Original Research

Categorising specimen referral delays for CD4 testing: How inter-laboratory distances and travel times impact turn-around time across a national laboratory service in South Africa

Naseem Cassim, Lindi M. Coetzee, Deborah K. Glencross
African Journal of Laboratory Medicine | Vol 9, No 1 | a1120 | DOI: https://doi.org/10.4102/ajlm.v9i1.1120 | © 2020 Naseem Cassim, Lindi Marie Coetzee, Deborah Kim Glencross | This work is licensed under CC Attribution 4.0
Submitted: 06 November 2019 | Published: 21 December 2020

About the author(s)

Naseem Cassim, National Health Laboratory Service, Johannesburg, South Africa
Lindi M. Coetzee, National Health Laboratory Service, Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
Deborah K. Glencross, National Health Laboratory Service, Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa


Share this article

Bookmark and Share

Abstract

Background: The South African National Health Laboratory Service provides laboratory services for public sector health facilities, utilising a tiered laboratory model to refer samples for CD4 testing from 255 source laboratories into 43 testing laboratories.

Objective: The aim of this study was to determine the impact of distance on inter-laboratory referral time for public sector testing in South Africa in 2018.

Methods: A retrospective cross-sectional study design analysed CD4 testing inter-laboratory turn-around time (TAT) data for 2018, that is laboratory-to-laboratory TAT from registration at the source to referral receipt at the testing laboratory. Google Maps was used to calculate inter-laboratory distances and travel times. Distances were categorised into four buckets, with the median and 75th percentile reported. Wilcoxon scores were used to assess significant differences in laboratory-to-laboratory TAT across the four distance categories.

Results: CD4 referrals from off-site source laboratories comprised 49% (n = 1 390 510) of national reporting. A positively skewed distribution of laboratory-to-laboratory TAT was noted, with a median travel time of 11 h (interquartile range: 7–17), within the stipulated 12 h target. Inter-laboratory distance categories of less than 100 km, 101–200 km, 201–300 km and more than 300 km (p < 0.0001) had 75th percentiles of 8 h, 17 h, 14 h and 27 h.

Conclusion: Variability in inter-laboratory TAT was noted for all inter-laboratory distances, especially those exceeding 300 km. The correlation between distance and laboratory-to-laboratory TAT suggests that interventions are required for distant laboratories.


Keywords

HIV; cluster of differentiation 4; CD4; immune status; inter-laboratory referral; distance; travel time

Metrics

Total abstract views: 335
Total article views: 86


Crossref Citations

No related citations found.