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Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
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Quality control of automated cell counters.

George S Cembrowski1, Gwen Clarke2

  • 1Laboratory Medicine and Pathology, 4B1.24 Mackenzie Health Sciences Centre, University of Alberta Hospital, 8440-112 Street, Edmonton, AB T6G 2B7, Canada.

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|February 14, 2015
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Summary

Modern hematology analyzers offer improved reproducibility, requiring updated quality control practices. Simpler rules and peer comparisons enhance accuracy, precision, and calibration for these advanced instruments.

Keywords:
Average of patientsBiologic variationCritical valuesDelta checksExternal quality assessmentHematologyQuality control

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Area of Science:

  • Clinical laboratory science
  • Hematology
  • Quality management in healthcare

Background:

  • Hematology analyzers have significantly advanced in reproducibility over recent decades.
  • Traditional quality control practices may no longer be optimal for current instrument performance.

Purpose of the Study:

  • To discuss the evolution of quality practices in hematology analysis.
  • To highlight the need for updated quality control rules and techniques.
  • To emphasize the benefits of peer group data in hematology quality assurance.

Main Methods:

  • Review of current hematology analyzer capabilities and performance metrics.
  • Analysis of existing quality control methodologies.
  • Discussion of advanced statistical approaches for quality control.

Main Results:

  • Improved analyzer reproducibility supports the use of simpler quality control rules.
  • Repeat analysis of critical value specimens is often non-value added.
  • Outdated patient averaging techniques require replacement with more efficient calculations.
  • Comparative peer quality control data enhance analyzer precision, accuracy, validation, and calibration.

Conclusions:

  • Hematology quality practices must evolve to match advancements in analyzer technology.
  • Implementing streamlined quality control rules and leveraging peer comparison data are crucial.
  • These updates lead to more efficient, accurate, and reliable hematology testing.