Evidence map›Paper›PMID 32248509›Full record

ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2020

Implementation of the WASPLab™ and first year achievements within a university hospital.

Abdessalam Cherkaoui, Gesuele Renzi, Arnaud Viollet, Mark Fleischmann, Ludovic Metral-Boffod, David Dominguez-Amado, Nicolas Vuilleumier, Jacques Schrenzel

Abstract read
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In one paragraph

Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 26% of its field
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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Pseudo-squared: Pseudomonas pseudo-outbreak lab investigation.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Performances of automated digital imaging of Gram-stained slides with on-screen reading against manual microscopy.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021
    Article
  6. Article
  7. Digitalization, clinical microbiology and infectious diseases.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020
    Article
  8. Review
  9. Article
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

8 authors at 1 institution in 1 country.

Abdessalam CherkaouiBacteriology Laboratory, Division of Laboratory Medicine, Department of Diagnostics, Geneva University Hospitals, Geneva, Switzerland. abdessalam.cherkaoui@hcuge.ch.
Gesuele RenziBacteriology Laboratory, Division of Laboratory Medicine, Department of Diagnostics, Geneva University Hospitals, Geneva, Switzerland.
Arnaud ViolletDivision of Biomedical Engineering, Procurement and Biomedical Engineering Center Vaud-Geneva, Geneva University Hospitals, Geneva, Switzerland.
Mark FleischmannDepartment of Information Technologies, Geneva University Hospitals, Geneva, Switzerland.
Ludovic Metral-BoffodDepartment of Diagnostics, Geneva University Hospitals, Geneva, Switzerland.
David Dominguez-AmadoPreanalytical Phase, Division of Laboratory Medicine, Department of Diagnostics, Geneva University Hospitals, Geneva, Switzerland.
Nicolas VuilleumierDivision of Laboratory Medicine, Department of Diagnostics, Geneva University Hospitals, Geneva, Switzerland.
Jacques SchrenzelBacteriology Laboratory, Division of Laboratory Medicine, Department of Diagnostics, Geneva University Hospitals, Geneva, Switzerland.
University Hospital of Geneva · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In essence, automation can be driven by several of the following incentives: increased processing capacity of the laboratory, better costs control through processes standardization, optimized traceability, or improved workflows to reduce turnaround times (TAT). This project aims at presenting an overview of the project management and change management with a focus on the major challenges addressed by lab staff and laboratory leadership during the different phases of the implementation of the WASPLab™ in a routine clinical bacteriology laboratory. This paper reports our experience and reviews changes in the bacteriology laboratory at Geneva University Hospitals when shifting to the WASPLab™. Practically, the whole automation process was segmented into different packages (specimen type-based segmentation) allowing sequential validation, staff training, and routine implementation. Such process allowed reaching 90% of the identified "automatable" samples within 1 year, including personal training, documentation for accreditation supported by publications, without interrupting routine operations. In addition, we implemented a validated automated solution for antimicrobial disk diffusion susceptibility testing. Structured supervision and accurate monitoring of all the activities related to the automation project including key partners such as IT support, technical committee, and after-sales service guaranteed a swift and timely achievement of the project allowing the improvement of the workflow in routine bacteriology within 1 year.

Indexed as

Outcome and Process Assessment, Health CareWorkflowAutomation, LaboratoryBacteriologyHospitals, UniversityHumansLaboratories, HospitalQuality ImprovementSwitzerlandAccuracyChange managementEfficiencyProject managementTurnaround timeWASPLab™Workflow

Identifiers

PMID32248509
OpenAlexW3015003897

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.