differently than others. An analytics system’s system also supports labs implementing the CMS/CLIA prescribed Individualized Quality Control Plan (IQCP) based on CLSI EP23 guidelines. Best prac- tices are identified using sigma ratings of instru- ments for each analyte to determine the appro- priate number and fre- quency of QC samples to run. With real-time assess- ment of instrument per- formance, labs can know immediately if an instru- ment problem occurs and if their instruments are not reporting in line with other analyzers. The abil- ity to identify reporting differences between instru- ments over time allows the laboratory to moni- tor the quality of their lab results through the analytic testing phase.

Figure 1-Identifying errors concerning reporting differences between instruments (workstations) of the same methods over time allows the laboratory to monitor the quality of its lab results. A comparison of analyte results for two worksta- tions or a single workstation for two periods as seen on Figure 1 allows laboratory management to quickly answer questions about reporting differences between workstations over time. This is useful for comparing lot changes, new methods, or comparisons every six months as required by accrediting lab agencies.

Access to this type of analytics ensures that QC prac- tices are properly implemented so laboratories can avoid repeat testing, unnecessary follow-up testing, and misdiagnoses. This is also useful for comparing lot changes, new methods, or comparisons every six months as required by accrediting lab compliance agencies.

Demonstrating evidence of compliance Detailed laboratory analytic reporting can also be used as EOC to demonstrate adherence with requirements related to quality management by agencies such as CAP. Not only can the reporting from a laboratory analyt- ics system offer a clear, at-a-glance guide to see what analytic reports support specific checklist requirements, but it can also be used to set benchmarks for specific quality metrics involved in quality management. Some

examples include: t Demonstrating specimen defects by comments such as cancellation reasons, result corrections, and specimen

dispositions t Analyzing specimen abnormal flags (critical values, diluted samples, delta checks) on a daily, weekly, or

monthly basis t Identifying instrument to instrument correlations for

analyzers with the same test and method t Verifying that analyzer reports automated by the LIS applied rules that are compliant

Having access to these in-depth quality reports helps to identify and reduce laboratory errors, manage QA, and ensures that laboratory management teams have adequate documentation and supporting information to demonstrate adherence to accrediting laboratory compliance agencies.


Conclusion With data readily available, laboratory management can view all their test results and not only identify errors but also retrace their root cause, delivering actionable informa- tion to monitor and improve QA processes. Subsequently, this improves the quality of laboratory measurements and enables management to verify that all processes are operating to set standards of performance. Daily manage- ment with a laboratory analytics system and an engaged leadership team are essential components in monitor- ing QA and reducing lab errors. When laboratory data is managed daily, dramatic improvements can be made and errors can be eliminated, resulting in improved specimen quality, utilization, instrument/analyte performance, and patient safety.

Article updated by Vanessa Hawrylak, 2019. Originally authored by Thomas Joseph, Tim Bickley, and Kristina Ziaugra, 2016.

Vanessa Hawrylak, MS, MT(ASCP), Technical Support Specialist, Visiun, Inc.

Thomas Joseph, MBA, MT(ASCP), President and CEO, Visiun, Inc.

Kristina Ziaugra,

Senior Marketing Manager, Visiun, Inc.

Tim Bickley, MT(ASCP), MBA, CPHIMS, Vice President of Sales, Visiun, Inc.

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