Diagnostic laboratory analyzer is essential for producing accurate test results, meeting turnaround times, and completing daily tasks. Whether it's a hematology analyzer, biochemistry system or an automated testing instrument, each item of analyzer contributes to the overall efficiency of the laboratory. However, having state-of-the-art analyzer does not mean that the analyzer will be used efficiently. Laboratories need to evaluate the extent to which their analyzer is being utilized.
Analyzer utilization allows laboratory managers to determine which instruments are being utilized less than they could be, find where there may be a capacity issue, monitor and manage operating expenses, and provide data-based insight into how to properly schedule maintenance, as well as when to invest in additional analyzer. In addition, for owners of pathology laboratories, operators of diagnostic centers, laboratory managers at hospitals, and multi-location laboratory organizations; monitoring the utilization of their analyzer will help increase operational effectiveness.
Laboratories with accurate operational data and suitable Pathology Laboratory Software will have a better understanding of their testing activities, will be able to monitor their workload, and will be able to plan for their resource requirements based on actual demand.
What Is Analyzer Utilization in a Diagnostic Laboratory?
Analyzer utilization refers to the effectiveness of a laboratory's use of its existing instrumentation, in terms of both the amount of time that those instruments are actively used to perform productive work and/or the total capacity of those instruments.
A lab could set up an automated blood analyzer for 8 hours per day, however only operate it for 5 hours of productive work. Therefore, based upon time utilized, there would be a utilization rate of 62.5% of the total number of hours (8) the analyzer is scheduled to run.
On the other hand, the rest of the day can consist of instrument calibration, quality assurance testing, instrument maintenance, warming up of the instrument, and/or times when there are no samples to test. Therefore, you need to consider all these factors before deciding whether the instrument is being used at its full potential.
A laboratory may find itself with a low usage rate on its analyzer, but this does not necessarily suggest that the laboratory does not need the analyzer. Conversely, a high usage rate does not automatically imply that the laboratory is operating efficiently. To determine the most cost-effective approach for analyzer selection, laboratory managers should evaluate several factors including workload, analytical quality, turnaround time, reliability, and back-up capacity.
Why Is Analyzer Utilization Important?
1. Identify Underused Analyzer
Laboratories often buy analyzer in anticipation of increased business or the introduction of new testing procedures. However, when actual business is less than expected, laboratory analyzer may be left unused.
Managers use data about the use of analyzer to find out why there is little use of analyzer. Some reasons for little use include; a need for more use of analyzer (demand), a need for even distribution of work amongst employees (workload distribution), a need for extended operating hours (operating hours) or the incorrect selection of analyzer (analyzer setup). By utilizing this type of data managers will be able to make better decisions regarding allocating resources and make plans for the future.
2. Improve Laboratory Productivity
If there is a high volume of testing being processed by one analyzer, and a second, compatible, analyzer is available for use but currently not in use, the laboratory may be able to move some of its test load from the first analyzer to the second.
Managers can use analyzer reviews to find out where there are problems with how long it takes to complete jobs (bottlenecks), make sure that workers are being scheduled correctly, and prevent workers from having to wait too much. Managers can also get more work done by allocating work more evenly across employees, rather than buying more analyzer right away.
3. Control Operating Costs
Costly items associated with laboratory operations include reagent purchases, consumption of supplies, service of machines, utility costs, calibration standards, and long-term contracts for machine repair. Over-sizing or under-sizing of analyzer capacities may lead to higher costs per unit of reported result.
Laboratories need to know if they are using their resources wisely when comparing laboratory expenditures with operating expenditures. To make accurate cost comparisons, you must consider how each laboratory performs tests, how many times each test is repeated, what each laboratory requires to maintain its analyzer, and the cost of buying and maintaining all analyzer.
4. Improve Maintenance Planning
Unexpected analyzer malfunctions will result in delays of testing, reporting, etc. Laboratory management should keep track of operating hours, downtime, number of errors/problems, and previous repairs/services for all analyzer so that they can schedule routine preventative maintenance and have available back up analyzer when needed.
The use of the analyzer is as important as the reliability of the analyzer. A piece of analyzer could be used a lot and have many problems, such as being down often, or needing to be tested over and over again, which will cause it to have less useful output.
5. Make Informed Investment Decisions
Laboratory managers need to review current usage, peak demand times, analyzer down-time and how efficient the work process is before they buy a second analysis machine. Laboratory managers may also want to look at improving their scheduling or distributing compatible tests to help ease the strain on capacity. Or, laboratory managers may find that they require an additional piece of analyzer in order to continue to meet quality standards and turn around time expectations.
Key Metrics for Measuring Analyzer Utilization
By using more than one metric, you will have a more comprehensive view of what is happening in your program than if you relied on just one percent.
1. Time-Based Utilization Rate
This measure quantifies the percentage of the total operating time that was used for performing tests.
Formula:
Utilization rate of analyzer (%) = (productive operating hours/total available operating hours) * 100.
An example of this would be if an analyzer is open for eight hours and used productively for testing during that time for five hours then its utilization is 62.5%.
Laboratories must use a standard way of defining their available time. Available time includes (or excludes) calibration, quality control, preventative maintenance and standby periods in accordance with a written procedure. Standardizing how you define available time will provide a better comparison of your laboratory's performance.
2. Test Volume Utilization
Test utilization refers to the comparison of what is tested compared to the instrument's potential testing capabilities.
Formula:
Test Volume Utilization (%) = (Actual Tests Processed / Practical Test Capacity) x 100
Utilization can be calculated by dividing the number of tests processed per day (280) by the maximum number of tests that can be processed per day (400), which results in a utilization rate of 70%.
The practical capacity should take into account all of the practical operational considerations such as: the practical test mix; practical loading times; practical calibration; practical quality control; practical repeat tests; and any other practical operational limitations. It is possible that the maximum throughput that the manufacturer states can be achieved per day does not accurately reflect the actual patient test capacity that can be produced in a single day.
3. Analyzer Downtime
Downtime is the time that a machine or system cannot operate properly due to mechanical problems, regular service/maintenance, or some type of malfunction.
Formula:
Downtime Rate (%) = (Unplanned Downtime ÷ Scheduled Operating Time) × 100
If a piece of analyzer operates for 40 hours each week and has 4 hours of unanticipated downtime, then the percentage of time that the analyzer was out-of-service would be 10%.
Monitoring for when systems fail allows for the identification of recurring issues with a system, the evaluation of the effectiveness of the support agreement in place, and the determination if there is adequate redundancy available.
4. Throughput Rate
The number of tests processed by an instrument in a certain amount of time is measured by throughput.
Formula:
Throughput Rate = Number of Tests Processed ÷ Operating Time
Laboratories can use their systems to track how many tests they run on a regular basis (per hour, per shift, or per day). In order to compare laboratories, however, you must take into consideration the different levels of complexity associated with each test being run; the configurations used for each type of laboratory analyzer; and the number of times a laboratory may have to repeat a test.
5. Cost per Reportable Test
This measurement calculates the estimated operating costs related to generating a valid test outcome.
Formula:
Cost per Reportable Test = Relevant Testing Costs ÷ Number of Reportable Tests
Cost categories used for analysis can be broken down into reagents, consumable supplies, maintenance, utility expenses, labor cost, and depreciation of analyzer. When analyzing multiple time frames or instruments, use the same cost categories to ensure consistency.
6. Peak-Hour Utilization
A daily average can mask an organization's ability to handle demand. For example, an organization could appear to have excess capacity when averaged over an entire work day, however, during peak times (such as early morning) there may be significant wait times due to high volume.
Peak period assessment assists management in understanding when demand is greater than the available capacity. This information will support more efficient scheduling of personnel, distribution of tasks among employees, and potential purchases of new analyzer.
How to Measure Analyzer Utilization Step by Step
Step 1: Prepare an Analyzer Inventory
Provide a list of each laboratory instrument including: analyzer type, location of the instrument, installation date, what tests can be run using the instrument, when the instrument is operational (operating hours/days), how often the instrument is maintained, and whether or not there are backups available for the instrument.
For multi-site networks, use consistent analyzer identification at all sites. This allows for easier comparisons of similar analyzer, as well as reviewing workload variations.
Step 2: Define Available Operating Time
Determine the number of hours each device will run per day, week, or month. Record how the calculations handle calibration, quality assurance/quality control (QA/QC), warm-up time, routine maintenance, and standby times.
A consistent definition is necessary for reliable comparisons.
Step 3: Collect Usage Data
Where possible, gather data from the analyzer log files, maintenance records, shift logs/registers, instrumentation interfaces and/or laboratory information systems. If available, document the productive testing times (test volume), downtimes (error events), and inactive/non-productive times.
The smaller laboratory can use manual record keeping. Automation of data collection by larger laboratories can reduce the time spent on recording data, while at the same time increasing the accuracy of data.
Step 4: Calculate the Metrics
Calculate the utilization based on time, the utilization of tests performed, how much time the analyzer was down, how many tests were completed in a given period of time, and the price of each test reported. Choose which metrics to use for your analyzer depending upon its purpose and what the organization is trying to achieve.
Solely based upon utilization rate, avoid comparing instruments that vary in terms of capabilities, capacity, and clinical use.
Step 5: Analyze Workload Patterns
Analyze your performance by hour, shift, day, and month. Pinpoint the times when you have high demands on your resources (peak demand), the times when you experience long lines of customers waiting for service (recurring queues), how your workload varies over the seasons (seasonal variations), the number of times that you find yourself interrupted during work hours (frequent interruptions), and which instruments are consistently underutilized.
The multi-branch laboratory should compare like analyzer with respect to variations in testing demands, laboratory staff size, operational times, and service requirements.
Step 6: Identify the Causes
Utilization levels could be low due to lack of testing requests, poor scheduling practices, insufficient number of employees working at the facility, improper distribution of work among employees, and/or analyzer that does not align with the current operational requirements.
High utilization is likely indicative of high productivity, however; it can also demonstrate a strain on capacity, as well as an inadequate backup system. Before you decide what to do about the issue, determine why the issue exists.
Step 7: Implement Improvements
Possible actions would be to move test kits to other sites that are compatible with the testing being done, adjust the schedule of employees' work hours, improve preventative maintenance on analyzer used for testing, verify that there is enough reagent available to perform the tests required, and train employees who will be performing the tests.
All changes made should adhere to validated procedures, manufacturers' guidelines, laboratory quality requirements, and all relevant regulatory requirements. You will then need to assess whether the changes are improving your overall efficiency while still maintaining high standards of quality for your testing.
How Pathology Lab Software Supports Analyzer Utilization
The modern pathology lab software brings together data about operations such as patient registration, sample tracking, testing, reporting and billing. It may be linked to other lab software, like a laboratory information system (LIS) or compatible testing devices, which will provide greater visibility into the testing activities and any problems with the work flow.
Labs can use software depending on the features that are available and what integrations can be made.
Review test volumes across shifts and branches.
Monitor sample movement and pending workloads.
Identify processing and reporting delays.
Compare workload trends over time.
Improve coordination between staff and analyzer operators.
Generate reports that support resource planning.
Laboratories need to determine if they can obtain the necessary information (actual instrument run time and/or downtime) through their analyzer(s), middleware system(s), maintenance software system(s) and/or other laboratory-connected information systems. Some pathology software platforms do not automatically record actual instrument run times and/or downtimes.
Lab management software can relate to both inventory management and business processes. An example of relating inventory management to analyzer would be analyzing the number of tests performed versus the amount of reagents used to determine whether there is waste or unexpected expenses. Similarly, the process of moving from sample receipt through to testing, validation and reporting can be reviewed in conjunction with instrument workload to find areas where delays are occurring.
Reliability of analysis is dependent upon accuracy of data, compatibility of integration, consistency in definitions, and frequency of reviews.
Common Mistakes to Avoid
Test Volume is Only Measured: The number of tests being run cannot account for why there are periods when the laboratory is not working, how difficult a particular test may be, how often a test will have to be repeated, and the financial cost associated with running the laboratory.
The advertised peak capacity of a machine may not reflect what it is capable of producing under normal working conditions.
Higher usage should never be achieved by compromising on quality control, validating results, protecting patients from harm, or meeting your reporting requirements.
Comparing various types of laboratory analyzer without the frame of reference provided by the type of testing (specialized analyzer vs. routine high-volume testing) will result in inaccurate performance comparisons. Therefore, it is important to select the most relevant benchmark for comparison.
When collecting data that has no action taken on it: Assign responsibility to review metrics, find out why certain metrics are off, document how those metrics have improved, and check if the improvements were effective.
Best Practices for Multi-Branch Laboratory Networks
Multi-branch diagnostic networks will require standardized analyzer identifiers, metric definitions, reporting period types and data quality standards at all branches.
Branch-level reports can show where there are differences in workload, but it is not necessary for each branch to use the same percentage of its capacity. A hospital lab, central reference lab and smaller diagnostic center will likely need to perform a variety of tests.
Capacity Planning must also account for Sample Transportation, Staffing, Maintenance Coverage, Back-Up Arrangements and Turnaround-Time Commitments. All decisions regarding the transferring of work-load or analyzer between branch locations must adhere to relevant operational and quality control measures.
Conclusion
Measuring laboratory analyzer use is a way to determine how well the lab's analyzer supports testing, quality of services, and financial results. Diagnostic laboratories use several measurements to assess the efficiency of their analyzer, including productive operating time, test volume, down-time, throughput, peak-hour demand, and costs per reported test. These measurements enable laboratory managers to find areas of inefficiency in their operation and to take action to improve them through analyzer maintenance, improved scheduling, and purchasing additional analyzer as needed.
The purpose is not to maintain the continuous functioning of all analyzers; however, to achieve a balance between productive capabilities and reliable functioning, quality standards, and patient requirements.
By utilizing appropriate pathology lab software or lab management software, laboratories will have better visibility into their work load, be able to identify where there are issues with the flow of work (bottlenecks), and confidently allocate resources.
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