scholarly journals Impact on Microbiology Laboratory Turnaround Times Following Process Improvements and Total Laboratory Automation

2021 ◽  
Vol 2 (1) ◽  
Keyword(s):  
Laboratory Automation ◽  
Microbiology Laboratory ◽  
Process Improvements ◽  
Total Laboratory Automation

scholarly journals Clinical Microbiology Is Growing Up: The Total Laboratory Automation Revolution

2019 ◽  
Vol 65 (5) ◽  
pp. 634-643 ◽  
Author(s):  
Adam L Bailey ◽  
Nathan Ledeboer ◽  
Carey-Ann D Burnham
Keyword(s):  
Laboratory Testing ◽  
Clinical Microbiology ◽  
Turnaround Time ◽  
Automation System ◽  
Clinical Microbiology Laboratory ◽  
Laboratory Automation ◽  
Microbiology Laboratory ◽  
Total Laboratory Automation ◽  
The Impact ◽  
Automated Methods

Abstract BACKGROUND Historically, culture-based microbiology laboratory testing has relied on manual methods, and automated methods (such as those that have revolutionized clinical chemistry and hematology over the past several decades) were largely absent from the clinical microbiology laboratory. However, an increased demand for microbiology testing and standardization of sample-collection devices for microbiology culture, as well as a dwindling supply of microbiology technologists, has driven the adoption of automated methods for culture-based laboratory testing in clinical microbiology. CONTENT We describe systems currently enabling total laboratory automation (TLA) for culture-based microbiology testing. We describe the general components of a microbiology automation system and the various functions of these instruments. We then introduce the 2 most widely used systems currently on the market: Becton Dickinson's Kiestra TLA and Copan's WASPLab. We discuss the impact of TLA on metrics such as turnaround time and recovery of microorganisms, providing a review of the current literature and perspectives from laboratory directors, managers, and technical staff. Finally, we provide an outlook for future advances in TLA for microbiology with a focus on artificial intelligence for automated culture interpretation. SUMMARY TLA is playing an increasingly important role in clinical microbiology. Although challenges remain, TLA has great potential to affect laboratory efficiency, turnaround time, and the overall quality of culture-based microbiology testing.

scholarly journals Total Laboratory Automation and Three Shifts Reduce Turnaround Time of Cerebrospinal Fluid Culture Results in the Chinese Clinical Microbiology Laboratory

2021 ◽  
Vol 11 ◽  
Author(s):  
Weili Zhang ◽  
Siying Wu ◽  
Jin Deng ◽  
Quanfeng Liao ◽  
Ya Liu ◽  
...  
Keyword(s):  
Clinical Microbiology ◽  
Laboratory Data ◽  
Turnaround Time ◽  
Klebsiella Pneumonia ◽  
Clinical Microbiology Laboratory ◽  
Laboratory Automation ◽  
Microbiology Laboratory ◽  
Significant Difference ◽  
Total Laboratory Automation ◽  
The Difference

BackgroundTotal laboratory automation (TLA) has the potential to reduce specimen processing time, optimize workflow, and decrease turnaround time (TAT). The purpose of this research is to investigate whether the TAT of our laboratory has changed since the adoption of TLA, as well as to optimize laboratory workflow, improve laboratory testing efficiency, and provide better services of clinical diagnosis and treatment.Materials and MethodsLaboratory data was extracted from our laboratory information system in two 6-month periods: pre-TLA (July to December 2019) and post-TLA (July to December 2020), respectively.ResultsThe median TAT for positive cultures decreased significantly from pre-TLA to post-TLA (65.93 vs 63.53, P<0.001). For different types of cultures, The TAT of CSF changed the most (86.76 vs 64.30, P=0.007), followed by sputum (64.38 vs 61.41, P<0.001), urine (52.10 vs 49,57, P<0.001), blood (68.49 vs 66.60, P<0.001). For Ascites and Pleural fluid, there was no significant difference (P>0.05). Further analysis found that the incidence of broth growth only for pre-TLA was 12.4% (14/133), while for post-TLA, it was 3.4% (4/119). The difference was statistically significant (P=0.01). The common isolates from CSF samples were Cryptococcus neoformans, coagulase-negative Staphylococcus, Acinetobacter baumannii, and Klebsiella pneumonia.ConclusionUsing TLA and setting up three shifts shortened the TAT of our clinical microbiology laboratory, especially for CSF samples.

scholarly journals Impact on microbiology laboratory turn-around-times following process improvements and total laboratory automation

2020 ◽  
Author(s):  
Carolyn Gonzalez-Ortiz ◽  
Alanna Emrick ◽  
Ying P. Tabak ◽  
Latha Vankeepuram ◽  
Stephen Kurtz ◽  
...  
Keyword(s):  
Turnaround Time ◽  
Categorical Variables ◽  
Research Database ◽  
Continuous Variables ◽  
Laboratory Automation ◽  
Process Standardization ◽  
Process Improvements ◽  
Before And After ◽  
Total Laboratory Automation ◽  
The Impact

ABSTRACTIntroductionThe impact of workflow changes and total laboratory automation (TLA) on microbiology culture processing time was evaluated in an academic-affiliated regional hospital.Materials and MethodsA retrospective analysis of microbiological data in a research database was performed to compare turnaround time (TAT) for organism identification (ID) before and after implementation of TLA (2013 versus 2016, respectively). TAT was compared using χ2 test for categorical variables and log-transformed t-test for continuous variables.ResultsA total of 9,351 pre-defined common and clinically important positive mono-bacterial culture results were included in the analysis. Shorter TAT (hours) in 2016 compared to 2013 (p<0.0001) for positive result pathogen ID were observed in specimen types including blood (40.7 vs. 47.1), urine (30 vs 44), wound (39.6 vs. 60.2), respiratory (47.7 vs. 67), and all specimen types, combined (43.3 vs. 56.8). Although shorter TAT were not observed from all specimen categories for negative result pathogen ID, TAT for all specimen types, combined, was shorter (p≤0.001) in 2016 compared to 2013 (94 vs. 101).ConclusionsTotal laboratory automation and workflow changes—including process standardization—facilitate shorter organism ID TAT across specimen sources.

Total laboratory automation: Do stat tests still matter?

2017 ◽  
Vol 50 (10-11) ◽  
pp. 605-611 ◽  
Author(s):  
Alberto Dolci ◽  
Davide Giavarina ◽  
Sara Pasqualetti ◽  
Dominika Szőke ◽  
Mauro Panteghini
Keyword(s):  
Laboratory Automation ◽  
Total Laboratory Automation

Total Laboratory Automation of Routine Hemostasis Testing

2014 ◽  
Vol 19 (4) ◽  
pp. 419-422 ◽  
Author(s):  
Giorgio Da Rin ◽  
Giuseppe Lippi
Keyword(s):  
Laboratory Automation ◽  
Total Laboratory Automation
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