Using laboratory data to categorise CD4 laboratory turn-around-time performance across a national programme

African Journal of Laboratory Medicine

 
 
Field Value
 
Title Using laboratory data to categorise CD4 laboratory turn-around-time performance across a national programme
 
Creator Coetzee, Lindi-Marie Cassim, Naseem Glencross, Deborah K.
 
Subject Molecular Medicine and Haematology CD4; HIV; turnaround time
Description Background and objective: The National Health Laboratory Service provides CD4 testing through an integrated tiered service delivery model with a target laboratory turn-around time (TAT) of 48 h. Mean TAT provides insight into national CD4 laboratory performance. However, it is not sensitive enough to identify inefficiencies of outlying laboratories or predict the percentage of samples meeting the TAT target. The aim of this study was to describe the use of the median, 75th percentile and percentage within target of laboratory TAT data to categorise laboratory performance. Methods: Retrospective CD4 laboratory data for 2015–2016 fiscal year were extracted from the corporate data warehouse. The laboratory TAT distribution and percentage of samples within the 48 h target were assessed. A scatter plot was used to categorise laboratory performance into four quadrants using both the percentage within target and 75th percentile TAT. The laboratory performance was labelled good, satisfactory or poor. Results: TAT data reported a positive skew with a mode of 13 h and a median of 17 h and 75th percentile of 25 h. Overall, 93.2% of CD4 samples had a laboratory TAT of less than 48 h. 48 out of 52 laboratories reported good TAT performance, i.e. percentage within target 85% and 75th percentile ≤ 48 h, with two categorised as satisfactory (one parameter met), and two as poor performing laboratories (failed both parameters). Conclusion: This study demonstrated the feasibility of utilising laboratory data to categorise laboratory performance. Using the quadrant approach for TAT data, laboratories that need interventions can be highlighted for root cause analysis assessment.
 
Publisher AOSIS
 
Contributor South African National Research Foundation
Date 2018-06-28
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion — Statistical data analysis
Format text/html application/epub+zip application/xml application/pdf
Identifier 10.4102/ajlm.v7i1.665
 
Source African Journal of Laboratory Medicine; Vol 7, No 1 (2018); 7 pages 2225-2010 2225-2002
 
Language eng
 
Relation
The following web links (URLs) may trigger a file download or direct you to an alternative webpage to gain access to a publication file format of the published article:

https://ajlmonline.org/index.php/ajlm/article/view/665/1016 https://ajlmonline.org/index.php/ajlm/article/view/665/1015 https://ajlmonline.org/index.php/ajlm/article/view/665/1017 https://ajlmonline.org/index.php/ajlm/article/view/665/1014
 
Coverage South Africa 2016 to 2017 CD4 data CD4 TAT, testing laboratory, episode number
Rights Copyright (c) 2018 Lindi-Marie Coetzee, Naseem Cassim, Deborah K. Glencross https://creativecommons.org/licenses/by/4.0
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