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

  • Melanie L. Yarbrough
  • William Lainhart
  • Allison R. McMullen
  • Neil W. Anderson
  • Carey-Ann D. BurnhamEmail author
Original Article


Total laboratory automation (TLA) has the potential to reduce specimen processing time, improve standardization of cultures, and decrease turnaround time (TAT). The objective of this study was to perform a detailed interrogation of the impact of TLA implementation in all aspects of the workflow for routine culture of urine specimens. Using a detailed motion capture study, the time required for major steps of processing and result reporting were prospectively assessed for urine samples prior to (n = 215) and after (n = 203) implementation of the BD Kiestra TLA system. Specimens were plated on all shifts, but cultures were read only during the day shift for both time periods. Significant increases were noted in the time from receipt to inoculation (23.0 min versus 32.0 min, p < 0.001) and total processing time (28.0 min versus 66.0 min, p < 0.0001) for urine specimens post-TLA. Rates of positive (18.6% versus 16.3%) and negative (71.2% versus 79.3%) urine cultures remained stable through the pre- and post-TLA time periods (p = 0.58). There were no changes in TAT for organism identification or susceptibility results. The time to final report was decreased from 43.8 h pre-TLA to 42.0 h post-TLA, which was attributed to significant decreases in TAT for negative cultures (42.0 h versus 37.5 h, p = 0.01). These findings demonstrate that changes in laboratory workflow are necessary to maximize efficiency of TLA and optimize TAT.


Total laboratory automation Urine culture Turnaround time Kiestra 



We thank Angela Shupe and Colleen Haug for assistance in collection of observational data. We thank Christopher Coon for assistance with data entry. We thank the staff of Barnes-Jewish Hospital for their ongoing efforts for the patients served by the clinical laboratory.

Compliance with ethical standards

Conflict of interest

Carey-Ann Burnham has received honoraria from BD for development of educational sessions on laboratory automation. MLY has received personal fees from Bio-Rad and Agena Biosciences. WL, ARM, and NWA have nothing to declare.

Informed consent

No informed consent was needed for this study since no personal data were involved.

Ethical approval

Approval by the institutional review board was not required for this study.

Supplementary material

10096_2018_3391_MOESM1_ESM.pdf (100 kb)
Online Resource 1 (PDF 100 kb)
10096_2018_3391_MOESM2_ESM.pdf (99 kb)
Online Resource 2 (PDF 99 kb)


  1. 1.
    Sautter RL, Thomson RB Jr (2015) Consolidated clinical microbiology laboratories. J Clin Microbiol 53(5):1467–1472CrossRefGoogle Scholar
  2. 2.
    Garcia E, Ali AM, Soles RM, Lewis DG (2015) The American Society for Clinical Pathology’s 2014 vacancy survey of medical laboratories in the United States. Am J Clin Pathol 144(3):432–443CrossRefGoogle Scholar
  3. 3.
    Genzen JR, Burnham CD, Felder RA, Hawker CD, Lippi G, Peck Palmer OM (2018) Challenges and opportunities in implementing total laboratory automation. Clin Chem 64(2):259–264CrossRefGoogle Scholar
  4. 4.
    Bourbeau PP, Ledeboer NA (2013) Automation in clinical microbiology. J Clin Microbiol 51(6):1658–1665CrossRefGoogle Scholar
  5. 5.
    Ledeboer NA, Dallas SD (2014) The automated clinical microbiology laboratory: fact or fantasy? J Clin Microbiol 52(9):3140–3146CrossRefGoogle Scholar
  6. 6.
    Croxatto A, Prod'hom G, Faverjon F, Rochais Y, Greub G (2016) Laboratory automation in clinical bacteriology: what system to choose?. Clin Microbiol Infect 22(3):217–235CrossRefGoogle Scholar
  7. 7.
    Da Rin G, Zoppelletto M, Lippi G (2016) Integration of diagnostic microbiology in a model of total laboratory automation. Lab Med 47(1):73–82CrossRefGoogle Scholar
  8. 8.
    Faron ML, Buchan BW, Coon C, Liebregts T, van Bree A, Jansz AR, Soucy G, Korver J, Ledeboer NA (2016) Automatic digital analysis of chromogenic media for vancomycin-resistant-enterococcus screens using Copan WASPLab. J Clin Microbiol 54(10):2464–2469CrossRefGoogle Scholar
  9. 9.
    Faron ML, Buchan BW, Vismara C, Lacchini C, Bielli A, Gesu G, Liebregts T, van Bree A, Jansz A, Soucy G, Korver J, Ledeboer NA (2016) Automated scoring of chromogenic media for detection of methicillin-resistant staphylococcus aureus by use of WASPLab image analysis software. J Clin Microbiol 54(3):620–624CrossRefGoogle Scholar
  10. 10.
    Kirn TJ (2016) Automatic digital plate reading for surveillance cultures. J Clin Microbiol 54(10):2424–2426CrossRefGoogle Scholar
  11. 11.
    McAdam AJ (2018) Total laboratory automation in clinical microbiology: a micro-comic strip. J Clin Microbiol 56 (4)Google Scholar
  12. 12.
    Burckhardt I, Panitz J, Burckhardt F, Zimmermann S (2017) Identification of Streptococcus pneumoniae: development of a standardized protocol for optochin susceptibility testing using total lab automation. Biomed Res Int 2017:4174168CrossRefGoogle Scholar
  13. 13.
    Hombach M, Jetter M, Blochliger N, Kolesnik-Goldmann N, Bottger EC (2017) Fully automated disc diffusion for rapid antibiotic susceptibility test results: a proof-of-principle study. J Antimicrob Chemother 72(6):1659–1668CrossRefGoogle Scholar
  14. 14.
    Bailey A, Ledeboer N, Burnham CA (2018) Clinical microbiology is growing up: the total laboratory automation revolution. Clin Chem in pressGoogle Scholar
  15. 15.
    Dauwalder O, Landrieve L, Laurent F, de Montclos M, Vandenesch F, Lina G (2016) Does bacteriology laboratory automation reduce time to results and increase quality management?. Clin Microbiol Infect 22(3):236–243CrossRefGoogle Scholar
  16. 16.
    Croxatto A, Dijkstra K, Prod’hom G, Greub G (2015) Comparison of inoculation with the InoqulA and WASP automated systems with manual inoculation. J Clin Microbiol 53(7):2298–2307CrossRefGoogle Scholar
  17. 17.
    Froment P, Marchandin H, Vande Perre P, Lamy B (2014) Automated versus manual sample inoculations in routine clinical microbiology: a performance evaluation of the fully automated InoqulA instrument. J Clin Microbiol 52(3):796–802CrossRefGoogle Scholar
  18. 18.
    Graham M, Tilson L, Streitberg R, Hamblin J, Korman TM (2016) Improved standardization and potential for shortened time to results with BD Kiestra total laboratory automation of early urine cultures: a prospective comparison with manual processing. Diagn Microbiol Infect Dis 86(1):1–4CrossRefGoogle Scholar
  19. 19.
    Mutters NT, Hodiamont CJ, de Jong MD, Overmeijer HP, van den Boogaard M, Visser CE (2014) Performance of Kiestra total laboratory automation combined with MS in clinical microbiology practice. Ann Lab Med 34(2):111–117CrossRefGoogle Scholar
  20. 20.
    Theparee T, Das S, Thomson RB, Jr. (2018) 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. J Clin Microbiol 56 (1)Google Scholar
  21. 21.
    Buchan BW, Olson WJ, Mackey TL, Ledeboer NA (2014) Clinical evaluation of the walk-away specimen processor and ESwab for recovery of Streptococcus agalactiae isolates in prenatal screening specimens. J Clin Microbiol 52(6):2166–2168CrossRefGoogle Scholar
  22. 22.
    Strauss S, Bourbeau PP (2015) Impact of introduction of the BD Kiestra InoqulA on urine culture results in a hospital clinical microbiology laboratory. J Clin Microbiol 53(5):1736–1740CrossRefGoogle Scholar
  23. 23.
    Klein S, Nurjadi D, Horner S, Heeg K, Zimmermann S, Burckhardt I (2018) Significant increase in cultivation of Gardnerella vaginalis, Alloscardovia omnicolens, Actinotignum schaalii, and Actinomyces spp. in urine samples with total laboratory automation. Eur J Clin Microbiol Infect Dis 37(7):1305–1311CrossRefGoogle Scholar
  24. 24.
    Lainhart W, Burnham CA (2018) Enhanced recovery of fastidious organisms from urine culture in the setting of total laboratory automation. J Clin Microbiol 56 (8)Google Scholar
  25. 25.
    Dauwalder O, Vandenesch F (2014) Clinical microbiology laboratory: from the Pasteur model to the 24/7 clinical chemistry concept. Clin Microbiol Infect 20(10):O593–O594CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Melanie L. Yarbrough
    • 1
  • William Lainhart
    • 1
  • Allison R. McMullen
    • 1
    • 2
  • Neil W. Anderson
    • 1
  • Carey-Ann D. Burnham
    • 1
    Email author
  1. 1.Department of Pathology and ImmunologyWashington University in St. Louis School of MedicineSaint LouisUSA
  2. 2.Department of PathologyMedical College of Georgia at Augusta UniversityAugustaUSA

Personalised recommendations