Impact of total laboratory automation on workflow and specimen processing time for culture of urine specimens
- 379 Downloads
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.
KeywordsTotal 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.
No informed consent was needed for this study since no personal data were involved.
Approval by the institutional review board was not required for this study.
- 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
- 11.McAdam AJ (2018) Total laboratory automation in clinical microbiology: a micro-comic strip. J Clin Microbiol 56 (4)Google Scholar
- 14.Bailey A, Ledeboer N, Burnham CA (2018) Clinical microbiology is growing up: the total laboratory automation revolution. Clin Chem in pressGoogle Scholar
- 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
- 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
- 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.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