QC History Summaries for Accuracy Assessment

QC History Review

Gathering a history of the outcome of quality control (QC) accuracy assessments provides a useful method of monitoring the effectiveness of the QC configuration. Accessing, reviewing and analysing this QC history ultimately highlights any CCLAS or instrument settings that could be updated to ensure a laboratory is testing accurately and with precision according to the standards set for that laboratory.

The examination of the results in the QC history indicates compliance or non-compliance with the QC specifications and standards allowing corrections to be deployed as they are identified. This is facilitated by the ability to produce charts and reports on the historical quality control data recorded from quality control samples assessed in the system.

Quality control can be configured to apply organisation wide, or to individual laboratories.

Where the scheme version analyte is configured to have the outcome of QC assessments written to the QC history table, then a record is written for the accuracy assessment, in which, the record's Analytical Type is set to Blank, Standard or Spike and the record's QC Type Code is set to the Primary QC Type Code or the Secondary QC Type Code, as appropriate.

Performing Quality Control History Reviews of Accuracy Assessments

If the scheme version analyte is configured to have the outcome of accuracy assessments written to the QC history table, then the table is updated for each accuracy assessment performed on a related sample scheme analyte. The QC history record's Analytical Type is set to Blank, Standard or Spike and the record's QC Type Code is set to the Primary QC Type Code or the Secondary QC Type Code, as appropriate.

After one or more outcomes of accuracy assessments are written to the QC history table, the results can be searched using the CCQCHS—QC History Summary application, which also can be accessed using the QA & Mgmt — QC Review menu option. The results returned can also be saved using the Saved Searches — Add to Saved Searches function in this application, including filtering and column sorting of results. QC history details for a blank, standard or spike QC sample can also be accessed from the CCWKOP—Open Workbook application.

QC history summaries are first searched by QC Type or Analytical Type, after which, discrete observations can be viewed for a selected QC type. Individual observations can be made active or inactive for inclusion in statistical analysis and on statistical charts. The results of the QC assessment are displayed with the number of observations per analyte displayed in the Count (# Observations) column.

A selected QC type can be opened to view the discrete observations (readings and their accuracy assessment), displayed in the Discrete Observations tab of the CCQCHS—Update QC History Summary screen. Readings can be further filtered from here.

Selected observations can have their activity status updated, can have their QC failure status ignored, or be deleted. These options are available in the CCQCHS—Update QC History Summary grid after selecting line items.

A selected discrete observation can be opened to view the reading, and the code of the user who conducted the analysis, the instrument used during analysis, sample details, and production job, or laboratory batch job and production job, details, including client and project.

Charting and Reporting Results of Accuracy Assessments

QC history summaries can also be exported to a report in CCLAS, as can QC history discrete observations, to provide trending and statistics data for QC analysis.

The following can be specified for most chart types that can be generated from the CCQCHS—QC History Summary application:

  • Target value for the QC assessment
  • Tolerance of results
  • Mean (or average) findings in the results or specified readings
  • The standard deviation across the results
  • The group size selected within the results returned, which determines the number of observations within each group.

Upper and lower warning or failure limits can also be selected for charting in certain charts, including histograms, scatter charts and P-Curve charts.