# Presentation: 928243

## Quality Control –Introduction

## The Quality System

**Information Management**

## The Quality Assurance Cycle

**The Quality Assurance Cycle**

- Pre-Analytic

- Analytic

- Post-Analytic

**Data and Lab Management**
**Safety**
**Customer Service**

- Patient/Client Prep
- Sample Collection

- Sample Receipt and Accessioning

- Sample Transport

- Quality Control

- Record Keeping

- Reporting

- Personnel Competency
- Test Evaluations

- Testing

## Quality Control

- Definitions
- Qualitative Quality Control
- Quantitative QC – How to implement
- Selection and managing control materials
- Analysis of QC data
- Monitoring quality control data

## What is Quality Control?

- Process or system for monitoring the quality of laboratory testing, and the accuracy and precision of results
- Routinely collect and analyze data from every test run or procedure
- Allows for  immediate corrective action

## Designing a QC Program – 

- Establish written policies and procedures
- Corrective action procedures
- Train all staff
- Design forms
- Assure complete documentation and review

## Qualitative vs.Quantitative

- Quantitative test
- measures the amount of a substance present
- Qualitative test
- determines whether the substance being tested for is present or absent

**Notes:**
Qualitative tests
Tests that do not have measurable endpoints, for example:
Growth-no growth
Positive-negative
Color change

## Qualitative QC

- Quality control is performed for both, system is somewhat different
- Controls available
- Blood Bank/Serology/Micro
- RPR/TPHA
- Dipstick technology
- Pregnancy

## Stains, Reagents, Antisera

- Label containers
- contents
- concentration
- date prepared
- placed in service
- expiration date/shelf life
- preparer

## Media Preparation

- Record amount prepared
- Source
- Lot number
- Sterilization method
- Preparation date
- Preparer
- pH
- Expiration date

## Microbiology QC

- Check:
- Sterility
- Ability to support growth
- Selective or inhibitory characteristics of the medium
- Biochemical response
- Frequency
- Test QC organisms with each new batch or lot number
- Check for growth of fastidious organisms on media of choice – incubate at time and temp recommended
- RECORD Results on Media QC form

**Notes:**
Check for sterility – incubate uninoculated plate – continue only if no growth

## Quality Control: Stains and Reagents

- Gram stain QC
- Use gram positive and gram negative organisms to check stain daily
- Other :
- Check as used – positive and negative reactions

## Stock QC organisms

- Organisms to be maintained must be adequate to check all media and test systems.
*E. coli* – MacConkey, EMB,  susceptibility tests
*Staphylococcus aureus* – Blood agar, Mannitol Salt, susceptibility tests
*Neisseria gonorrhoeae* – chocolate, Martin-Lewis

**Notes:**
Discussion of where to get control organisms
Discuss media used in their labs and what organisms should be used to test it.
ATCC – best, but other sources may be available.

May use known organisms from their lab and make stock cultures??

## Detecting Errors

- Many organisms have predictable antimicrobial test results
*Staphylococcus* spp. are usually susceptible to vancomycin
*Streptococcus pyogenes* are always susceptible to penicillin
*Klebsiella pneumoniae* are resistant to ampicillin

**Notes:**
I think you could include a pretty long list here, that are worldwide in application.

## Sources of Error

- If you encounter an unusual pattern
- rule out error by checking identification of organisms
- repeat antimicrobial susceptibility test
- Report if repeat testing yields same result, or refer the isolate to a reference laboratory for confirmation

**Notes:**
Establish patterns in your patient population and advise health care providers.

So providers can initiate treatment if necessary before susceptibility testing is complete

## Quality Control – Quantitative Tests

- How to implement a laboratory quality control program

## Implementing a QC Program –Quantitative Tests

- Select high quality controls
- Collect *at least* 20 control values over a period of 20-30
-       days for each level of control
- Perform statistical analysis
- Develop Levey-Jennings chart
- Monitor control values using the Levey-Jennings chart and/or Westgard rules
- Take immediate corrective action, if needed
- Record  actions taken

**Notes:**
Monitor control values on a run-by-run basis using the Levey-Jennings chart and/or Westgard rules 

Develop Levey-Jennings chart using the calculated values for mean, SD, and range

## Selecting Control MaterialsCalibrators

- Has a known concentration of the substance (analyte) being measured
- Used to adjust instrument, kit, test system in order to standardize the assay
- Sometimes called a standard, although usually not a true standard
- This is *not* a control

##  Selecting Control Materials Controls

- Known concentration of the analyte
- Use 2 or three levels of controls
- Include with patient samples when performing a test
- Used to validate reliability of the test system

## Control MaterialsImportant Characteristics

- Values cover medical decision points
- Similar to the test specimen (matrix)
- Available in large quantity
- Stored in small aliquots
- Ideally, should last for at least 1 year
- Often use biological material, consider bio-hazardous

**Notes:**
Values cover medical decision points – often use high and low, or normal and abnormal

## Managing Control Materials

- Sufficient material from same lot number or serum pool for one year’s testing
- May be frozen, freeze-dried, or chemically preserved
- Requires very accurate reconstitution if this step is necessary
- Always store as recommended by manufacturer

## Sources of QC Samples

- Appropriate diagnostic sample
- Obtained from:
-  Another laboratory
- EQA provider
- Commercial product

**Notes:**
1. QC Sample
The Sources of QC Samples
QC samples can be obtained from a number of different sources:
Producing your own external control  - requires resources because there are many validation and testing steps.  Can produce very large volumes with exact specifications.
Selecting a diagnostic sample - must meet QC sample requirements.  Cheaper option but difficult to get very large volumes so may have to change QC samples often.  This will inhibit the collection of longitudinal and batch to batch data.
Obtaining a QC sample form another laboratory - saves time, but does not guarantee a well standardised and validated product.  Collaboration between laboratories assists in providing the large volume required and may decrease costs. 
Samples provided as participation in an External QC Programme -this is the preferable option as it provides follow up and feedback on your performance in comparison to other laboratories. 
Commercially available controls - e.g. BBI Accurun (Boston Biomedica Inc) are purchased by the millilitre and are expensive.  Samples are ‘stand alone’ because no results are collected and no feedback is provided.  BBI Accurun is a very stable sample due to its production process which involves heat treatment.  Because of this the sample is not as sensitive to small fluctuations and may only identify large shifts in variation shifts, similar to the positive control. 

## Types of Control Materials

- Assayed
- mean calculated by the manufacturer
- must verify in the laboratory
- Unassayed
- less expensive
- must perform data analysis
- “Homemade” or “In-house”
- pooled sera collected in the laboratory
- characterized
- preserved in small quantities for daily use

## Preparing In-House Controls

## Criteria for Developing                           Quality Controls for HIV

- Low positive
- Between the cut off and positive control
- At a level where variability can be followed
- Generally ~2 times the cut off** **

**Notes:**
QC Sample Criteria
The selection of the QC sample is critical to the QC programme.  
A QC should be selected at a level where the sample can identify variability.  When plotting serial dilutions of a high positive sample this range is the linear portion of the sigmoidal curve, between the upper and lower plateau of the graph (Refer section 1.3.2 Selecting a suitable sample dilution).
Generally, an appropriate level for a QC sample is a low positive which reacts between the cut off and the low positive control.  For many assays a low positive which reacts at between 2 to 3 times the cut off is appropriate.
A sample at this level will identify any minor changes in assay performance which may not be easily recognised by reviewing the negative and positive kit controls.  For example, if a borderline QC sample proceeds out of range in the negative direction ie. below the lower control limit, this indicates an opportunity for the specimens with OD’s below the cut off to be falsely interpreted as negative.  A decrease such as this may not be evident if monitoring the negative or high positive kit controls.
The sample must be of good quality, of large volume and stable for long storage.

##  Production of a QC Sample - Production Protocol

- Materials
- Calculation of Volume
- stock sample
- diluent
- QC batch
- Method
- Validation Acceptance Criteria
- 	batch
- 	stability** **

**Notes:**
Protocol for the Production of QCs
A production protocol should be developed to ensure that a QC sample of high precision and consistent performance is the result.  This is particularly important when more than one batch of the same sample will be produced over time.
1.1 Materials
All materials to be used should be listed in the protocol, in particular the stock sample which will be diluted to make up the sample, must be identified.  This sample should be uniquely identified and its source, location and remaining volume recorded.
1.2 Calculating Volumes
The volumes of each reagent and the total volume of QC sample required must be calculated before beginning production to ensure all reagents  are available.
The volume of sample produced will depend on:
How  long the batch needs to last (eg 12 months)
The sample volume required by the assay (eg 20ul for Sanofi Genelavia MIXT HIV-1/2 and 400 ul for Abbott PRISM HIV-1/2 per run)
How often the assay is performed
Number of laboratories using the QC sample 
1.3 Method
The laboratory method to define what steps are required to produce the sample should be defined and documented.
1.4 Validation
The validation acceptance criteria for batch to batch variation and stability testing should be defined in the protocol and based on previous experience.

## Process for Preparing In-house Controls

- Serial dilution of high positive stock sample
- Select suitable dilution
- Produce large batch
- Test stability
- Test batch variation
- Dispense, label, store

**Notes:**
Method of QC Production
A protocol should be developed which details how to carry out each step. 

An original stock sample of high antibody titre is tested at different dilutions to identify a suitable antibody concentration to use as a QC sample  

 Large volumes of the selected dilution are prepared and tested on different batch numbers to validate the samples stability and reproducibility. 

After validation the sample is aliquoted into volumes suitable for a weeks use and stored according to protocol which will be written to assure sample stability during storage.

It may be appropriate to make a multi-marker QC sample which includes more than one analyte in the sample.  For example, the NRL has produced a multi-marker QC  sample which includes anti-HIV1/2, anti HTLV, anti-HCV and HBsAg markers.  

After production of a multimarker all analytes must be validated individually.

## Making Suitable Dilutions

**100 ul serum**
**in tube 1**

**100ul diluent in each tube**

**Mix and Transfer**

**Each tube is a 1:2 dilution **
**of the previous tube**

**Discard**

**Notes:**
1.3 Method of QC Production
1.3.1 Making Suitable Dilutions
A high antibody titre positive sample is diluted in normal human serum (NHS) or Basematrix (BioMedica BBI). 
The positive sample should be heat treated at 62°C for 20 minutes and filtered though a 0.2um Biological filter. 
A plasma diluent may need to be defibrinated, delipified and filtered (0.2um filter). 
An anti-bacterial agent such as Bronidox can be added to the dilutions.  Check the package insert of the assay which the QC sample is to be produced for, to ensure that the preservative is appropriate and will not interfere with assay performance.
A titration is conducted in tenfold or in doubling dilutions as follows.  
100ul of NHS is added to each tube.
100ul of positive sample is added to the first tube.
mix by moving the pipette plunger up and down at least 3 times.
transfer 100ul from tube 1 to tube 2 and mix well. 
repeat this step for the remaining tubes.
dilution in tube 10 is 1/1024 or in the case of tenfold dilution, 1010.
Test each titration in the particular assay(s) for which the QC is (are) being synthesised.

## Selecting a Suitable Sample Dilution

**Serial Dilutions on Abbott AxSYM HIV-1/HIV-2 MEIA**

**Doubling Dilutions**

**S/Co Ratio**

- 0

- 2

- 4

- 6

- 8

- 10

- 12

- 14

- 16

- 18

- 20

- Pos Cont 3.3

- Neg Cont 0.38

- Cut Off 1.0

**Notes:**
1.3 Method of QC Production
1.3.2 Selecting a Suitable Sample Dilution 
Plot the assay results against the sample dilutions to review the sigmoidal response curve.  
An appropriate QC dilution should be selected from the section of the graph were variability can be followed ie. the linear portion between 1/512 and 1/1638.  Sample dilutions at the upper and lower plateau of the graph will not identify variation.  
The dilution should be between the positive kit control value and the calculated cut off value.  
If a QC sample is chosen with an OD which is too low, then the OD may fluctuate above and below the cut off due to normal variations. Although variation can still be monitored with this sample it is preferable to choose a QC which is consistently reactive.  
A sample chosen with an OD which is too high will be of limited use for border line monitoring and may not identify subtle changes.
In the above example the 1/8192 dilution which produced a S/Co of 2.3 was chosen as the appropriate dilution. 
If the results achieved in the serial dilution are not suitable further dilutions between these titrations may be required.

## Batch Production 

- Prepare positive sample
- centrifuge
- heat inactivate
- Mix positive sample in diluent
- magnetic stirrer
- Bottle batch in numbered lots of suitable volume

**Notes:**
1.3 Method of QC Preparation
1.3.3 Batch Production
Centrifuge and filter (0.2um) positive sample.  Positive sample may be heat inactivated at 62oC for 20 minutes. (Note: this may disturb the reactivity in some assays).
Mix sample and the calculated volume of diluent for at least 1 hour on a magnetic stirrer in a biohazard cabinet, 3-4 hours may be required for volumes > 2 litres.  
Aliquot the batch into sterile large polypropylene storage containers such as Nalgene 250ml square bottles.  Do not use polystyrene containers as these adsorb antibodies and will alter the antibody level of the QC sample.  Number each bottle for future identification.
Store at 4°C until ready to dispense.

## Stability Testing 

- Assess the rate of deterioration

**QC Sample**

**Storage**

**Day 7**

**Day 14**

**Day 21**

**Day 28**

**-20c**

****

****

****

****

**4c**

****

****

****

****

**16-25°C**

****

****

****

****

**Notes:**
1.3 Method of QC Production
1.3.4 Testing the Stability of the QC
If the dilution selected is greater than 1/3000, it will be necessary to check the stability of the prepared sample to assess the rate of possible deterioration.  
Place aliquots of the diluted QC sample at -20C, 4C and  room temperature (in areas where room temperature is 15-25C) for one month.  The samples in multiple aliquots are then tested throughout the month at 7, 14, 21 and 28 days.
The results obtained at each temperature are reviewed and pass stability testing if the value is not statistically different from the original calculated results.  
The stability requirements are dependent on the future use of the sample.  For example, if a sample is to be shipped to another region and may be at ambient temperature for a few weeks in transit, it is critical that the QC sample pass stability testing at this level. 

## Batch Validation 

- Dispense aliquots
- Test aliquots
- Confirm desired titre level
- compare against target value
- Confirm minimal batch variation
- acceptable if CV <20%
- aim for <10%

**Notes:**
1.3 Method of QC Production
1.3.5 Batch Validation
The batch must be validated to ensure it has been sufficiently mixed and that the product is homogenous.
Validation of the QC sample is extensive and should include the testing of an appropriate number of aliquots to represent the total volume.  For example, if 1 litre of sample is produced and stored in 5 200 ml bottles, 20 aliquots from each of the bottles should be tested.  
The aliquots should be numbered so the results can be traced back to the original storage bottles. 
Test these aliquots in at least one assay system which the QC sample was designed to quality control.  Compare the results with the target value to ensure correct result.
Investigate the variability of the of the QC sample batch by calculating the coefficient of variation (CV) for selected samples.  The batch is acceptable if the CV of the results is less than 20% (a discussion on statistical analyses and how to calculate a CV is described further in this chapter) .   

This validation process is a most important step in the methodology especially for large volume batches of QC with extensive dilution (e.g. 5 litres of  1/3000 dilution).

## Storage of QC Samples 

- Validated batch aliquoted into smaller ‘user friendly’ volumes for storage
- Establish a storage protocol:
- store at -20oC
- in use vials stored at 4oC
- use 0.5 ml vial maximum of one week
- freeze-dried
- (requires accurate reconstitution)
- chemically preserved

**Notes:**
1.3 Method of QC Production 
1.3.6 Storing QC Samples
The QC sample is dispensed into labelled aliquot's of a smaller ‘user friendly’ volume. 
Aliquot's in use can be stored at 4C.  These should be discarded after 7 days and a new 1ml vial introduced. 
By aliqoting the sample into 1ml volumes all but the QC sample in use can be stored at -20C.  This prevents freeze thawing which can affect the QC sample result.  
1ml aliquot's can be sub-aliquoted if  the 1ml volume will not be exhausted in a week.
The label on the QC Sample should include the name of the QC Sample, and may include the expiry date (usually 12 months from the date of production) and the production laboratory’s initials.

## Slide 34

## Quality Control -Quantitative

- Analysis of QC Data

## How to carry out this analysis?

- Need tools for data management and analysis
- Basic statistics skills
- Manual methods
- Graph paper
- Calculator
- 	Computer helpful
- Spreadsheet
- Important skills for laboratory personnel

## Analysis of Control Materials

- Need data set of at least 20 points, obtained over a 30 day period
- Calculate mean, standard deviation, coefficient of variation; determine target ranges
- Develop Levey-Jennings charts, plot results

## Establishing Control Ranges

- Select appropriate controls
- Assay them repeatedly over time
- at least 20 data points
- Make sure any procedural variation is represented:
- different operators
- different times of day
- Determine the degree of variability in the data to establish acceptable range

## Measurement of Variability

- A certain amount of variability will naturally occur when a control is tested repeatedly.
- Variability is affected by operator technique, environmental conditions, and the performance characteristics of the assay method.
- The goal is to differentiate between variability due to chance from that due to error.

## Measures of Central Tendency

- Data are frequently distributed about a central value or a central location
- There are several terms to describe that central location, or the ‘central tendency’ of a set of data

## Measures of Central Tendency

- Median = the value at the center (midpoint) of the observations
- Mode = the value which occurs with the greatest frequency
- Mean = the calculated average of the values

## Calculation of Mean

**X = Mean**
**X****1 ****= First result**
**X****2 ****= Second result**
**X****n**** = Last result in series**
**n – Total number of results**

## Calculation of Mean:  Outliers

- 192 mg/dL
- 194 mg/dL
- 196 mg/dL
- 196 mg/dL
**160 mg/dL**
- 196 mg/dL

- 200 mg/dL
- 200 mg/dL
- 202 mg/dL
**255 mg/dL**
- 204 mg/dL
- 208 mg/dL
- 212 mg/dL

## Calculation of Mean

- 192 mg/dL
- 194 mg/dL
- 196 mg/dL
- 196 mg/dL
- 196 mg/dL
- 200 mg/dL
- 200 mg/dL
- 202 mg/dL
- 204 mg/dL
- 208 mg/dL
- 212 mg/dL
- Sum = 2,200 mg/dL

- Mean = the calculated average of the values
- The sum of the values (X1 + X2 + X3 ... X11) divided by the number (n) of observations
- The mean of these 11 observations is (2200  11) = 200 mg/dL

## Calculation of Mean:ELISA  Tests

- Collect optical density (OD) values for controls for each assay run
- Collect cutoff  (CO) value for each run
- Calculate ratio of OD to CO (OD/CO) for each data point or observation
- This ratio standardizes data
- Use these ratio values to calculate the mean

## Normal Distribution

- All values are symmetrically distributed around the mean
- Characteristic “bell-shaped” curve
- Assumed for all quality control statistics

## Normal Distribution

**Frequency**

**	****4.7’****	****4.8’****	****4.9’****	****Mean****	****5.1’****	****5.2’****	****5.3’**

## Normal Distribution

- Mean

## Accuracy and Precision

- The degree of fluctuation in the measurements is indicative of the “precision” of the assay.
- The closeness of measurements  to the true value is indicative of the “accuracy” of the assay.
- Quality Control is used to monitor both the precision and the accuracy of the assay in order to provide reliable results.

## Precision and Accuracy

- Precise and accurate

**Precision and Accuracy**

## Imprecise and  inaccurate

**Imprecise and  inaccurate**

## Measures of Dispersion or Variability

- There are several terms that describe the dispersion or variability of the data around the mean:
- Range
- Variance
- Standard Deviation
- Coefficient of Variation

## Range

- Range refers to the difference or spread between the highest and lowest observations.
- It is the simplest measure of dispersion.
- It makes no assumption about the shape of the distribution or the central tendency of the data.

## Calculation of Variance (S2)

## Calculation of Variance

- Variance is a measure of variability about the mean.
- It is calculated as the average squared deviation from the mean.
- the sum of the deviations from the mean, squared, divided by the number of observations (corrected for degrees of freedom)

## Degrees of Freedom

- Represents the number of independent data points that are contained in a data set.
- The mean is calculated first, so the variance calculation has lost one degree of freedom (n-1)

## Calculation of Standard Deviation 

## Calculation of Standard Deviation

- The standard deviation (SD) is the square root of the variance
- it is the square root of the average squared deviation from the mean
- SD is commonly used (rather than the variance) since it has the same units as the mean and the original observations
- SD is the principle calculation used in the laboratory to measure dispersion of a group of values around a mean

## Standard Deviation and Probability

- For a set of data with a normal distribution, a value will fall within a range of:
- +/- 1 SD 68.2% of the time
- +/- 2 SD 95.5% of the time
- +/- 3 SD 99.7% of the time

## Standard Deviation and Probability

- In general, laboratories use the +/- 2 SD criteria for the limits of  the acceptable range for a test
- When the QC measurement falls within that range, there is 95.5% confidence  that the measurement is correct
- Only  4.5% of the time will a value fall outside of that range due to chance; more likely it will be due to error

## Calculation of Coefficient of Variation

- The coefficient of variation (CV) is the standard deviation (SD) expressed as a percentage of the mean
- Ideally should be less than 5%

## Monitoring QC Data

## Monitoring QC Data

- Use Levey-Jennings chart
- Plot control values each run, make decision regarding acceptability of run
- Monitor over time to evaluate the precision and accuracy of repeated measurements
- Review charts at defined intervals, take necessary action, and document

## Levey-Jennings Chart

- A graphical method for displaying control results and evaluating whether a procedure is in-control or out-of-control
- Control values are plotted versus time
- Lines are drawn from point to point to accent any trends, shifts, or random excursions

## Levey-Jennings Chart

## Levey-Jennings Chart - Record Time on X-Axis and the Control Values on Y-Axis

- Time (e.g. day, date, run number)

## Levey-Jennings Chart -Plot Control Values for Each Run

- Time (e.g. day, date, run number)

## Levey-Jennings Chart Calculate the Mean and Standard Deviation;Record the Mean and +/- 1,2 and 3 SD Control Limits

- Mean

- Day

- +1SD

- +2SD

- +3SD

- -1SD

- -2SD

- -3SD

## Levey-Jennings Chart -Record and Evaluate the Control Values

- Mean

- Day

- +1SD

- +2SD

- +3SD

- -1SD

- -2SD

- -3SD

## Findings Over Time

**Findings Over Time**

- Ideally should have control values clustered about the mean (+/-2 SD) with little variation in the upward or downward direction
- Imprecision = large amount of scatter about the mean.  Usually caused by errors in technique
- Inaccuracy = may see as a trend or a shift, usually caused by change in the testing process
- Random error = no pattern. Usually poor technique, malfunctioning equipment

## Statistical Quality Control Exercise

- Hypothetical control values (2 levels of control)
- Calculation of mean
- Calculation of standard deviation
- Creation of a Levey-Jennings chart

## When does the Control Value Indicate a Problem?

- Consider using Westgard Control Rules
- Uses premise that 95.5% of control values should fall within ±2SD
- Commonly applied when two levels of control are used
- Use in a sequential fashion

## Westgard Rules

- “Multirule Quality Control”
- Uses a combination of decision criteria or control rules
- Allows determination of whether an analytical run is “in-control” or “out-of-control”

## Westgard Rules (Generally used where 2 levels of control material are analyzed per run)

- 12S rule
- 13S rule
- 22S rule

- R4S rule
- 41S rule
- 10X rule

## Westgard – 12S Rule

- “warning rule”
- One of two control results falls outside ±2SD
- Alerts tech to possible problems
- Not cause for rejecting a run
- Must then evaluate the 13S rule

## 12S Rule = A warning to trigger careful inspection of the control data

- Mean

- Day

- +1SD

- +2SD

- +3SD

- -1SD

- -2SD

- -3SD

- 12S rule violation

## Westgard – 13S Rule

- If either of the two control results falls outside of ±3SD, rule is violated
- Run must be rejected
- If 13S not violated, check 22S

## 13S Rule = Reject the run when a single control measurement exceeds the +3SD or -3SD control limit

- Mean

- Day

- +1SD

- +2SD

- +3SD

- -1SD

- -2SD

- -3SD

- 13S rule violation

## Westgard – 22S Rule

- 2 consecutive control values for the same level fall outside of ±2SD in the same direction, or
- Both controls in the same run exceed ±2SD
- Patient results cannot be reported
- Requires corrective action

## 22S Rule = Reject the run when 2 consecutive control measurements exceed the same +2SD or -2SD control limit

- Mean

- Day

- +1SD

- +2SD

- +3SD

- -1SD

- -2SD

- -3SD

- 22S rule violation

## Westgard – R4S Rule

- One control exceeds the mean by –2SD, and the other control exceeds the mean by +2SD
- The range between the two results will therefore exceed 4 SD
- Random error has occurred, test run must be rejected

## R4S Rule = Reject the run when 1 control measurement exceed the +2SD and the other exceeds the -2SD control limit

- Mean

- Day

- +1SD

- +2SD

- +3SD

- -1SD

- -2SD

- -3SD

- R4S rule violation

## Westgard – 41S Rule

- Requires control data from previous runs
- Four consecutive QC results for one level of control are outside ±1SD, or
- Both levels of control have consecutive results that are outside ±1SD

## Westgard – 10X Rule

- Requires control data from previous runs
- Ten consecutive QC results for one level of control are on one side of the mean, or
- Both levels of control have five consecutive results that are on the same side of the mean

## 10x Rule = Reject the run when 10 consecutive control measurements fall on one side of the mean

- Mean

- Day

- +1SD

- +2SD

- +3SD

- -1SD

- -2SD

- -3SD

- 10x rule violation

## Westgard Multirule QC

## When a rule is violated

- Warning rule = use other rules to inspect the control points
- Rejection rule = “out of control”
- Stop testing
- Identify and correct problem
- Repeat testing on patient samples and controls
- Do not report patient results until problem is solved and controls indicate proper performance

## Solving “out-of-control” problems

- Policies and procedures for remedial action
- Troubleshooting
- Alternatives to run rejection

## Summary

- Why QC program?
- Validates test accuracy and reliability

## Summary: How to implement a QC program?

- Establish written policies and procedures
- Assign responsibility for monitoring and reviewing
- Train staff
- Obtain control materials
- Collect data
- Set target values (mean, SD)
- Establish Levey-Jennings charts
- Routinely plot control data
- Establish and implement troubleshooting and corrective action protocols
- Establish and maintain system for documentation