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Original Research
Weekly laboratory turn-around time identifies poor performance masked by aggregated reporting
Submitted: 18 September 2019 | Published: 21 December 2020
About the author(s)
Lindi-Marie Coetzee, National Health Laboratory Service (NHLS), Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South AfricaNaseem Cassim, National Health Laboratory Service (NHLS), Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
Deborah K. Glencross, National Health Laboratory Service (NHLS), Johannesburg, South Africa; and, Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
Abstract
Background: High-level monthly, quarterly and annual turn-around time (TAT) reports are used to assess laboratory performance across the National Health Laboratory Service in South Africa. Individual laboratory performances are masked by aggregate TAT reporting across network of testing facilities.
Objective: This study investigated weekly TAT reporting to identify laboratory inefficiencies for intervention.
Methods: CD4 TAT data were extracted for 46 laboratories from the corporate data warehouse for the 2016/2017 financial period. The total TAT median, 75th percentile and percentage of samples meeting organisational TAT cut-off (90% within 40 hours) were calculated. Total TAT was reported at national, provincial and laboratory levels. Provincial TAT performance was classified as markedly or moderately poor, satisfactory and good based on the percentage of samples that met the cut-off. The pre-analytical, testing and result review TAT component times were calculated.
Results: Median annual TAT was 18.8 h, 75th percentile was 25 h and percentage within cut-off was 92% (n = 3 332 599). Corresponding 75th percentiles of component TAT were 10 h (pre-analytical), 22 h testing and 1.6 h review. Provincial 75th percentile TAT varied from 17.6 h to 34.1 h, with three good (n = 13 laboratories), four satisfactory (n = 24 laboratories) and two poor performers (n = 9 laboratories) provinces. Weekly TAT analysis showed 12/46 laboratories (28.6%) without outlier weeks, 31/46 (73.8%) with 1–10 outlier weeks and 3/46 (6.5%) with more than 10 (highest of 20/52 weeks) outlier weeks.
Conclusion: Masked TAT under-performances were revealed by weekly TAT analyses, identifying poorly performing laboratories needing immediate intervention; TAT component analyses identified specific areas for improvement.
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