Define Quality Assurance
Refers to a set of all actions and activities taken to ensure that the organization delivers products that meet performance requirements while adhering to standards and procedures.
Define Quality Control
Refers to the set of activities or procedures designed to monitor the specific test measurement procedure and results to ensure all quality requirements are being met
Define Control
Controls are substances that contain an established amount of the substance being tested—the analyte. Controls are tested at the same time and in the same way as patient samples.
Controls must be as closely related to human samples, as possible.
Why are control necessary?
Examining controls of known makeup along with patient samples allows for the monitoring (accuracy and precision) of the complete examination process.
Define Assayed Controls
Assayed controls have been analyzed by the manufacturer so that the range of values for the analytes they contain is known.
Define Unassayed Controls
Unassayed controls are unknowns. The laboratory must determine the concentration of each analyte
Define Precision
You are consistent with your results. You obtain similar outcomes time after time
The amount of variation in a series of (repeated) measurements. The less variation, the more precise
Define Accuracy
The closeness of a measurement to its true (known) value.
Define Specificity
A test’s specificity measures the percentage of individuals without the condition being tested for, who will have a negative test. (A test with high specificity will produce fewer false positive results.)
Define True Negative
The individual does not have the disease or illness; results are negative
Define False Positive
The individual does not have the disease or illness; results are positive
How do you calculate specificity?
True Negatives (TN)
Divided by True Negatives (TN) plus False Positives (FP)
Times 100
or
[TN ÷ (TN + FP)] x 100
Define Sensitivity
the ability of a test to correctly identify individuals who indeed do have a particular disease or disorder. (A test with high sensitivity will produce few false-negative and many false-positive results.)
Define True Positive
the individual has the disease or illness; test results are positive
Define False Negative
the individual has the disease or illness; test results are negative
What is the formula for Sensitivity?
True Positives (TP)
Divided by True Positives (TP) plus False Negatives (FN)
Times 100
or
[TP ÷ (TP + FN)] x 100
The result will be in percentage
Sensitivity is the ability of a test to correctly identify individuals who indeed do have a particular disease or disorder. A test with high sensitivity will:
Produce few false-negative and many false-positive results
What is Predicted Value?
Actual disease or illness prevalence (the proportion of a particular population affected by the medical condition over a specified period of time)
How can PPV be used to predict prevalence?
The higher the disease prevalence, the higher the predictive value of a positive test.
What is the formula for PPV?
True Positives (TP)
Divided by True Positives (TP) plus False Positives (FP)
Times 100
or
[TP ÷ (TP + FP)] x 100
What is the Negative Predictive Value
The higher the disease prevalence, the lower the predictive value of a negative test. (Note: This effect may be small when test sensitivity and specificity are high.)
How do you calculate Negative Predictive Value?
True Negatives (TN)
Divided by True Negatives (TN) plus False Negatives (FN)
Times 100
or
[TN ÷ (TN + FN)] x 100
What factors contribute to random error?
Bubbles in reagents or reagent lines
Instrument instability
Temperature variations
Operator variability, such as variation in pipetting (sampling
Does Random Error affect Precision or Accuracy?
Random error affects the precision of a test (reproducibility).
