Urinary tract infections (UTIs) are among the most common bacterial infections in outpatient and inpatient settings. They significantly contribute to the use and misuse of antibiotics, threatening the present and the future of global healthcare.
Traditional manual urine culture methods often struggle to meet the demands of high-volume laboratories, due to long turnaround times (TAT) and human error potential.
In recent decades, automated systems have revolutionized how labs handle various bacterial cultures, offering solutions to the most common limitations in microbiology sample processing. This is also true for urine analysis, where this advanced technology streamlined workflows, enhanced diagnostic accuracy, and reduced the time required to deliver actionable results.
The Global Burden of Urinary Tract Infections (UTIs)
Gram-negative bacteria, including Escherichia coli, Klebsiella, Proteus, Pseudomonas, and Enterobacter, are the primary cause of UTIs. However, emerging pathogens like Staphylococcus and Serratia are also becoming more prominent.
UTIs affect millions of people worldwide every year, and in 2019, an estimated 405 million infections occurred, resulting in over 267,000 deaths. Notably, these diseases disproportionately affect women, with a 3.6 times higher likelihood of contracting a UTI compared to men in the same age group. Although antibiotics can treat the majority of uncomplicated UTIs, the rise of drug-resistant isolates has made the accurate and rapid identification of pathogens of the highest priority.
The economic burden of UTIs is staggering. In Europe, the average cost per case is approximately €5,700; in the United States, it exceeds $13,000 for each hospitalization. Taken together, these figures amount to billions of dollars in healthcare expenditure annually, highlighting the urgent need for more efficient diagnostic tools.
The laboratory point of view: challenges of urine sample processing
Urine and blood remain among the most frequently processed specimens in microbiology laboratories. Particularly, the amount of urine samples creates logistical and operational challenges that can challenge even the most well-equipped labs.
Manual processing – inoculation, incubation, colony reading, and reporting – takes up approximately 30% of a technologist’s time. This time-consuming operation limits throughput and increases the risk of error based on inconsistent interpretation. Moreover, culture-based methodologies suffer from intrinsic limitations:
- Long TAT: Culture results typically take at least 18–24 hours, with additional time for Antimicrobial Susceptibility Testing (AST).
- Sensitivity: Diagnostic findings generally rely on human colony recognition, which is not always accurate and linked to clinical significance.
- Contamination issues: Discrimination of actual pathogens from contaminants remains an issue, especially with low-level growth.
- Standardization gaps: Despite recommendations, laboratories vary in following culture reports and establishing which isolates to characterize and where to test.
These inefficiencies delay diagnosis and compromise antimicrobial stewardship efforts, leading to unnecessary or inappropriate antibiotic treatment.
How Can Lab Workflow Automation Help Process and Analyze UTIs?
In recent years, lab automation has revolutionized microbiology processes. Automated urinalysis systems, more specifically, offer significant advantages in terms of speed, reliability, and integration with laboratory processes.
Designed specifically for high-volume microbiology labs, automation covers the key steps in the urine culture process:
- Standardized and precise inoculation with accurate volumes
- Incubation with real-time temperature monitoring
- Digital imaging for early microbial growth
- Artificial intelligence-based image analysis
Automation significantly reduces the time required for bacterial culturing by eliminating manual handling, ensuring faster microbial detection and earlier reporting of negative results. Studies have shown that implementing automation systems can cut TAT by up to 24 hours, allowing clinicians to make informed therapeutic decisions sooner.
Moreover, automation led to measurable improvements in workflow standardization and productivity, and plate recognition software enhanced with AI can further speed up result reporting by automatically discarding negatives and assigning the correct workup to positive ones.
Finally, automation also enhances traceability and reproducibility. Digital imaging offers objective images of growth patterns, reducing inter-operator variability. Moreover, integration with LIS facilitates data transfer, minimizing errors and facilitating compliance with regulatory standards.
Embracing Automated Urinalysis Systems for Better Patient Outcomes
As UTI incidence rises and antimicrobial resistance grows more complicated, clinical labs must adapt to maintain high-quality care. Automated urinalysis presents an excellent answer by meeting the dual demands for high sample volume and accuracy of diagnosis.
Through tools like the WASP automated microbiology platform, labs can achieve greater efficiency, shorter TAT, and improved antimicrobial stewardship. By including automated lab workflow in routine urine testing, healthcare providers can deliver prompt, precise diagnoses that positively affect patient outcomes and data to guide global infection control efforts.
Looking ahead, advancements in AI, robotics, and digital interpretation promise to further refine automated urine culture, making it an indispensable component of modern clinical microbiology.
Bibliography
- Timm MR, Russell SK, Hultgren SJ. Urinary tract infections: pathogenesis, host susceptibility and emerging therapeutics. Nat Rev Microbiol. 2025 Feb;23(2):72-86.
- Bermudez T, Schmitz JE, Boswell M, Humphries R. 2025. Novel technologies for the diagnosis of urinary tract infections. J Clin Microbiol 63:e00306-24.
- Culbreath K, Piwonka H, Korver J, Noorbakhsh M.2021.Benefits Derived from Full Laboratory Automation in Microbiology: a Tale of Four Laboratories. J Clin Microbiol
- Cherkaoui A, Renzi G, Martischang R, et al. Impact of Total Laboratory Automation on Turnaround Times for Urine Cultures and Screening Specimens for MRSA, ESBL, and VRE Carriage: Retrospective Comparison With Manual Workflow. Front Cell Infect Microbiol. 2020 Oct 28;10:552122.
Join CoScience HUB
Create your CoScience HUB account now to access cutting-edge science and position yourself at the forefront of innovation.
Sign Up Now
