“revolutionising healthcare through continuously

improving diagnostic solutions”

UNDERSTANDING STATISTICS – LABORATORY QUALITY CONTROL

Learning Objectives:

1. Be able to calculate your own mean and standard deviation

for a set of QC results

2. Be able to calculate your own decision limits

3. Be able to draw a Levey-Jennings chart

4. Accept or reject results based on QC multi-rules

Quality control is underpinned by statistics

These statistics are used to provide confidence in data

Assayed Control Vs. Precision Controls

Precision (Unassayed) Controls Precision controls are supplied without target values or ranges as such

laboratories will need to determine their own mean for comparison.

Precision controls can effectively be used to assess precision however

cannot be used in isolation to assess accuracy. (When combined with a

Peer Group Reporting programme they may be used to monitor

accuracy)

Assayed controls Assayed controls can be used to assess both precision and accuracy

and are supplied with pre-assigned target values and ranges. When

using an assayed control however you may still be required to

establish your own mean and range as sometimes the ranges supplied

will be too wide and will not serve as a good measure of accuracy.

How to interpret your QC results….

Remember IQC…..

………..is used to monitor the accuracy and precision of the

complete analytical process both daily and over time in

order to detect errors ….. so that you can decide if patient

results are reliable and can be released.

So in order to interpret your IQC results meaningfully you

need to decide what is sufficient accuracy and what is

sufficient precision for each analytical test performed, in

order to ensure you are producing reliable patient results.

1. Calculate the mean

2. Calculate SD

3. Establish Decision limits

4. Create a Levey-Jennings chart

5. Accepts or reject results based

on a defined set of QC rules.

Steps in Interpreting Your QC

Results

Step 1 – Establishing the Mean

a) Analyse the QC sample a

minimum of 20 times over several days

b) Calculate the average or mean value

c) Compare the observed value to that quoted by the manufacturer.

d) Providing the observed value falls within the quoted range it will then become the ‘new mean’

Step 1 – Establishing the Mean

• The mean provides a good estimate of the true value

or accuracy for a specific level of control. May also be used to indicate the presence of systematic error.

• External Quality Assessment (EQA) and Peer Group Comparison programs will provide useful information on the means and SDs observed in other laboratories.

• Peer group comparison programmes can also be used to automatically calculate the mean and cumulative means.

Formula:

Step 2: Calculate the Standard

Deviation

a) Calculate the difference of each control result from the mean

b) Square the difference

c) Divide by the number of results minus 1 (n-1)

d) Finally calculate the square root

Step 2: Calculate the Standard Deviation

• The SD quantifies how close numerical values are in relation to each other providing a good measure of precision and an indication of random error.

• A small SD indicates good precision while a larger SD indicates variation in the results and thus poor precision. A large SD may also indicate random error.

• Peer group reporting programmes will automatically calculate the Standard Deviation however the SD can be easily calculated using a scientific calculator or an excel spreadsheet

Both the mean and SD are used to

establish decision limits. A 2SD range

is adopted by most laboratories.

a) Once the mean and SD have

been established calculate 2SD

by multiplying the SD by 2

b) To establish the lower decision

limits subtract 2SD from the

mean

c) To establish the upper decision

limits add 2SD to the mean

Example

Results: 101, 102, 103, 104, 105

Mean: 103

1SD: 1.6

2SD: 1.6 x 2 = 3.2

Calculation:

103 – 3.2 = 99.8

103+3.2 = 106.2

+/- 2SD range = 99.8 - 106.2

Step 3: Establish Decision Limits

Why use a 2SD range?

• In a normalised distribution it is estimated that 68% of data points will be within + 1SD and 95% of data points will be within + 2SD

Step 3: Establish Decision Limits

• Both the mean and SD should be

periodically recalculated throughout the

shelf life of each control lot

• Peer Group Reporting programmes will do

this each time a control is analytes and will

automatically calculated a cumulative

mean and SD.

Step 4: Create a Levey-Jennings chart

Using the mean and a +/-3 SD range create a Levey-Jennings

chart. Daily control data for each test and level of control is

plotted to monitor trends in performance over time.

Step 4: Create a Levey-Jennings

chart • Levey-Jennings charts can be used to identify

any positive/negative bias as well as trends over time

• Ideally there will be an even spread of results (within 1/2SD) above and below the mean

• Again a good QC program or Peer Group Reporting package will conveniently generate Levey-Jennings charts based on either the SD or percentage deviation from the mean

Step 5: Accepts or reject results

based on a defined set of QC rules. • QC rules are often referred to a Westgard

rules are used to help minimise false rejections and maintain a high degree of error detection

Step 5: Accepts or reject results based on a defined

set of QC rules.

IQC

Data

12

s

13

s

22

s

R4

s

4IS

In - Control

Accept Run

Out – of - Control Reject

Run

No

No No No No

No Yes

Yes Yes Yes Yes Yes

Step 5: Accepts or reject results

based on a defined set of QC rules. • The 12S rule is normally used as a warning rule

before applying other QC rules

• Most QC packages or peer group programs will allow laboratories to set user defined QC multi-rules for each individual test

• The program will then automatically reject/alert any QC results that violate any of the rules

Other Useful Statistics

• Coefficient of Variation (CV)

• Standard Deviation Index

Coefficient of Variation (CV)

• The CV is essentially the SD expressed as a percentage of the mean

CV = (SD/Mean) x 100

• The SD of a method is dependent on concentration i.e. the higher the concentration the larger the SD.

• The CV can therefore be used to assess performance over a range of concentrations

Standard Deviation Index (SDI)

• If participating in an EQA or peer group reporting program you will have come across the term SDI

• SDI is a measure of your performance relative to others in your peer group without having to consider magnitude of change

SDI = (Mean – Peer Group Mean) / SD of Peer Group

THE FUTURE OF INTERLABORATORY DATA MANAGEMENT

What is Acusera 24.7?

• An internal quality control and peer group reporting package

– Calculate internal statistics e.g. mean, SD, CV

– Minimise false rejections and the number of repeat tests with user defined QC multi-rules

– Detect and identify trends/errors through the use of Levey-Jennings and Histogram charts thus minimising expensive repeat tests and unnecessary troubleshooting

Acusera 24.7 Live Online Benefits • Online QC monitoring 24 hours a day, 7 days a week

– Acusera 24.7 can be accessed anytime, anywhere

– The online nature eliminates the need to backup/update software

• Peer group data generated from up to 20,000 laboratory participants – Peer group statistics available for a

wide range of instruments and methods

– Large peer groups to compare to

– Availability of statistically valid data

• Peer group statistics updated daily – Unique to Acusera 24.7

– Aids troubleshooting and may even help to identify issues before they arise in your lab

Acusera 24.7 Live Online

• Unique dashboard interface – Automatically displayed when a user logs in – Highlights poor performance at a glance – Highlights rejected/alerted results from the last

7 days

• Interactive charts capable of combining multiple analytes, lots and instruments – The program will automatically generate

Histogram, Levey-Jennings and performance summary charts

– Easily identify if the same bias or trends are seen with more than one level of QC or more than one parameter

Acusera 24.7 Live Online • Comprehensive reports for advanced bench review

– Laboratory comparison report – Exception report – Peer goup statistics – Data rejection report – Affiliate group reports

• Audit trail reports helping to meet regulatory requirements

– Records all actions relating to creation/modification of data

– Cannot be edited or destroyed – Excellent tool for documenting the

review process

• Automatic QC entry via Acusera 24.7 Connect – Connects to Middleware or LIMs for automated QC result entry – Eliminates issues with manual data entry – Increases efficiency and productivity

Acusera 24.7 Data Entry Options

Watch the Video

Learning Objectives:

1. Be able to calculate your own mean and standard deviation

for a set of QC results

2. Be able to calculate your own decision limits

3. Be able to draw a Levey-Jennings chart

4. Accept or reject results based on QC multi-rules

Visit our website www.Acusera247.com

Contact Us Acusera@randox.com

“revolutionising healthcare through continuously

improving diagnostic solutions”