Basics&
Need of Quality ControlIn Clinical Laboratory
Dr. Bikash Kr. Chaudhury MDConsultant (Biochemistry)Dept. of Laboratory MedicineIndira Gandhi Memorial HospitalMale’, Maldives
Objectives
• At the end of the presentation, participants should – Understand the basic principles of Quality control
– Understand the importance for internal and external quality control schemes
Quality is....
invisible when GOOD
impossible to ignore when BAD
Definitions
1.Quality Control
2.Quality Assurance
3.Quality Assessment
What is Quality Control?→ Quality control in the medical laboratory is a statistical process used to monitor and evaluate the analytical process that produces patient results.
→ Quality control refers to the measures that must be included during each assay run to verify that the test is working properly
What is Quality Assurance?→ Quality Assurance is defined as the overall program that ensures that the final results reported by the laboratory are correct.
i. Quality assurance means quality enhancement
ii. Quality assurance aims at ensuring that the data provided are reliable and relevant
iii. Quality assurance involves all measures that can be taken to improve laboratory efficiency and effectiveness.
iv. It ensures laboratory performance with minimum risk for laboratory workers and gives maximum benefit to the individual and community
The Quality Assurance Cycle
•Data and Lab Management•Safety•Customer Service
Patient/Client PrepSample Collection
Sample Receipt and Accessioning
Sample TransportQuality Control
Record Keeping
ReportingPersonnel CompetencyTest Evaluations
Testing
Quality Assurance vs. Quality Control
Quality Assurance Quality Control
An overall management plan to guarantee the integrity of data (The “system”)
A series of analytical measurements used to assess thequality of the analytical data (The “tools”)
“The aim of quality control is simply to ensure that the results generated by the test are correct. However, quality assurance is concerned with much more: that the right test is carried out on the right specimen, and that the right result and right interpretation is delivered to the right person at the right time”
What is Quality Assesment?→ Also known as proficiency testing
→ Quality Assessment is a means to determine the quality of the results generated by the laboratory
→ Quality Assessment is a challenge to the QA and QC programs
→ Quality Assessment may be external or internal, examples of external programs include EQAS, RIQAS, etc
Need of Quality Control In Clinical Laboratory
• Support provision of high
quality health-care
→ Reduce
morbidity
→ Reduce mortality
→ Reduce
economic loss
• Ensure credibility of lab
• Generate confidence in
lab results
Consequences of poor quality
• Inappropriate action– Over-investigation
– Over-treatment
– Mistreatment
• Inappropriate inaction– Lack of investigation
– No treatment
• Delayed action
• Loss of credibility of laboratory
• Legal action
Variables that affect the quality of results
The educational background and training of the laboratory
personnel
The condition of the specimens
The controls used in the test runs
Reagents
Equipment
The interpretation of the results
The transcription of results
The reporting of results
Factors influencing internal quality
Outside laboratoryOutside laboratory
Within laboratoryWithin laboratory
Samplehandling
Patientpreparation
Requisition
SamplereceivingSample
Collection
SampleTransport
PatientDoctor
Analysis
Reports
Results
Factors influencing quality: Pre-analytical
→ Specimen
→ Collection technique
→ Storage and
transportation
→ Quantity
→ Labeling
→ Mismatch of sample
→ Laboratory : No necessary
test capacity
Factors influencing quality: Analytical
EQUIPMENT RELIABILITY:Meet technical needs, Compatible, User & maintenance friendly, Cost effective, Validated
Procedural reliability using
Standard Operating
Procedures
REAGENTS STABILITY, INTEGRITY AND EFFICIENCY:Stable, Efficient, Desired quality, Continuously available, Validated
SPECIFICITY & SENSITIVITY OF SELECTED TEST:Adequate ST, Sufficient SP, cost effective, compatible with, available infrastructure and expertise, interpretable, meets the needs/ objectives, validated
PROFICIENCY OF PERSONNEL: Education, Training, Aptitude, Competence, Commitment, Adequate number, CME, Supervision, Motivation
USE OF APPROPRIATE CONTROLS:• Internal: Labs, Calibrated against national• External: Supplied by manufacturer, National, International
DOCUMENTATION:All the written policies, plans, procedures, instructions and
records, quality control procedures and recorded test results involved in providing a service or the manufacture of a
product
Assessment
ANALYTICAL FACTORS
Documentation
If you have not documented it,
you have NOT done it …
If you have not documented,
it is a RUMOUR !!!
Value of Documentation
• Ensures processes and outcomes are traceable
• Processes can be audited, thus external
assessments can take place
• Tool for training
• Reminds you what to do next
Standard Operating Procedures (SOP)
It is a comprehensively
written document that describes
the laboratory procedure and all
other related issues
Essential for ensuring
uniformity in laboratory
procedures
Factors influencing quality: Post-analytical
Right recording and
reporting
Right interpretation Range of normal values
Right turnaround
time
Report to right user
True Value vs. Measured Value
True Value
The known, accepted value of a quantifiable property
Measured Value
The result of an individual’s measurement of a quantifiable property
Accuracy vs. Precision
AccuracyHow well a measurement agrees with an accepted value
PrecisionHow well a series of measurements agree with each other
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.
Accuracy vs. Precision
Accuracy vs. Precision
Errors in measurement
True value - The known, accepted value of a
quantifiable property
Accepted true value - the value approximating the
true value, the difference between the two values is
negligible.
Error - the discrepancy between the result of a
measurement and the true (or accepted true value).
Sources of error
• Input data required - such as standards used, calibration values,
and values of physical constants.
• Inherent characteristics of the quantity being measured
• Instruments used - accuracy, repeatability.
• Observer fallibility - reading errors, blunders, equipment selection,
analysis and computation errors.
• Environment - any external influences affecting the measurement.
• Theory assumed - validity of mathematical methods and
approximations.
Systematic & Random Errors
Systematic ErrorAvoidable error due to controllable variables in a measurement.
Random ErrorsUnavoidable errors that are always present in any measurement. Impossible to eliminate
Random Error
• An error which varies in an unpredictable manner, in magnitude and
sign, when a large number of measurements of the same quantity are
made under effectively identical conditions.
• Random errors create a characteristic spread of results for any test
method and cannot be accounted for by applying corrections.
Random errors are difficult to eliminate but repetition reduces the
influences of random errors.
• Examples of random errors include errors in pipetting and changes in
incubation period. Random errors can be minimized by training,
supervision and adherence to standard operating procedures.
Systematic Error
• An error which, in the course of a number of measurements of
the same value of a given quantity, remains constant when
measurements are made under the same conditions, or varies
according to a definite law when conditions change.
• Systematic errors create a characteristic bias in the test results
and can be accounted for by applying a correction.
• Systematic errors may be induced by factors such as
variations in incubation temperature, blockage of plate washer,
change in the reagent batch or modifications in testing method.
My control results are “out of control”! Now what?
Monitoring QC Data
Statistical Quality Control Exercise
• Hypothetical control values (2 levels of
control)
• Calculation of mean
• Calculation of standard deviation
• Creation of a Levey-Jennings chart
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
Calculation of Standard Deviation
mg/dlS 1N)x(x 2
1
variance
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
68.2%
95.5%
99.7%F
requ
ency
-3s - 2s -1s Mean +1s +2s +3s
X
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
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 -Records and Evaluate the Control Values
80
85
90
95
100
105
110
115
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Mean
Day
+1SD
+2SD
+3SD
-1SD
-2SD
-3SD
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
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
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” developed by Dr. James O.
Westgard based on statistical concepts
• Uses a combination of decision criteria or control rules
• Allows determination of whether an analytical run is “in-control”
or “out-of-control”
Dr. Westgard
Westgard Multirule System Titles
12S rule
13S rule
22S rule
R4S rule
41S rule
10X rule
Used when 2 levels of control material are analyzed per run.
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Mean
Day
+1SD
+2SD
+3SD
-1SD
-2SD
-3SD
10x rule violation
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
Westgard Multirule QC
Why use Westgard Rules?
• We use Westgard Multi-rules to help us reduce
costs while maintaining a high level of certainty that
our analytical process is functioning properly.
• In other words to diminish the false rejection
rate without compromising quality.
Why go through all this?
Accreditation
Accreditation
It is a process of inspection of laboratories and their licensing by a
third party to ensure conformity to pre-defined criteria
Very very long task (it may take around 2-3 years to follow the
roadmap)
Last step of the entire process
Quality assurance (procedures, way of working)
IQC
EQC
Networking of the laboratories
… and then only accreditation if 1-4 completed
Carry home message……..
• Quality is a lousy idea …if its only an Idea
• Quality assurance measures what a lab can do to
improve reliability
• Validate all test accuracy and reliability
• ALWAYS, ALWAYS, ALWAYS: DOCUMENT THE
PROBLEM AND CORRECTIVE ACTIONS TAKEN!!!!!
Thank you for your attention