Evidence map›Paper›PMID 30269180›Full record

ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2018

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 Burnham

Abstract read
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Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
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  3. Deep Learning-Based Rapid Identification ofRisk management and healthcare policy · 2026
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  15. Reducing the time between inoculation and first-read of urine cultures using total lab automation significantly reduces turn-around-time of positive culture results with minimal loss of first-read sensitivity.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019
    Article
  16. Laboratory Automation in Clinical Microbiology.Bioengineering (Basel, Switzerland) · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Melanie L YarbroughDepartment of Pathology and Immunology, Washington University in St. Louis School of Medicine, 660 S. Euclid Ave, Campus Box 8118, Saint Louis, MO, 63110, USA.
William LainhartDepartment of Pathology and Immunology, Washington University in St. Louis School of Medicine, 660 S. Euclid Ave, Campus Box 8118, Saint Louis, MO, 63110, USA.
Allison R McMullenDepartment of Pathology and Immunology, Washington University in St. Louis School of Medicine, 660 S. Euclid Ave, Campus Box 8118, Saint Louis, MO, 63110, USA.
Neil W AndersonDepartment of Pathology and Immunology, Washington University in St. Louis School of Medicine, 660 S. Euclid Ave, Campus Box 8118, Saint Louis, MO, 63110, USA.
Carey-Ann D BurnhamDepartment of Pathology and Immunology, Washington University in St. Louis School of Medicine, 660 S. Euclid Ave, Campus Box 8118, Saint Louis, MO, 63110, USA. cburnham@wustl.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Automation, LaboratoryWorkflowBacteriological TechniquesHumansSpecimen HandlingTime and Motion StudiesUrineKiestraTotal laboratory automationTurnaround timeUrine culture

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.