Original Research
Addressing antiretroviral therapy-related diagnostic coverage gaps across South Africa using a programmatic approach
Submitted: 18 September 2017 | Published: 12 November 2018
About the author(s)
Naseem Cassim, Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa; and, National Priority Programme, National Health Laboratory Service, Johannesburg, South AfricaLindi M. Coetzee, Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa; and, National Priority Programme, National Health Laboratory Service, Johannesburg, South Africa
Wendy S. Stevens, Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa; and, National Priority Programme, National Health Laboratory Service, Johannesburg, South Africa
Deborah K. Glencross, Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa; and, National Priority Programme, National Health Laboratory Service, Johannesburg, South Africa
Abstract
Background: A major challenge facing South Africa is the concomitant HIV and tuberculosis epidemics. The National Health Laboratory Service provides testing for staging HIV-positive patients, monitoring patients on antiretroviral therapy (ART) and diagnosing tuberculosis. Not all health districts have equivalent ART-related coverage in particular for CD4 and HIV viral load testing.
Objectives: The Integrated Tiered Service Delivery Model coverage precinct approach was used to address ART-related testing service coverage gaps in a manner that balances cost, quality and equity.
Methods: An algorithm was developed to identify and address ART-related diagnostic coverage gaps. Data was extracted from the corporate data warehouse and Oracle systems for the period of April 2015 to March 2016. Daily test volumes were based on 21.73 working days per month. Data were analysed using MS Excel and mapped using ArcCatalog and ArcMap. Capacity analysis was informed by the available testing-platforms.
Results: Health district daily HIV viral load volumes ranged from 2 to 1308 samples. Nineteen candidate laboratories were identified to address the coverage gaps. Following the proximity analysis, testing was consolidated at four candidate laboratories, resulting in 13 revised candidate laboratories. The revised candidate laboratory daily HIV viral load referrals ranged between 5 and 205 samples, with CD4 volumes between 6 and 85 samples. Remaining coverage gaps were identified in seven municipalities.
Conclusions: The study demonstrated that the service coverage precinct approach could be used to identify coverage gaps for a defined ART-related testing repertoire.
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