Finding reliable methods to streamline lab outcomes sometimes feels insurmountable. From differing workcells to multiple modality manufacturers, researchers who have to work with these ever-changing variables inevitably become variables themselves.
Unfortunately, having a sluggish laboratory turnaround time (TAT) has real, and sometimes dire consequences. Delays in lab results can cause a 61% longer stay in the emergency room and a 43% treatment delay. Luckily, you can optimize your lab’s workflows. By tracking your lab’s average TAT, you can spot inefficiencies and find actionable improvements.
Introduction to laboratory turnaround time (TAT)
TAT, or turnaround time in a laboratory, refers to the total time it takes for a research lab to complete a workflow, DMTA cycle, or for a medical lab to report findings from a sample.
Having a shorter TAT may be the make-or-break metric that propels your team to, for example, make a novel insight during the drug discovery process, ultimately allowing your lab to compete.
Why is turnaround time important in the laboratory?
Tracking your laboratory’s TATs can improve:
- Refining diagnostics: One study found that non-analytical causes may be responsible for up to 96% of delayed diagnoses.
- Fast-tracking research: Prompt TATs allow life researchers to analyze data quickly, potentially sparking quicker breakthroughs that can fast-track a study to clinical trials.
- Promoting customer satisfaction: Customers expect fast and accurate results. Improving your lab’s TATs can quickly build trust, maintain and attract a client base, and give you the bandwidth to amend potential errors.
What is the normal turnaround time for lab results?
You can expect standard research protocols such as basic assays, cell culture assays, genome sequencing, or microscopy to take anywhere from an hour to three weeks to process. This depends on modalities used to acquire data, workflow queues, and sample type.
Factors such as processing a complex sample can cause your laboratory’s TAT to take even longer. Most labs may redo some tasks during the pre-analytical phase, as 60% to 70% of total laboratory errors occur during this time.
How to measure turnaround time in the laboratory
Some sub-processes you and your colleagues can track are:
- Sample collection
- Sample processing
- Result reporting
- Cataloging and archiving
The Six Sigma problem-solving methodology can also help you define, measure, analyze, improve, and control (DMAIC) your lab processes. Monitoring your benchmarks can also help you identify bottlenecks and error-causing variables while streamlining your workflows.
When you have your preliminary laboratory TATs, you can evaluate what makes your workflows function more efficiently. Some standard metrics you can use to better understand your median, 75%, and 25% quartile TATs are:
- Average TAT is the most straightforward metric. It represents the mean time it takes to deliver results and provides a general overview of lab efficiency.
- Peak vs off-peak TAT: This metric may take several weeks to compile, but it reveals how peak sample volume periods lead to longer sample processing.
- Percentage of results delivered within target timeframes: This metric tracks how often your lab meets its throughput goals. For instance, your lab processes a liver tissue sample within six days, 90% of the time.
10 ways to reduce laboratory turnaround time
1. Optimize sample transportation
Some resources you can implement to standardize transported sample speeds are by using:
- Autonomous mobile robots (AMRs): AMRs can flexibly transport samples to various lab areas and help to unlock after-hours productivity.
- Automated track systems: Much like how a train moves raw materials to important logistical hubs, automated track systems can move bio materials around your lab with minimal contamination.
- Magnetically levitating planar movers: The difference between magnetically levitated systems and automated track systems is that the former can achieve significantly higher speeds while eliminating maintenance caused by friction, significantly reducing downtime.
- Optimized courier routes: A planned route can lower your laboratory’s TATs if your laboratory needs to transport samples for external processing and analysis.
- Integrating automated hardware solutions: Green Button Go Orchestrator can conduct automated hardware and software from various manufacturers to process samples outside of working hours.
2. Automate sample processing
Unlike their human counterparts, Automated Liquid Handlers and Robotics do not get aches from carrying out repetitive actions like pipetting.
GBG Scheduler builds upon these automated hardware efficiencies by optimizing longer sequences of tasks and offering real-time data on the process.
By automating sample processing in your lab to leverage hours typically not staffed by scientists, you can add 128 working hours to the 40-hour work week, exponentially increasing your lab’s throughput.
3. Integrate laboratory information management systems (LIMS)
A Laboratory Information Management System (LIMS) can allow you to find customized data acquisition methods for your lab. A LIMS solution streamlines your lab’s workflows by tracking a sample’s entire lifecycle, including gathering results and data reporting.
4. Prioritize preventative maintenance for equipment
Prioritizing preventive rather than reactive maintenance can immediately reduce your lab’s downtime. In manufacturing, operations that relied on preventive maintenance had 52.7% less unplanned downtime and 78.5% fewer equipment defects.
Unexpected maintenance may seem inevitable, but using automation software to track key metrics can immediately identify workflow irregularities.
5. Optimize staffing during peak hours
Allocating your staff’s skills to high-throughput workflows while also finding time to train them on additional equipment may only feel feasible during downtime. But, the key to creating a more cohesive lab is reviewing where you can optimize your staff during working hours.
Using data collected from your automated hardware and software solutions can help you identify opportunities for dynamic scheduling based on peak workcell throughputs, train staff on more complex equipment, and track sample queues.
6. Standardize workflow protocols
Standardized protocols allow your lab to troubleshoot issues meaningfully while reducing the time spent developing a reactive and potentially ineffective plan.
Another advantage of standardized workflow protocols is that they build trust in your laboratory’s TATs and efficiency. While designing consistent workflows often takes a backseat to more pressing tasks, implementing protocols can circumvent delays associated with using differing equipment manufacturers.
7. Use real-time monitoring tools
Real-time monitoring tools of key performance indicators (KPIs) can meaningfully increase your lab’s throughput. With them, the University of Lausanne’s microbiology department processed 1,500 SARS-CoV-2 tests per day.
These tools allow you to make data-driven decisions to allocate your lab’s resources more effectively, ensuring that your workflows are not disrupted or delayed.
8. Implement AI and machine learning for data analysis
Training AI or machine learning (AI or ML) software can alleviate the massive undertaking of analyzing hundreds of samples. You won’t reduce your capabilities by outsourcing this; instead, you can train AI or ML software to accurately identify any data anomalies while quantifying them in a dataset.
GBG supports AI/ML software by gathering your system’s data and presenting it to the software so the additional data can be incorporated and analyzed, providing more accurate results.
9. Reduce sample retesting through quality control
Stringent quality control (QC) can protect your lab from sample retesting and repeat preparation, lowering the redundant work in your lab’s workflows.
Automating these workflows can make QC more approachable. You can design consistent processes and ensure that every sample is processed identically, which promotes repeatability.
10. Streamline reporting and result delivery
Automated reporting tools combine compiling, cataloging, and analyzing results. They also highlight data trends and anomalies, reducing the likelihood of errors and providing a clearer understanding of a test’s datasets.
Overall, streamlined reporting tools can provide better TATs for the analysis stage since they cut down on administrative resources and ensure consistency across multiple platforms.
Optimizing TAT for laboratory success
Turnaround time (TAT) highlights inefficient processes and provides real-time insights into your lab’s performance. With more reliable and repeatable results, you can streamline your laboratory’s TATs, reducing the time spent amending errors.
However, efficiency is one of many valuable outcomes of tracking laboratory TATs. Outlining processes and metrics packaged for auditing can help your lab uphold strict regulatory standards.
Following compliance metrics, in turn, creates trust between your lab and external stakeholders. By focusing on these strategies, you can ensure more reliable, efficient TATs without compromising data quality.
Automated solutions can offer your lab easy-to-use tools to maintain consistency, reduce manual error, and increase throughput. If you would like to improve your laboratory’s TATs, the Biosero team can help you find automated solutions for your lab, regardless of its size. Contact us today to get started.
