The accuracy of a point-of-care test among different operators using the QBC Autoread Plus Analyzer for the measurement of a basic full blood count.

Background: Major issues around the implementation of point-of-care testing (POCT) include: user type, regulatory control, ongoing quality monitoring and limited guideline adherence.59 December 2019, Print editionObjectives. To determine if there are significant differences in the results of a POC full blood count test between different levels of healthcare and non-medical 'lay' users compared with laboratory users (technologists/pathologists).
Methods: This article retrospectively reviews the technical evaluation database of the intensive care unit (ICU), Chris Hani Baragwanath Academic Hospital, Johannesburg, South Africa. We searched for samples analysed by doctors, clerks and laboratory personnel. A minimum number of 60 comparisons were required. Bland-Altman plots, Spearman's correlation and Passing-Bablok fit were used to analyse the dataset.
Results: There were 72 comparisons for haematocrit (Hct), 98 for white cell count (WCC) and 137 for platelets (Plt) between the clerk and laboratory personnel. The correlations were 0.91, 0.96 and 0.92, respectively. All were statistically significant. Using the Bland-Altman method, there was good agreement between results of the clerk and those of the laboratory staff, with a mean bias of 0.5% (Hct), 0.1 × 109/L (WCC) and 10 × 109/L (Plt). An insufficient number of tests were performed by medical doctors for statistical comparison.
Conclusions: With appropriate training, non-medical, non-healthcare lay users are able to perform a moderately complex POCT with similar accuracy as trained laboratory professionals. The focus should shift to equipment and quality management processes rather than the medical/technical qualification of the user.