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Original Research
Modelling CD4 reagent usage across a national hierarchal network of laboratories in South Africa
Submitted: 21 September 2022 | Published: 15 May 2023
About the author(s)
Naseem Cassim, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; and, National Priority Programme, National Health Laboratory Service, Johannesburg, South AfricaLindi-Marie Coetzee, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, 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, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
Abstract
Background: The National Health Laboratory Service is mandated to deliver cost-effective and efficient diagnostic services across South Africa. Their mandate is achieved by a network of laboratories ranging from centralised national laboratories to distant rural facilities.
Objective: This study aimed to establish a model of CD4 reagent utilisation as an independent measure of laboratory efficiency.
Methods: The efficiency percentage was defined as finished goods (number of reportable results) over raw materials (number of reagents supplied) for 47 laboratories in nine provinces (both anonymised) for 2019. The efficiency percentage at national and provincial levels was calculated and compared to the optimal efficiency percentage derived using pre-set assumptions. Comparative laboratory analysis was conducted for the provinces with the best and worst efficiency percentages. The possible linear relationship between the efficiency percentage and call-outs, days lost, referrals, and turn-around time was assessed.
Results: Data are reported for 2 806 799 CD4 tests, with an overall efficiency percentage of 84.5% (optimal of 84.98%). The efficiency percentage varied between 75.7% and 87.7% between provinces, while within the laboratory it ranged from 66.1% to 111.5%. Four laboratories reported an efficiency percentage ranging from 67.8% to 85.7%. No linear correlation was noted between the efficiency percentage, call-outs, days lost, and turn-around time performance.
Conclusion: Reagent efficiency percentage distinguished laboratories into different utilisation levels irrespective of their CD4 service level. This parameter is an additional independent indicator of laboratory performance, with no relationship with any contributing factors tested, that can be implemented across pathology disciplines for monitoring reagent utilisation.
What this study adds: This study provides an objective methodology to assess reagent utilisation as an independent measure of laboratory efficiency. This model could be applied to all routine pathology services.
Keywords
Sustainable Development Goal
Metrics
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