implementation cost is uncertain. We sought to estimate the costs of decentralized POC testing compared to centralized laboratory testing for PLHIV initiating treatment in South Africa. METHODS: We conducted a microcosting analyses comparing clinic-based POC testing to centralized laboratory testing for HIV viral load, creatinine, and CD4 count monitoring. We completed time-and-motion studies to assess staff time for sample collection and processing. Instrument costs were estimated assuming five-year lifespans and we applied a 3% annual discount rate. Total costs and cost per patient were estimated over a five-year period: the first year of ART initiation and four years of routine HIV monitoring, following World Health Organization ART monitoring guidelines. RESULTS: We estimated that per-patient costs of POC HIV viral load, CD4, and creatinine tests were USD $25, $11, and $9, respectively, assuming a clinic volume of 50 patients initiated per month. At centralized laboratories, per-patient costs of POC HIV viral load, CD4, and creatinine tests were USD $26, $6, $3. Total monitoring costs of all testing over a 5-year period was $45 higher for POC testing compared to centralized laboratory testing ($210 vs $166). CONCLUSIONS: POC testing for HIV care and treatment can be feasibly implemented within clinics in South Africa, particularly those with larger patient volumes. POC HIV viral load costs are similar to lab-based testing while CD4 count and creatinine testing are more costly as POC tests. Our cost estimates are useful to policymakers in planning resource allocation and can inform cost-effectiveness analyses of POC testing.

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