Integral to patient care and the overall healthcare system, diagnostic testing continues to surge. Driven by the persistence of chronic disorders and infectious diseases, and the emergence of new diagnostic assays, this surge has prompted high-throughput areas of the clinical lab to implement automation for safe, accurate, and timely processing of samples. Robust and flexible automated solutions for pre- and postanalytic specimen sequencing remains vital to meeting testing demands and tackling the critical shortage of experienced laboratory personnel.
Complex, labor-intensive demands
Sometimes viewed as a “factory” that produces diagnostic data from testing patient specimens, high-volume clinical labs support multiple concurrent production workflows. From the arrival of specimens to the delivery of final test results, clinical labs are expected to have quick turnaround times (TATs) with near-zero tolerance for loss or compromise of patient samples. A seemingly daunting task to manage, laboratory supervisors and their teams are discovering that efficient, reliable, and flexible automation systems compatible with modern digital infrastructure are up for the challenge. These systems optimize the spatial placement of specimen reception and analytical areas and improve workflows while reducing errors.
With an expected steady growth from 2023 to 2028, the North American Lab Automation Market will meet clinical lab pain points head-on to address the high burden of chronic disease, as well as the increasing demand for early diagnostics. From higher processing speeds and greater test accuracy to safer work environments and reduced laboratory staff workload, both pre-engineered standalone work cells and customized process solutions are providing the capability and capacity where needed to identify, prepare, route, and maintain patient specimens quickly yet accurately.
Automation evaluation and preparation
Able to assist in the efficient and accurate operations of high-throughput labs, advanced automation, including robot utilization, is well-suited to repetitive tasks that are vulnerable to error when performed manually. Target areas for workflow optimization often include barcode reading, sorting, decapping, aliquoting, recapping (or sealing), and rack loading, as well as other niche applications.
As only 30 percent of clinical labs in Europe, Japan, and the United States have implemented a significant degree of automation, new entrants into this field should be mindful of the critical requirements necessary for successful implementation. Key areas for lab evaluation and preparation include:
1. Container standardization and labeling
Container standardization and labeling are vital to maintaining a safe and efficient automated lab workflow that maximizes operational efficiency and protects patient data. In preparation for automation, laboratory supervisors should address several questions:
- What is the range (i.e., dimensions and type) of the specimen containers?
- Are labels printed with consistent quality using the same barcode schema?
- Are labels applied correctly and consistently?
Answering these questions will help determine the proper hardware and software solutions. While contemporary automation system design allows for multiple container configurations with some tolerance for label misplacement, there are limitations. The greater the range of tube sizes and label placement errors, the more challenging it is for automation to perform the task at the desired rate and accuracy.
Consider an automated system that connects with your lab’s IT infrastructure to facilitate the high level of traceability needed to control specimen workflows. Process automation systems with multiple connectivity and configurability options are ideal. They enable rapid data exchange across information systems and ensure compatibility with future IT architecture.
2. Process volume capacity
Knowing the volume of specimens to be processed is paramount when determining the optimum automation solution. In fact, this information is key to justifying the use of automation. There are a variety of preanalytic specimen processing instruments and systems designed to handle a few hundred specimens per hour and others capable of processing 2,500 specimens per hour.
Since most clinical labs receive patient specimens throughout the day in varying hourly volume, the peak and average volumes, automation capacity, diagnostic testing capacity, and TAT should be all evaluated to determine the appropriate scale of the automation solution.
Pay attention to postanalytic sorting and archiving system selection as well. Availability of postanalytic samples for retesting and add-on testing, length of archive hold, and archiving environmental requirements will contribute to defining the downstream workflow and suitable automation solution.
3. Facility workflow optimization
To enable seamless specimen processing, consider the existing facility floor plans. Older laboratory environments often feature divided areas for each department and process, whereas newer laboratory designs trend toward open-concept layouts, allowing for flexibility as throughput demands fluctuate.
In the rare instance where a new lab is being designed without the burden of outdated criteria, workflow can guide positioning, with automated preanalytic processing systems (e.g., bulk sorters/loaders) are placed near receiving docks, and preanalytic output systems (e.g., specimen sorters) are placed near high-volume diagnostic areas.
4. Dynamic clinical lab future
To meet pressing demands in both closed and open floor plans, laboratory supervisors should thoroughly evaluate current lab processes and strongly weigh the benefits of flexible automation systems, implementing them as appropriate. A shift to modular automation systems, including the integration of existing equipment, can not only optimize production but also reduce inefficiencies, bolster workforces, cut down expenses, and improve revenue for a competitive advantage.
Custom solutions provide workflow- and site-specific automation for many large, high-volume labs. On the other hand, flexible modular automation can expand operations for small to medium facilities, enabling labs of all sizes to become more resilient.