(blank) - No result. The sample is likely to be ineligible for calculation because it is missing an actual and/or reference value.
(✓) → The individual result is out of agreement range and/or the run is not within agreeable parameters
(✓) → The individual result is out of agreement range however the run/day is still within agreeable parameters
(✓) → The individual result is within agreeable parameters (pass)
95% Agreement
The 95% agreement threshold is widely recommended in MV experiments to ensure that the new method reliably matches the reference method. This level of agreement is chosen because it strikes a balance between clinical significance and statistical reliability.
Specifically, the Bland-Altman method, which is a commonly used approach for assessing agreement, calculates the 95% limits of agreement as the mean difference plus and minus 1.96 times the standard deviation of the differences. This approach ensures that 95% of the differences between the new method and the reference method fall within these limits, providing a high degree of confidence that the two methods produce comparable results in most cases.
Qualitative Experiments
Qualitative Test Experiments, including Method Comparison (MC), Precision (Prec), Limit of Detection (LoD), and Trueness experiments, are essential for confirming the validation information provided in the manufacturer insert.
These experiments verify that the manufacturer's claims about the method's performance—such as accuracy, precision, detection limits, and trueness—are accurate and applicable in the specific laboratory's environment.
Name | Definition |
|---|---|
Agreements | The total number of measurements between actual and reference value in agreement. |
Eligible (Sample and Results) | Samples that provide the necessary information for statistical calculations to be performed. Usually this is possessing both an actual and expected result. |
Label | The general identification used to identify a specific Sample. |
Replicate | Multiple tests on the same sample to assess precision and repeatability, conducted within a run or across multiple runs. |
Run | A sequence of measurements on a set of samples under the same conditions, performed within a defined time period. |
Sample Source | The original source of the Sample such as Sample, EQA, or the name of the Manufacturer. |
Sample Type | Can describe the specific Sample Type, source and/or medium that is used to collect and/or store the sample. |
Sample(s) | Individual specimens collected for testing representing the source. In MV experiments with Runs, this can refer to to the number of concentration levels used. |
Test Details | Information about a test relevant to the description, background and performance metrics. |
Quantitative Experiments
Quantitative Test Experiments confirm the performance characteristics claimed by manufacturers by evaluating precision, accuracy, sensitivity, and linearity. These experiments ensure that the method performs reliably under specific laboratory conditions, maintaining the integrity of test results.
Linearity and Reference Interval experiments assess the method’s accuracy across various concentrations and population groups. Trueness, Carryover, and Interference experiments further validate the method’s reliability in practical clinical scenarios.
By replicating these experiments, laboratories ensure that the method performs as described in the manufacturer insert, providing consistency and reliability. This process ensures regulatory compliance and builds confidence in the method’s suitability for clinical use.
Quantitative MV experiments verify that methods yield accurate and reproducible results, enhancing the quality and effectiveness of laboratory testing. This validation is essential for maintaining high standards of diagnostic accuracy and patient care.
Name | Definition |
|---|---|
Precision (Prec) Experiment | An experiment that evaluates Random Error through replicate measurements across concentration levels. |
Limit of Blank (LoB) Experiment | An is the highest concentration of analyte detected for a blank sample. This can be determined through the LoB MV Experiment. : Mean of the results : Standar Deviation of results |
Limit of Quantitation (LoQ) Experiment | An MV Experiment used to determine the lowest amount of analyte that can be reliably determined. |
Method Comparison (MC) Experiment | An MV experiment used to estimate the systematic difference on the basis of the differences observed between the methods.
See: |
Linearity (Lin) Experiment | Linearity is an MV experiment to establish the correlation between Reference and Actual Results |
Reference Interval (RI) Experiment | An experiment used to determine the normal ranges for a test within populations measured by the laboratory |
Trueness (TN) Experiment | Trueness is an MV Experiment that evaluates the performance of a test by comparing sample test results with true values. Usually an EQA. |
Carryover Experiment | An MV experiment used to evaluate the effect of high concentration testing on subsequent low concentration samples. |
Interference Experiment | An MV experiment used to evaluate the effect of interfering substances on sample concentration measurements. |
Getting an Overview of the Status
Getting an Overview of the Status of each experiment offers a quick glance method of seeing the whole state of the MV instead of clicking through individual files and PDFs. To access this view navigate to the Experimental Design section and then Experiments.
The toolbar above the sections allows to:
- View all experiment with a specific experiment state
- View all experiments by result type
- Expand/collapse all experiment blocks
- Search by keywords
Experiment States
Experiment States indicate the current condition of the experiment to give clean identifiers to their status. These identifiers may also be found on individual samples with replicates and runs.
Experiment State Descriptions
Status | Description |
Not Started | No measurements have been entered into the experiment. |
Incomplete | Measurement has been entered, however an insufficient amount to fulfill the criterias of the experiment. |
Failed | Sufficient measurements have been entered, however the results do not pass the requirements set by the acceptance criterias. |
Passed | Sufficient measurements have been entered and passed the requirements set by the acceptance criterias. |
Summaries
The Experiment Summary field is a highly flexible editor for generating summaries. This fulfills the requirements set by many accreditation organizations.
The Summary field is a powerful editor used to automatically generate and update summaries. From the editor you may add headings, text formatting, checkboxes, number lists, tables and smart content.
Smart Content Variables are powerful tools to automatically update your summaries while giving enough flexibility for customizing the MV. Text highlighted in Purple a variables that automatically update based on your MV.
Smart content can be accessed through the either pressing / or the Smart Content button. The / menu offers a smaller selection of variables that are more specific to the current focus. The larger Smart Content menu offers more options and templates. Templates are pre-defined templates that can offer full sets of Smart Content to generate your summaries quickly.
Smart Content selection can be changed by clicking on them to remove or replace them with another.
