Achieve laboratory breakthroughs with IT www.siemens.com/diagnostics CentraBytes Integrating Patient Moving Averages into the QC Process Nils B. Person, PhD, FACB and Elizabeth Kozak, MBA Siemens Healthcare Diagnostics, Inc. While the pivotal role of quality control (QC) in the delivery of high-quality patient results is well recognized, the opportunity to fine-tune the QC process in order to reduce turnaround time (TAT) and improve efficiency is sometimes overlooked. This tutorial reviews the use of patient moving averages (PMA) as a component of the QC program and how it can be applied in day-to-day operations to detect problems and proactively address issues. What are patient moving averages (PMA)? PMA are running averages of patient results for a specific assay over a preset number of data points (batch size), and historically have been commonly used in the hematology laboratory. With the computing power made available by data management systems, PMA are increasingly used in chemistry and immunodiagnostics as an adjunct to the QC process. Answers for life. 2 CentraBytes Based on actual patient results, PMA complement scheduled analysis of control materials used in conjunction with Levey-Jennings charts and QC rules. With PMA, monitoring is continuous, and thus shifts and changes may be detected before errors are detected using QC results. PMA can detect systematic changes such as differences in assay performance between analyzers, changes attributable to specific reagent lots, or issues with specimen containers. Additionally, there is no incremental cost associated with reagents or the cost or time to perform additional tests. Audit vs. defined PMA There are two types of PMA. Audit or undefined PMA is passive, continuous monitoring. PMA are calculated and presented, but no rules or limits are defined and no alerts are triggered. It is the essential first step in using PMA in order to develop understanding of how PMA trend. It is also useful in troubleshooting. For example, when a QC flag is triggered, time-stamped, instrument-specific PMA audit data can be retrieved to possibly see when the problem began and which samples may be affected. Additionally, for some assays, there may be shifts in QC results when a new reagent lot is used. These shifts are often related to the altered sample matrix of the QC material and do not indicate a reagent problem. However, the way to verify this is to look at patient results. If PMA Figure 1. Chloride audit in use, courtesy of University of Michigan Hospital. show no shift in patient results, then the shift in QC may be a matrix issue, the reagent lot is performing acceptably, and QC targets need to be updated. If PMA show a comparable shift in both patient and QC results, there may be a reagent problem and the manufacturer should be contacted. In defined PMA, QC alerts are triggered and results held based on preset limits. Many laboratories use a combination of audit and defined PMA, depending on the assay. Chloride audit in use. In the Figure 1 example, PMA over a period of five hours show that chloride results for all four instruments are within range of each other. The QC runs, likewise, are within one standard deviation. 3 CentraBytes Calcium varying between shifts. In the Figure 2 example, the laboratory used PMA to help troubleshoot drifts in calcium due to pH changes caused by a new water system. Which tests should be monitored? Not all assays benefit from PMA monitoring. Table 1 summarizes attributes to consider when deciding when to use PMA. Determining batch size and setting targets The batch size or number of patient results used to compute the average should be large enough so that it is representative of the patient population, in order to avoid overreaction and wasting time in unnecessary follow-up. Conversely, an overly large batch may take too long to accumulate and result in delayed detection of issues that arise during the longer intervals. The batch size differs by method, and determining the optimal batch size will require a process of trial and error. There is guidance in the literature on how to determine appropriate batch size for many assays.1 The same rationale holds true for defining the acceptable range. Table 1. Assays vs. suitability for monitoring Attribute Rationale Stable assays: day-to-day Inherent instability can make it difficult to for a single patient, over time isolate problems for a patient population Reasonable analytical range Inherent broad range (e.g., CA 125, CK, or ALT) may challenge data collection Significant volume Sufficient data can be gathered in a reasonable amount of time to detect shifts and trends Target value and deviation can be established for a patient population Once target value (typically the average of the PMA values obtained from weeks or months of auditing can be used) and acceptable deviation are set, the system can be configured to flag “out of control” batches Figure 2. Calcium varying between shifts, courtesy of University of Michigan Hospital. 4 CentraBytes Integrating PMA into your QC process The data management system plays an important role in integrating PMA seamlessly into day-to-day laboratory operations. For example, based on a defined acceptable range, the CentraLink Data Management System can be configured to notify the user when a possible shift in performance has occurred. The notification, including quality severity (QS), is displayed on the Patient Review screen. The QC screen can readily be assessed from the navigation screen to provide additional information for troubleshooting. Probable causes may be a change in patient population, a calibration issue, an instrument issue, or a reagent issue. Once on the QC screen, the user has the ability to view the assay across all instruments on the network (local or remote) to further troubleshoot the problem or determine where the assay can be diverted to minimize impact on TAT and avoid running assays on the instrument with the issue, saving reagents. When integrated with a Siemens Aptio™ Automation System, the CentraLink system reroutes automatically. The CentraLink system also provides a means to hold for review a set of assays based on one of the assays in the set failing QC. Examples are in hematology (e.g., if RBC fails, all CBC tests could be configured to be held for review) and for calculated results derived from multiple tests. It should also be noted that the CentraLink system uses a moving average method based on a variation of Bull’s algorithm. The batch size, N, is defined for each assay configured on a specific instrument. The PMA is an exponentially weighted average of the previous N-1 patient results. The previous average contributes Nils B. Person, PhD, FACB, Senior Clinical Consultant, Siemens Healthcare Diagnostics, is a board-certified clinical chemist with over 30 years’ experience in laboratory medicine. He spent 15 years directing hospital laboratories prior to joining Siemens and has spent the last 18 years supporting Siemens technical staff and customers. In his current role, Dr. Person provides support for clinical issues that cross diagnostic product lines. His particular areas of expertise are quality control, method evaluation and verification, and laboratory regulatory compliance. Dr. Person has also been part of a number of Clinical and Laboratory Standards Institute (CLSI) Standards development teams and was involved in the development of EP23 Laboratory Quality Control Based on Risk Management and EP26 User Evaluation of Between Reagent Lot Variation. He is currently involved in the revisions of EP21 Total Analytical Error and C24 Statistical Quality Control for Quantitative Measurement Procedures. to the calculation of the current batch average. As in Bull’s algorithm, all patient samples are included, not just the normal ones. Summary Patient moving averages (PMA) can be a valuable adjunct to the QC process, allowing tighter control of assay performance, faster and better responses to issues, and cost savings on QC material and tech time. A clear vision of goals and methodical planning will help guide proper use of PMA to focus on issues that need to be addressed and avoid data overload. References: 1.Westgard JO, Smith FA, Mountain PJ, Boss S. Clin Chem 1996; 42:1683-1688. Elizabeth Kozak, Global Portfolio and Product Manager, CentraLink Data Management System, Siemens Healthcare Diagnostics, has an MBA and a BS in computer science and over 25 years’ experience working in the IVD industry. She spent the first 10 years of her career in software development and project management. In her current role as Siemens CentraLink system global product manager, Elizabeth works with Siemens customers around the world to understand their informatics needs and collaborates with Siemens teams to provide the right product to the customer. She contributes to defining Siemens IT strategies and roadmaps and leads a cross-functional team that monitors and supports CentraLink system products. Elizabeth believes that in today’s competitive and consolidating clinical laboratory marketplace, labs must operate with Lean workflows and processes in order to survive. Informatics is customers’ biggest lever to streamline workflows, improve processes, meet turnaround time requirements, and facilitate growth with minimal investment. According to Elizabeth, today’s clinical laboratories are rich in data, but products like the CentraLink system enable customers to focus only on the information that needs immediate action and to proactively address potential issues. Siemens Healthcare Diagnostics, a global leader in clinical diagnostics, provides healthcare professionals in hospital, reference, and physician office laboratories and point-of-care settings with the vital information required to accurately diagnose, treat, and monitor patients. Our innovative portfolio of performance-driven solutions and personalized customer care combine to streamline workflow, enhance operational efficiency, and support improved patient outcomes. Aptio, CentraLink, and all associated marks are trademarks of Siemens Healthcare Diagnostics Inc. All other trademarks and brands are the property of their respective owners. Product availability may vary from country to country and is subject to varying regulatory requirements. Please contact your local representative for availability. Order No. A91DX-CAI-140962-GC1-4A00 08-2014 | All rights reserved © 2014 Siemens Healthcare Diagnostics Inc. 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