Quality Assurance in Clinical Chemistry

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Questions and Answers

Which of the following represents a common issue in the pre-analytical stage of quality assurance?

Improper sample collection technique (correct)

Software errors during analysis

Calibration failures of the testing equipment

Misinterpretation of test results

In a Levey-Jennings chart, what does a shift in data points indicate?

A sudden change in the assay system performance (correct)

Consistent test results with no issues

Increased variability without systematic errors

Normal random variation within expected limits

According to Westgard Multirules, a violation of which rule indicates that a system error has occurred?

10x rule (correct)

12s rule

R-4s rule

1-2s rule

What is the purpose of running at least two levels of quality control for each test in a laboratory?

To detect analytical errors that may impact patient results Signup and view all the answers

Which percentage represents the area outside of ±2 standard deviations in a normal distribution?

5% Signup and view all the answers

What type of error is detected during the analytical stage of quality assurance?

Instrument calibration errors Signup and view all the answers

In statistical terms, what percentage of results is expected to fall within ±1 standard deviation from the mean in a normal distribution?

68.2% Signup and view all the answers

What is a key characteristic of quality control materials used in laboratory settings?

Same chemical and physical properties as the measured samples Signup and view all the answers

What characterizes a trend in quality control?

Results steadily increasing or decreasing over 6 or more days Signup and view all the answers

Which of the following is NOT an example of a shift in quality control?

Consistent decrease in control results for several days Signup and view all the answers

What is one of the common problems associated with quality control (QC) when analyzing serum samples?

Improper dilution of lyophilized QC materials Signup and view all the answers

Which of the following best describes a trend in quality control?

A consistent diversion of control points in one direction Signup and view all the answers

What is the primary use of Levey-Jennings charts in the clinical laboratory?

To visualize shifts and trends in daily QC results Signup and view all the answers

How does the Westgard rule help in the analysis of QC data?

By allowing laboratories to take corrective actions based on standard deviations Signup and view all the answers

Which Westgard rule indicates a random error if violated?

12s Rule Signup and view all the answers

What is indicated if a Levey-Jennings chart shows a point outside the mean ±2SD limits?

An error has occurred in the testing process Signup and view all the answers

What action should be taken if the 13s Rule is violated?

Reject the result and investigate potential systematic error Signup and view all the answers

In a Levey-Jennings chart, what does ±2SD represent?

The acceptable range of variation for QC results Signup and view all the answers

What constitutes a shift in quality control data?

A sustained movement of control points in one direction for multiple consecutively tested samples Signup and view all the answers

Which of the following factors could contribute to a trend in quality control?

Gradual deterioration of standards or reagents Signup and view all the answers

Which calculation method is used to determine the dispersion of QC data?

Standard deviation calculation Signup and view all the answers

If a semi-automatic pipette has lost calibration, what type of QC problem does this most likely represent?

Systematic error Signup and view all the answers

Why are the mean and standard deviation analyzed over 20 days for a new lot of QC material?

To establish control limits representative of the material's variance Signup and view all the answers

What is the result of calculating 3SD for a QC material with a mean of 140 mmol/L and a standard deviation of 3 mmol/L?

131 to 149 mmol/L Signup and view all the answers

Study Notes

Quality Assurance - Clinical Chemistry

Quality assurance (QA) is the process of monitoring any activity linked to a lab result.
QA includes errors that can occur at three stages:
- Pre-analytical: errors before the sample reaches the lab or is analyzed. Examples include collecting a HbA1c sample in a SST tube.
- Analytical: errors during the analysis of a sample. For instance, analyzer malfunction during testing.
- Post-analytical: errors after the analysis of a sample.

Descriptive Statistics - Basic Terms

Qualitative data: Subjective observations that can't be quantified. Examples include turbidity, color, and odor.
Quantitative data: Measurable characteristics. Examples include glucose (mmol/L) and creatinine (µmol/L).
Data: A collection of related observations used to draw conclusions about a population. For instance, reference intervals for healthy people.

Accuracy and Precision

Accuracy: Closeness of a result to the true value.
Precision: Reproducibility of a result.
In labs, accurate and precise results are desired.

Key Terminology

Population: All possible observations.
Sample: Part of a population.
Random sample: Sampling where no part of the population has preference.
Parameter: Calculation using population information.

Calculated Statistical Values

Statistics: Values calculated from random samplings of a population.
Classified into two groups:
- Measures of Central Tendency: Distribution of values around a central value (mean, median, mode).
- Measures of Dispersion: How spread out the values are (range, variance, standard deviation).

Measures of Central Tendency - Mean

The mathematical average of a set of values.
Parametric mean (μ): Data based on all of a population.
Statistical mean (x̄): Data based on a sample of a population.

Mean - Example

Provided example data set to calculate the mean.

Measures of Central Tendency - Median

Median is the middle number when values are arranged in sequential order.
If the number of values is even, the average of the two middle numbers is the median.
If the number of values is odd, the middle number is the median.

Median - Example

Provided example data set to calculate the median.

Measures of Central Tendency - Mode

Mode is the most frequently occurring number in a group of numbers.

Mode - Example

Provided example data set to calculate the mode.

Measures of Dispersion - Range

Range is the difference between the highest and lowest value.

Range - Example

Example data set provided to calculate the range.

Measures of Dispersion - Variance

Variance (s²) measures the precision of a group of numbers.
High variance indicates wide ranges of values.
Low variance indicates closely grouped values.
The smaller the variance, the more precise the numbers.

Variance - Formula

Formula for calculating variance is provided.

Variance - Example

Example data set provided to demonstrate variance calculation steps.

Measures of Dispersion - Standard Deviation

Standard Deviation (SD) is the most frequent measure of precision.
Symbol is s(or SD).
Standard deviation is the square root of the variance.
Formula for calculating standard deviation is included.

Standard Deviation - Example

Provided example problem which resulted in the standard deviation result.

Coefficient of Variation

Used to compare precision of two or more data groups.
Expressed as a percentage.
Lower the CV, the greater the precision of a data set.

Coefficient of Variation - Example

Example provided to show calculation method.

Probabilities Associated with Standard Deviation

Statistically, analyzed 30 times, results will fall within a certain percentage range for 1 SD, 2 SD, 3 SD from the mean.
68.2% of the time results fall within ±1 SD.
95.5% of the time results fall within ±2 SD.
99.7% of the time results fall within ±3 SD.

Normal Distribution Curve- Examples

Depiction of the bell curve including percentages and regions identified for 1, 2 and 3 SD.

Quality Control Analysis

Acceptable quality control results fall within expected limits.
If the result is outside accepted limits, no further patient results will be reported until the problem is corrected/resolved.

Types of Errors - Random and Systematic Errors

Random Errors: Errors due to chance, extreme variations on consecutive days in lab results. Instrument, operator, reagent/environmental issues.
Systematic Errors: Errors affecting all samples in the same direction. Reagent issues, calibration problems, etc.

Common QC Problems - Shifts

QC results consistently distributed on one side of the mean for 6 or more days.
Cause must be identified, samples re-analyzed for correction of problem.
Examples: incorrectly prepared reagents, wrong timing/temperature, wrong wavelength.

Common QC Problems - Trends

QC results consistently decrease or increase over 6 or more consecutive days.
Cause must be identified, samples re-analyzed for correction of problem.
Examples: reagent degradation, temperature issues, change to light source.

Levey-Jennings Charts

Daily QC plotted on Levey-Jennings charts.
Charts visualize shifts and trends.
At least 2 levels of QC material should be analyzed daily for each test.

Levey-Jennings Charts - Example

Example provided of a graph visualization and acceptance/rejection criteria of a test on a Levey-Jennings Chart.

Westgard Multirules

A set of quality control rules used to interpret quality control results for acceptability in a lab.
If any rule (except the warning rule) is violated the lab results are not acceptable.

Westgard 12s Rule

One point exceeds +2SD.
Acceptable random error in results is often indicated by this rule. (ex: air bubble in sample).

Westgard 13s Rule

One point exceeds +3SD.
Indicates unacceptable random error or beginning of systematic issues in results.

Westgard 22s Rule

Two points above the mean and exceed +2SD.
Indicates a systematic error within the test protocol

Westgard 4s Rule

Four consecutive results beyond the +1SD line.
Indicates potential systematic error in the test.

Westgard 10x Rule

Ten consecutive results on the same side of the mean.
Indicates a systematic error.

Establishing Statistical Quality Control Limits

Determining acceptance range using multiple data points for a certain testing period to determine a mean and Standard Deviation.
Most labs accept the mean ± 2SD as the quality control range or acceptable values. This will equate to a 95% confidence that results are within acceptable range. QC results outside this range trigger a review and resolution for the test.
Methods of establishing acceptable ranges using 1, 2, and 3 SD.
Example calculation providing results.

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Description

This quiz focuses on the quality assurance processes in clinical chemistry, highlighting the three stages where errors can occur: pre-analytical, analytical, and post-analytical. Understanding these stages is crucial for ensuring accurate lab results and maintaining high standards in laboratory practice.