1. “revolutionising healthcare through continuously
improving diagnostic solutions”

2. UNDERSTANDING STATISTICS –
LABORATORY QUALITY CONTROL

3. 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

4. Quality control is underpinned by statistics
These statistics are used to provide confidence in data

5. 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.

6. 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.

7. 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

8. 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’

9. 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.

10. 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

11. 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

12. 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

13. 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

14. 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.

15. 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.

16. 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

17. 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

18. 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
NoYes
Yes Yes Yes Yes Yes

19. 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

20. Other Useful Statistics
• Coefficient of Variation (CV)
• Standard Deviation Index

21. 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

22. 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

23. THE FUTURE OF INTERLABORATORY
DATA MANAGEMENT

24. 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

25. 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

26. 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

27. 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

28. Acusera 24.7 Data Entry Options

29. Watch the Video

30. 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

31. Visit our website
www.Acusera247.com
Contact Us
Acusera@randox.com

32. “revolutionising healthcare through continuously
improving diagnostic solutions”