Journal:Conversion of a classical microbiology laboratory to a total automation laboratory enhanced by the application of lean principles
| Full article title | Conversion of a classical microbiology laboratory to a total automation laboratory enhanced by the application of lean principles |
|---|---|
| Journal | Microbiology Spectrum |
| Author(s) | Trigueiro, Graça; Oliveira, Carlos; Rodrigues, Alexandra; Seabra, Sofia; Pinto, Rui; Bala, Yohann; Granado, Monica G.; Vallejo, Sandra; Gonzalez, Victoria; Cardoso, Carlos |
| Author affiliation(s) | Dr. Joaquim Chaves Clinical Analysis Laboratory, bioMérieux |
| Primary contact | Email: alexandra dot cristina at jcs dot pt |
| Editors | Doucet-Populaire, Florence C. |
| Year published | 2024 |
| Volume and issue | 12(2) |
| Article # | e02153-23 |
| DOI | 10.1128/spectrum.02153-23 |
| ISSN | 2165-0497 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://journals.asm.org/doi/10.1128/spectrum.02153-23 |
| Download | https://journals.asm.org/doi/pdf/10.1128/spectrum.02153-23?download=true (PDF) |
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This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
Laboratory automation in microbiology improves productivity and reduces sample turnaround times (TATs). However, its full potential can be unlocked through the optimization of workflows by adopting lean principles. This study aimed to explore the relative impact of laboratory automation and continuous improvement events (CIEs) on productivity and TATs. Laboratory automation took place in November 2020 and consisted of the introduction of WASPLab and VITEK MS systems. CIEs were run in May and September 2021. Before the conversion, the laboratory processed approximately 492 samples on weekdays and had 10 full-time equivalent (FTE) staff for a productivity of 49 samples/FTE/day. In March 2021, after laboratory automation, the caseload went up to approximately 621 while the FTEs decreased to 8.5, accounting for a productivity improvement to 73 samples/FTE/day. The hypothetical productivity went up to 110 samples/FTE/day following CIEs, meaning that the laboratory could at that point deal with a caseload increase to approximately 935 with unchanged FTEs. Laboratory conversion also led to an improvement in TATs for all sample types. For vaginal swabs and urine samples, median TATs decreased from 70.3 hours (interquartile range [IQR]: 63.5–93.1) and 73.7 hours (IQR: 35.6–50.7) to 48.2 hours (IQR: 44.8–67.7) and 40.0 hours (IQR: 35.6–50.7), respectively. Automation alone was responsible for 37.2% and 75.8% of TAT reduction, respectively, while the remaining reduction of 62.8% and 24.2%, respectively, was achieved due to CIEs. The laboratory reached productivity and TAT goals predefined by the management after CIEs. In conclusion, automation substantially improved productivity and TATs, while the subsequent implementation of lean management further unlocked the potential of laboratory automation.
Importance
In this study, we combined total laboratory automation with lean management to show that appropriate laboratory work organization enhanced the benefit of the automation and substantially contributed to productivity improvements. Globally, the rapid availability of accurate results in the setting of a clinical microbiology laboratory is part of patient-centered approaches to treat infections and helps the implementation of antibiotic stewardship programs backed by the World Health Organization (WHO). Locally, from the point of view of laboratory management, it is important to find ways of maximizing the benefits of the use of technology, as total laboratory automation is an expensive investment.
Keywords: turnaround time, productivity, lean principles, laboratory automation, change management
Introduction
Compared to general hematology and biochemistry laboratories, automation was late to arrive in microbiology laboratories because of the complexity of the processes involved. [1–3] The most important driver of automation adoption in microbiology laboratories in recent times is represented by a shift of paradigm in clinical microbiology that increased the demand for rapid and accurate results. [1, 2, 4] The availability of such results is important for the success of patient-centered approaches to treat infections and for antibiotic stewardship programs. [5] Over the past 20 years, and especially since the onset of the coronavirus disease 2019 (COVID-19) pandemic, microbiology laboratories have been increasingly adopting technologies and processes that improve quality and efficiency, alongside a reduction in sample turnaround times (TATs). [1]
In total laboratory automation systems, all main system components (i.e., plating/streaking unit, incubation unit, high-resolution imaging system, colony picking for identification and antimicrobial susceptibility testing, and post-imaging analysis workstation) are robot driven. Artificial intelligence (AI) has recently been incorporated into imaging analysis to automatically interpret plates. Automating analyses has been the key to improving productivity. [6–8] System components may be connected via a conveyor belt system or placed in convenient locations in laboratories. [9] In the WASPLab system, plates are sorted out to stackers and transferred to workstations by technologists. The systems must be flexible enough to accommodate several variables, such as specimen types and non-standardized containers. Moreover, some samples are sent to be screened for a specific pathogen (e.g., throat swab samples to be screened for Streptococcus pyogenes), while others may require a variety of microbial culture and identification methods for a full diagnostic work-up. [1]
There are numerous advantages to total laboratory automation. Although a high investment is needed for the conversion from a manual to an automated lab, in the long run, automated laboratories are cheaper to run. [4] The implementation of total laboratory automation increases efficiency, measured as turnaround time and total productivity, and improves the quality of testing, thanks to the standardization and optimization of the procedures. Automation offers a possibility of better sample management and traceability, often requires lower volumes of samples, renders laboratory accreditation easier to obtain, and lowers the biological risk to the operators. [2, 10] In the context of a microbiology laboratory, a significantly better recovery of pathogens—defined as a greater number of unique colony morphologies, a higher proportion of discrete colonies, and the identification of more species/plates—can be achieved, as described by Bailey et al. [1]
However, there are two principal elements of laboratory automation: hardware and workflow. [1] Total laboratory automation improves efficiency through the reduction of repetitive tasks with moderate added value, i.e., through the modification of the workflow. Automated incubators with digital imaging drastically reduce the number of manipulations of the culture media plates. About 97% of samples are suitable for automatic processing. [2] Employees often resist change. Fear of the unknown, lack of trust toward leaders, comfort derived from a familiar routine, lack of perception that a change is needed, perceived lack of knowledge or competence and the necessity to retrain, poor communication of what will happen from the management, and exhaustion or saturation when changes are too frequent are all factors at the basis of resistance to change. [12] Therefore, to be successful, the introduction of a change must be “managed” through a process known as change management. Change management occurs through steps (i.e., prepare, implement, monitor, sustain, and reevaluate). [12] In particular, a continuous improvement in streamlining workflow must be introduced. Change management is done with the use of lean methodology, an evidence-based approach to increase quality and efficiency that combines philosophy, processes, people, and structures. [13]
The study aimed to assess the relative impact of laboratory automation, change management, and continuous improvement events (CIEs) on key performance indicators (KPIs, i.e., full-time equivalent [FTE]/day and TAT) in a clinical microbiology laboratory concerning the processing of urine samples, vaginal swabs, and stool samples that comprise over 90% of the caseload of the laboratory.
Results
Pre-conversion
Caseload and FTE
In May 2019, prior to the conversion, Dr. Joaquim Chaves Saúde Clinical Analysis Laboratory (JCS) processed on average 492 samples/day on weekdays, 389 on Saturdays, and approximately 12 on Sundays. Three-quarters of the samples received were urine samples, 16% were vaginal swabs, 4% stool samples, 2% pharyngeal swabs, and about 1% were samples sent in for mycology testing. Other sample types comprised 3%. The laboratory had 10 FTEs of staff at the time.
KPIs
The productivity pre-conversion was 49 samples/FTE/day (Table 1). The median TAT was the shortest for the negative urine samples (median 13 hours; interquartile range [IQR; 3.1; 23.7]) and the longest for the positive stool samples (median 93.3 hours; IQR [70.1; 122.8]). Positive urine and vaginal swabs, in comparison, had a similar median TAT with a narrower IQR for vaginal swabs (median 73.7 hours; IQR [43.4; 94.6] versus median 70.3 hours; IQR [64.5; 93.1]). Full results are given in Table 2.
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Acknowledgements
Funding
Competing interests
Yohann Bala, Monica Gutiérrez Granado, Sandra Vallejo, and Victoria Gonzalez are employees of bioMérieux SA.
References
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
