Rethinking workflow and processes can have an impact on the ability of any clinical laboratory to do more with less—and to do it well, providing greater value for the healthcare dollars spent. By looking at a clinical lab the way a workflow consultant would, a lab manager can evaluate the products, tasks, ergonomics, repetition, safety, and best practices that can make a lab more productive and increase efficiency and quality.
Automation as a way of improving processes
For clinical laboratories, efficiency equates to reducing the number of process steps. Automation tailored to the needs of a lab can expedite workflow and optimize the use of personnel and equipment, improve safety by reducing contact with potential biohazards, and allow staff to spend more time on abnormal or critical results.
In addition to improving operating efficiency by decreasing the number of labor-intensive hands-on steps and the potential for error, automation can improve metrics and the level of service they represent, including turnaround time (TAT) and TAT consistency. A lab with persistent downtime, extensive reruns due to questionable results, or a cumbersome manual storage system can see dramatic changes by automating its processes. In turn, these improvements can build confidence in the lab’s ability to deliver consistently accurate results in a timely manner.
Four issues tend to affect most labs’ ability to deliver timely, predictable results: TAT, management of STAT samples, transportation of samples, and post-analytic storage. Automation can improve performance in all four.
Healthcare institutions and their physicians depend on fast, predictable turnaround time to optimize patient care and control costs. When TAT is not dependable—when it fluctuates or is delayed—timely diagnosis and therapeutic intervention become more difficult to achieve, potentially calling into question a laboratory’s capabilities and institutional standing. When appropriately configured, a total lab automation system demonstrates its measurable ability to streamline and shorten TAT and TAT variability, even during peak workflows.
Effective management of STAT samples depends on the efficiency of the workflow. Given the critical nature of the time-sensitive information needed, improving the handling of STAT samples in order to expedite delivery of results has the potential to have a positive impact on patient care. One way to increase efficiency is to use automation that ensures true STAT prioritization throughout the entire process. This maintains one process for all samples, whether routine or STAT, but allows STATS to bypass all other samples that are not urgent.
Transportation of samples
Automated handling of samples offers the benefit of time savings with little or no need for human intervention. Staff touch a specimen tube once, and the system handles it the rest of the way.
Installing a transportation system between pre-analytics and analytics and between analytics and storage can markedly improve efficiency and reduce manual steps by as much as 80%, but that is not the only thing that can be done. To increase efficiency further, it’s important to know how traffic is routed on the transport lines. Ideally, the transport system should be bi-directional and, when it becomes available, multi-level. This separates full samples from empty ones in dedicated lanes and gives labs fast, predictable TAT, even during peak workflows.
Manual processes often result in delays in locating archived specimens for add-on or reflex testing. One way to reduce or eliminate potential workflow disruptions is to automate storage and retrieval.
Manual archiving processes can require logging each specimen’s rack location in an Excel spreadsheet or placing samples into a plastic rack based on accession numbers. In either case, the specimen racks are manually transported to a refrigerator. When a sample is required, a laboratorian can go to the refrigerator to find it for an add-on test. If the sample is not there, he or she returns to the bench and computer terminal to search for another sample. It can require 10 minutes or more to retrieve a single specimen.
There are different levels of automation that can minimize or eliminate these manual steps and provide quick access to the sample and immediate transport to the analytics for testing. Semi-automated systems archive samples in trays that are manually transported to the refrigerator. Fully automated systems take this a step further, with automated delivery to the storage unit and automated retrieval once a subsequent test is ordered.
Improving processes using LEAN principles
LEAN is a customer-centric methodology used to continuously improve any process through the elimination of waste. It is a pathway to better quality and lower costs.
LEAN management, as a concept, goes back to the efficiencies that Henry Ford brought to the manufacture of automobiles a century ago. It is famously associated with theories put into practice by the Toyota Corporation, particularly under the visionary Taiichi Ohno (1912-1990) in the decades after World War II. In 1990, the very influential book The Machine That Changed the World: The Story of Lean Production—Toyota’s Secret Weapon in the Global Car Wars That Is Now Revolutionizing World Industry, by James P. Womack, Daniel T. Jones, and Daniel Roos, gave the concept more widespread currency. LEAN practices have been incorporated into a very large number of industries during the last few decades, including the clinical laboratory.
Adaptability as an attitude is essential to LEAN practices, starting with the ability to study a process and see it with fresh eyes. The following are the steps a lab manager can take to streamline lab processes, taking advantage of LEAN principles and a strategic approach to workflow assessment.
Eyes wide open: take a walk
In LEAN practice, the first step in improving the efficiency, quality, and productivity of a lab is to take a fresh look at every process. By taking a walk through the laboratory and observing carefully, following a process from start to finish, a lab manager is able to see what works and what doesn’t; for instance, workload requirements and challenges regarding TAT, bottlenecks, nonstandard practices, problems that laboratorians are consistently facing. If the way a process is currently being handled is causing frustration—that presents an opportunity for improvement.
Selecting a team and a process
The next step is to bring together a team to focus on one process or part of a process. The team, selected from staff members who do the specific work under consideration, should ideally also include a vendor. LEAN-certified vendor-consultants can provide a valuable viewpoint in two ways: they can provide simulation studies on their equipment, and they can look at the rest of the process objectively.
Here are guidelines for working with the team:
- Clearly define the scope of the task at hand.
- Choose one process and begin there.
- Include how success will be measured.
Here are examples of a goal whose success can be unambiguously measured:
- Reduce overall turnaround time from 90 to 60 minutes.
- Send results for all emergency department samples within
- 45 minutes.
- Reduce non-value-added steps in the processing area by 50%.
Observing the process: establishing baseline metrics
The team measures and collects data on the process under study, using the information first as a baseline before implementing changes, and then as a way to see the improvement after implementing changes. Metrics can also reveal where further improvement is needed.
Some critical-to-quality metrics, depending on a lab’s goals:
- Reduction in TAT
- Improved of TAT consistency
- Improvements in reliability/reproducibility of results
- Greater patient and operator safety
- Reduction in overtime
- Increase in results/paid hour
- Reduction in non-value-added steps
- Increase in autoverification
- Overall medical value as defined by the people your lab serves.
The standard work document
Perhaps the team’s most challenging task is to create a standard work document for the process being studied. This is a detailed, step-by-step process that all staff will follow in order to reap the benefits of working LEAN. In the laboratory, the desired outcomes typically include improving consistency, reproducibility, quality, efficiency, and patient and employee safety, and the potential to reduce costs and increase return on investment (ROI). To do this, the team observes and maps the process, beginning to end, breaking it down to its basic components, noting the order of the steps, what resources are used, who or what performs the task, and the outcomes.
As the team studies the process and its steps on the way to creating a standard work document, opportunities for improvement will become apparent.
What are value-added steps?
In LEAN terms, value is seen as the steps that are absolutely necessary in order to complete an analysis. For a clinical chemistry lab, for example, value-added steps might include drawing the sample (or receiving the sample), centrifuging, analysis, and release of results. To streamline a lab’s processes and improve efficiency and productivity, the goal is to eliminate as many of the remaining non-value-added steps as possible.
Training and implementation
After standardizing a process, it is necessary to train everyone, including supervisors, to that standard. Consistency in the way a process is performed helps to increase efficiency and eliminate variability. Implementation follows, using the standard work document developed by the team.
Monitoring the process
As the team members implement the new version of the process, they monitor the process against the standard work document. Whenever possible, every shift needs to perform the work the same way, according to the standard the team has established. The team then observes the process again and gathers data to evaluate the progress and potentially uncover further opportunities for improvement.
Analysis and adjustment
Analysis of the data the team collects shows progress compared to the starting point. The outliers, data that stand out by being out of line with the rest of the observed performance, suggest opportunities for further improvement.
Repeating the process
Looking at processes one at a time, a lab manager and staff can analyze and improve each of the processes that matter most to the goals of the lab. These typically are related to cost, quality, service, and productivity. For example, a team can look at reruns, rework, and the reasons for them. By identifying the problem, the team can concentrate on solving it.
Tip: go after “low-hanging fruit” first
What qualifies as low-hanging varies from lab to lab. A process or part of a process that can be implemented quickly or simply to make a notable difference is a good first choice. Another option is to choose the one change that would have a major impact on efficiency.
- Sample movement in the processing area. From time received to analytics, what is the process, and how can the process be improved?
- Visual Cues. Can the staff tell—without asking—what’s happening to a sample? Where are the opportunities for visual or audio control?
- TAT ans STAT samples. Is standard TAT being met and monitored? Are STAT samples easily identifiable throughout a process?
Tip: use auto-verification
For improving processes, auto-verification is an area where efficiency and improvement can be impressive. Improving the current auto-verification percentage (to as high as 95%) can help to eliminate waste that comes from having to verify too many samples manually, improve TAT and management of STATs, and improve the efficiency and productivity of the lab by automating repeats and reruns.
In LEAN practice, improvement is never finished; the process is continual. As a lab manager and staff work on assessments and improvements, rethinking workflow and processes, it’s likely that they will continue to raise the bar on what can be accomplished. Seeing improvement as an ongoing goal rather than a one-time task can encourage a lab to become increasingly innovative about eliminating waste, improving productivity, increasing quality, and providing value for healthcare dollars spent. That focus can lead the lab toward solutions that can contribute to the overarching goals of the institution, including better outcomes for patients.
Automation and optimization: the importance of the health check
By Alistair Gammie, PhD
Automation is one of the biggest investments a laboratory can make. The goals of automation are to make workflow more efficient, improve the turnaround time and predictability of test results, and reduce errors. Many factors must be considered when exploring automation solutions. One important requirement is the need to choose an automation partner that has the expertise and capability to help manage the changing needs of the lab over the course of the automation contract.
The implementation of laboratory automation begins well before any contract is signed, with selection and institution of the project-management methodology that will be used throughout the project. As the engagement proceeds, it is important to manage the installation and implementation process according to the project plan as well as to establish the key performance indicators that will demonstrate that the process has been successful.
Health checks: what and why?
The period following the implementation go-live date is the beginning of a new phase in project management—the health check or optimization phase. There are three main reasons why health checks are necessary: internal forces, external forces—and peace of mind.
Internal forces include change-management issues that prevent necessary process changes, even though the implementation of the automation system proceeds as originally planned. Also, changes to service-level agreements often challenge the planned-for test volume and utilization.
External forces include changes to regulations such as ISO 15189 and to working terms and conditions, both of which can refocus staff activity. Healthcare as a whole is going through a period of consolidation, and workloads may change dramatically due to mergers and acquisitions.
Even without disruptive forces such as these, it is still essential to ensure that this expensive acquisition is delivering the appropriate level of production and return on investment.
Initial health check
It is critical to perform an initial health check on an automation installation within three months of go-live; the initial timing depends on the complexity of the installation. The goal of this first health check is to take the pulse of the system and understand how it is performing as a whole.
During implementation, the focus is on ensuring that the track, individual modules and analyzers, and requested IT workflow are in place and functioning correctly. In contrast, the health check assesses how the entire production system is working, from the time the sample enters the laboratory until the result is generated and the tube is disposed. The health check examines the human-machine interaction and takes a snapshot of the laboratory’s current performance characteristics.
Making adjustments: action plan
The results of the initial health check help to set the performance benchmark for the laboratory moving forward. If performance is below target, an action plan is devised.
The action plan may include a rapid improvement event which may involve dissecting and rebuilding the current process, removing non-value-added steps. The new process is then implemented, measured, and refined as necessary, following the Plan-Do-Check-Act steps of traditional continuous improvement.
The action plan may also include specific training events, technical refinement of the system, or a combination.
If an action plan is required, the health check is repeated within a month of its completion to ensure that the improvements have been realized.
After the initial health check and any required improvements, health check events should be performed annually, although they may need to be conducted more frequently.
In an optimization, it’s recommend that two to three days’ worth of log and middleware files be collected and then analyzed in four distinct categories: production, utilization, turnaround time (TAT) analysis, and errors.
In the production analysis, each module and analyzer should be assessed to see how many tubes and tests are being processed per hour. Analysis criteria may include the distribution of processing within module and analyzer groups, the load balance, and how samples are being processed (e.g., batch size, front loading, etc.).
Utilization looks at the theoretical and effective capacity of each module and analyzer (depends on tube and test density) in order to monitor the effect of annual growth rates, identify capacity for service improvements, and make decisions to increase capacity by adding individual modules. The utilization analysis can identify specific pressure points and help the laboratory make informed decisions for service improvement.
TAT analysis looks at routine and STAT samples, measuring standard deviation, mean, and 95th percentiles, and considers other statistical parameters if necessary. The TAT analysis is conducted holistically but can be driven down to analyzer, analyzer group, and test level. It can also be stratified by time segment. For example, TAT analysis could assess test order time to time the tube is first seen on the track, which allows an understanding of pre-analytical TAT. It could also look at time on track to time out of centrifuge to determine whether the centrifuge operating characteristics are set correctly to manage the workload.
Error analysis assesses the number and type of errors and information messages recognized and recorded by the automation system and attached modules; many of these messages are unimportant when seen in isolation, but very high numbers or patterns seen across days can highlight sample-handling issues that reflect on the human-machine interface. This is particularly helpful when looking across operation of all three shifts.
After data collection and analysis, a one-day, on-site observational analysis allows integration of the collected data with what is actually happening in the laboratory. A review of the analysis and observations may result in a clean bill of health, or a few recommendations, or a full action plan.
This brings us back to peace of mind. A deep understanding of laboratory performance provided by health checks can help the laboratory director to achieve that often-elusive goal.