Total lab automation in microbiology: An overview of BD Kiestra InoqulA and Copan WASP

2021 ◽  
Vol 1 (1) ◽  
pp. 07-015
Author(s):  
Assama Riaz ◽  
Dinali Obeysekera ◽  
Kelsie Ruslow
Keyword(s):  
Sensitivity And Specificity ◽  
Healthcare Setting ◽  
Turnaround Time ◽  
Practical Approach ◽  
Laboratory Diagnostics ◽  
Laboratory Automation ◽  
Satisfactory Solution ◽  
The Future ◽  
Total Laboratory Automation ◽  
Dependent Field

Total Laboratory Automation (TLA) is the future of laboratory diagnostics due to its efficiency, reproducibility, better turnaround time (TATs), precision, sensitivity, and specificity. Microbiology is generally considered a human dependent field and still, most of the microbiology world is confused with TLA implementation. Two better-claimed technologies BD Kiestra InoqulA and Copan WASP have emerged as a well satisfactory solution of microbiology automation in the last decade. Here we design a practical approach and reviewed all studies of BD Kiestra InoqulA and Copan WASP, assessed microbiology samples in a healthcare setting.

scholarly journals Advantages and limitations of total laboratory automation: a personal overview

2019 ◽  
Vol 57 (6) ◽  
pp. 802-811 ◽  
Author(s):  
Giuseppe Lippi ◽  
Giorgio Da Rin
Keyword(s):  
Laboratory Diagnostics ◽  
Laboratory Automation ◽  
Assembly Lines ◽  
Modular Systems ◽  
Critical Issues ◽  
Current Scenario ◽  
History Of ◽  
Total Laboratory Automation ◽  
Space Requirements

Abstract Automation is considered one of the most important breakthroughs in the recent history of laboratory diagnostics. In a model of total laboratory automation (TLA), many analyzers performing different types of tests on different sample matrices are physically integrated as modular systems or physically connected by assembly lines. The opportunity to integrate multiple diagnostic specialties to one single track seems effective to improve efficiency, organization, standardization, quality and safety of laboratory testing, whilst also providing a significant return of investment on the long-term and enabling staff requalification. On the other hand, developing a model of TLA also presents some potential problems, mainly represented by higher initial costs, enhanced expenditure for supplies, space requirements and infrastructure constraints, staff overcrowding, increased generation of noise and heat, higher risk of downtime, psychological dependence, critical issues for biospecimen management, disruption of staff trained in specific technologies, along with the risk of transition toward a manufacturer’s-driven laboratory. As many ongoing technological innovations coupled with the current scenario, profoundly driven by cost-containment policies, will promote further diffusion of laboratory automation in the foreseeable future, here we provide a personal overview on some potential advantages and limitations of TLA.

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 The Role of Total Laboratory Automation in a Consolidated Laboratory Network

2000 ◽  
Vol 46 (5) ◽  
pp. 751-756 ◽  
Author(s):  
Richard S Seaberg ◽  
Robert O Stallone ◽  
Bernard E Statland
Keyword(s):  
Cost Effective ◽  
Turnaround Time ◽  
Automation System ◽  
Laboratory Automation ◽  
Labor Costs ◽  
The Core ◽  
The North ◽  
Laboratory Network ◽  
Automation Systems ◽  
Total Laboratory Automation

Abstract Background: In an effort to reduce overall laboratory costs and improve overall laboratory efficiencies at all of its network hospitals, the North Shore–Long Island Health System recently established a Consolidated Laboratory Network with a Core Laboratory at its center. Methods: We established and implemented a centralized Core Laboratory designed around the Roche/Hitachi CLAS Total Laboratory Automation system to perform the general and esoteric laboratory testing throughout the system in a timely and cost-effective fashion. All remaining STAT testing will be performed within the Rapid Response Laboratories (RRLs) at each of the system’s hospitals. Results: Results for this laboratory consolidation and implementation effort demonstrated a decrease in labor costs and improved turnaround time (TAT) at the core laboratory. Anticipated system savings are ∼$2.7 million. TATs averaged 1.3 h within the Core Laboratory and less than 30 min in the RRLs. Conclusions: When properly implemented, automation systems can reduce overall laboratory expenses, enhance patient services, and address the overall concerns facing the laboratory today: job satisfaction, decreased length of stay, and safety. The financial savings realized are primarily a result of labor reductions.

scholarly journals Artificial Neural Network for Total Laboratory Automation to Improve the Management of Sample Dilution

2016 ◽  
Vol 22 (1) ◽  
pp. 44-49 ◽  
Author(s):  
Cristiano Ialongo ◽  
Massimo Pieri ◽  
Sergio Bernardini
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Troponin I ◽  
Turnaround Time ◽  
Laboratory Automation ◽  
Data Set ◽  
Common Task ◽  
Total Laboratory Automation ◽  
Artificial Neural ◽  
Sample Dilution

Diluting a sample to obtain a measure within the analytical range is a common task in clinical laboratories. However, for urgent samples, it can cause delays in test reporting, which can put patients’ safety at risk. The aim of this work is to show a simple artificial neural network that can be used to make it unnecessary to predilute a sample using the information available through the laboratory information system. Particularly, the Multilayer Perceptron neural network built on a data set of 16,106 cardiac troponin I test records produced a correct inference rate of 100% for samples not requiring predilution and 86.2% for those requiring predilution. With respect to the inference reliability, the most relevant inputs were the presence of a cardiac event or surgery and the result of the previous assay. Therefore, such an artificial neural network can be easily implemented into a total automation framework to sensibly reduce the turnaround time of critical orders delayed by the operation required to retrieve, dilute, and retest the sample.

scholarly journals Implementation of total laboratory automation at a tertiary care hospital in Saudi Arabia: effect on turnaround time and cost efficiency

2018 ◽  
Vol 38 (5) ◽  
pp. 352-357 ◽  
Author(s):  
Tracy Louise Ellison ◽  
Maha Alharbi ◽  
Morad Alkaf ◽  
Shamad Elimam ◽  
Mariam Alfaries ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Cost Efficiency ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Turnaround Time ◽  
Care Hospital ◽  
Laboratory Automation ◽  
Total Laboratory Automation

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.

scholarly journals Nonanalytic Laboratory Automation: A Quarter Century of Progress

2017 ◽  
Vol 63 (6) ◽  
pp. 1074-1082 ◽  
Author(s):  
Charles D Hawker
Keyword(s):  
Clinical Laboratory ◽  
Turnaround Time ◽  
Laboratory Automation ◽  
Sample Processing ◽  
Laboratory Sample ◽  
Quarter Century ◽  
Single Function ◽  
Automation Systems ◽  
Total Laboratory Automation ◽  
Manual Processing

Abstract Clinical laboratory automation has blossomed since the 1989 AACC meeting, at which Dr. Masahide Sasaki first showed a western audience what his laboratory had implemented. Many diagnostics and other vendors are now offering a variety of automated options for laboratories of all sizes. Replacing manual processing and handling procedures with automation was embraced by the laboratory community because of the obvious benefits of labor savings and improvement in turnaround time and quality. Automation was also embraced by the diagnostics vendors who saw automation as a means of incorporating the analyzers purchased by their customers into larger systems in which the benefits of automation were integrated to the analyzers. This report reviews the options that are available to laboratory customers. These options include so called task-targeted automation—modules that range from single function devices that automate single tasks (e.g., decapping or aliquoting) to multifunction workstations that incorporate several of the functions of a laboratory sample processing department. The options also include total laboratory automation systems that use conveyors to link sample processing functions to analyzers and often include postanalytical features such as refrigerated storage and sample retrieval. Most importantly, this report reviews a recommended process for evaluating the need for new automation and for identifying the specific requirements of a laboratory and developing solutions that can meet those requirements. The report also discusses some of the practical considerations facing a laboratory in a new implementation and reviews the concept of machine vision to replace human inspections.

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