Literature DB >> 26577142

Does bacteriology laboratory automation reduce time to results and increase quality management?

O Dauwalder1, L Landrieve2, F Laurent3, M de Montclos4, F Vandenesch5, G Lina6.   

Abstract

Due to reductions in financial and human resources, many microbiological laboratories have merged to build very large clinical microbiology laboratories, which allow the use of fully automated laboratory instruments. For clinical chemistry and haematology, automation has reduced the time to results and improved the management of laboratory quality. The aim of this review was to examine whether fully automated laboratory instruments for microbiology can reduce time to results and impact quality management. This study focused on solutions that are currently available, including the BD Kiestra™ Work Cell Automation and Total Lab Automation and the Copan WASPLab(®).
Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Automation; InoqulA+(TM); ReadA(TM); WASPLab; clinical microbiology laboratory; time to results; traceability

Mesh：

Year:  2015        PMID： 26577142     DOI： 10.1016/j.cmi.2015.10.037

Source DB:  PubMed          Journal:  Clin Microbiol Infect        ISSN： 1198-743X            Impact factor:   8.067


  27 in total

Review 1.  Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for the Rapid Detection of Antimicrobial Resistance Mechanisms and Beyond.

Authors:  Marina Oviaño; Germán Bou
Journal:  Clin Microbiol Rev       Date:  2018-11-28       Impact factor: 26.132

2.  How small modifications in laboratory workflow of blood cultures can have a significant impact on time to results.

Authors:  B Van den Poel; A Klak; S Desmet; J Verhaegen
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2018-06-30       Impact factor: 3.267

3.  Laboratory automation reduces time to report of positive blood cultures and improves management of patients with bloodstream infection.

Authors:  Giuseppe Vittorio De Socio; Francesco Di Donato; Riccardo Paggi; Chiara Gabrielli; Alessandra Belati; Giuseppe Rizza; Martina Savoia; Antonella Repetto; Elio Cenci; Antonella Mencacci
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2018-09-14       Impact factor: 3.267

4.  Impact of total laboratory automation on workflow and specimen processing time for culture of urine specimens.

Authors:  Melanie L Yarbrough; William Lainhart; Allison R McMullen; Neil W Anderson; Carey-Ann D Burnham
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2018-09-29       Impact factor: 3.267

5.  Automatic Digital Plate Reading for Surveillance Cultures.

Authors:  Thomas J Kirn
Journal:  J Clin Microbiol       Date:  2016-08-10       Impact factor: 5.948

6.  Machine Learning Takes Laboratory Automation to the Next Level.

Authors:  Bradley A Ford; Erin McElvania
Journal:  J Clin Microbiol       Date:  2020-03-25       Impact factor: 5.948

7.  Evaluation of the WASPLab Segregation Software To Automatically Analyze Urine Cultures Using Routine Blood and MacConkey Agars.

Authors:  Matthew L Faron; Blake W Buchan; Ryan F Relich; James Clark; Nathan A Ledeboer
Journal:  J Clin Microbiol       Date:  2020-03-25       Impact factor: 5.948

Review 8.  Consolidation of Clinical Microbiology Laboratories and Introduction of Transformative Technologies.

Authors:  Zisis Kozlakidis; Alex van Belkum; Olivier Vandenberg; Géraldine Durand; Marie Hallin; Andreas Diefenbach; Vanya Gant; Patrick Murray
Journal:  Clin Microbiol Rev       Date:  2020-02-26       Impact factor: 26.132

9.  Scanning Electron Microscope: A New Potential Tool to Replace Gram Staining for Microbe Identification in Blood Cultures.

Authors:  Gabriel Haddad; Sara Bellali; Tatsuki Takakura; Anthony Fontanini; Yusuke Ominami; Jacques Bou Khalil; Didier Raoult
Journal:  Microorganisms       Date:  2021-05-28

10.  Total Laboratory Automation and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Improve Turnaround Times in the Clinical Microbiology Laboratory: a Retrospective Analysis.

Authors:  Talent Theparee; Sanchita Das; Richard B Thomson
Journal:  J Clin Microbiol       Date:  2017-12-26       Impact factor: 5.948
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