presented on training organized by "Provincial Public Health Laboratory- Bagamati State" dated 21 september 2022

1. Overview of Quality Control and
its implementation in the
laboratory
Dipesh Tamrakar
MSc. Clinical Biochemistry (IOM-TUTH)
BSc. MLT, CMLT

2. • Why do we need to about TQM/QA/QC?
• What are its practical approaches in the lab?
• Can we do it regularly in the lab of our setup?

3. Overview
• Brief on TQM, QA, QC
• Quality Indicators
• Lab errors
• Quality Control
• Implementation of QC in the lab

4. WHAT IS LABORATORY TEST ?
• “A laboratory test is intervention of any kind (diagnostic or
therapeutic) ; more likely to benefit than to harm the patient
and can be done at a reasonable cost and with reasonable
risk”.
• Laboratory tests provide information (with strong impact)
which help doctors to provide better and more effective care
for their patients.
• Laboratory results are component of 70% medical claims =
70% of medical decisions = 70% of medical records

5. ROLES OF LABORATORY MEDICINE
1. Perform laboratory investigations
2. Improve testing appropriateness
3. Improve patient outcomes
4. Improve decision making strategies
5. Improve cost effectiveness
6. Educate clinical users
7. Clinical optimization of operational efficiencies
8. Survey performance through appropriately designed quality control
9. Assist and improve on laboratory clinic interface
10. Improve information accessibility to the patient
11. Speed-up bringing in new diagnostic EVIDENCE BASED technologies
12. Redesign diagnostic paths towards an easier integrated service

6. STATUS and CHALLENGES
• Status: Laboratory experts are often perceived as a service for doctors.
• In order to have a successful healthcare ecosystem, they need to have the
same status as other experts in their own medical disciplines.
• Laboratory experts involve themselves more in structuring and ordering
tests
• Poor communication between medical departments and laboratories.
• Initiatives to make laboratory experts act as medical consultants are being
neglected that weakens the communication.
• Modern healthcare systems are oriented towards developing better
communication between doctors and laboratory experts.
• This form of communication has an enormous influence on the treatment
outcomes and medical expenses in general.

7. OFTEN KNOWN AS:
• Total Quality Control
• Total Quality Leadership
• Continuous Quality
Improvement
• Quality Management Science

8. • Quality assurance relates to how
a process is performed or how a
product is made.
• Quality control can be defined as
"part of quality management
focused on fulfilling quality
requirements."
• Quality control is more the
inspection aspect of quality
management.

9. • Quality Assurance - the overall program that ensures that the final
results reported by the laboratory are correct.
• It is much more concerned with :Right result from the Right test at
the Right time on the Right specimen from the Right patient with the
Right result interpretation based on correct reference data at the
Right price

10. Quality Control
• One of the most scientific and significant tool to correct errors in
analytical phase in the clinical laboratories
• Designed to monitor the routine performance of testing process
• Detect possible errors, reduce and correct deficiencies before the test
results are reported
• From service user: Quality of a good service for the price of the
product
• Internal quality control (IQC) and external quality assessment (EQA)
programs are used to assess and improve analytical performance.

11. IQC Vs EQA
• IQC is self-assessing tool by
using control samples for the
continuous and immediate
monitoring of the analytical part.
• IQC : to observe precise and
accurate results on daily
analytical phase
• EQA is intended for periodic and
retrospective observing of
laboratory results by an
autonomous external agency to
specify to the laboratory about
the accuracy or bias in their
systems methods and results.
• EQA : to monitor long term
accuracy and bias of their results
and stability of methods over a
longer period of time.

12. Aims of Quality assurance
• Accuracy and precision
• Satisfactory
• Quality report
• Economical
• Aims at preventing defects rather
than detecting the defects
• Minimize errors
• Timely report

13. Quality Assurance
An overall management plan to
guarantee the integrity of data (The
“system”)
PRECISION
The degree of fluctuation in the
measurements
Quality Control
A series of analytical measurements
used to assess the quality of the
analytical data (The “tools”)
ACCURACY
The closeness of measurements to the
true value
Quality Control is used to monitor both the precision and the accuracy
of the assay in order to provide reliable results.

14. • Precise and inaccurate
• Precise and accurate
• Imprecise and inaccurate

15. LABORATORY ERRORS ???
• From the patient’s perspective, every error is perceived
the same, whether it is made in pre-analytic, analytic or
post-analytic phase.
• Most of the errors occur outside the laboratory due to
various pre-analytic factors.
• A large number of errors occur in post-analytic phase as
well.
• In recent time, errors in analytic phase got significantly
reduced.

17. How to implement a laboratory quality control
program???

18. FLOW OF LAB PROCESS

19. •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
The Quality Assurance Cycle

21. Pre-analytical stage
• Test requisition slip
• Patient preparation
• Sample tube labeling
• Sample collection
• Sample transportation
• Reagent storage
• Reagent preparation
• Quality control sera
storage
• Callibrator storage
• QC alliquet storage
• Quality monitoring of
refrigerator, waterbath
• Maintenance and
cleaning of instruments
Machine maintenance: Daily, Weekly, Monthly and Annually

22. Preanalytical errors
• The importance of correctly carrying out all pre-analytical activities
performed by laboratory and non-laboratory staff in safeguarding the
quality and reliability of the final laboratory information.
• An error in any step of pre-analytical phase can adversely affect both
the quality of analytical results and the interpretation of information
provided.

23. Quality indicators of preanalytical phase
Misidentification error
• Misidentified requests
• Misidentified samples
• Samples with fewer than 2 identifiers
• Unlabeled samples
Inappropriate test request
• Requests without clinical questions (OPD)
• Inappropriate requests (OPD)
• Inappropriate requests (IPD)

24. Test transcription errors
• Erroneous data entry of
• Test name
• Missed test
• Added test
Unintelligible request
• Inappropriate sample type
• Samples collected in wrong container
• Incorrect fill level
• Inappropriate sample-anticoagulant volume

25. Unsuitable samples for transportation and storage problems
• Samples not properly stored before analysis
• Samples damaged during transportation
• Samples transported at inappropriate temperature
• Samples with excessive transportation time
• Contaminated samples
• Hemolyzed sample
• Clotted samples
• Inappropriate time in sample collection

26. Quality indicators for analytical phase
• Test with inappropriate IQC performances (CV higher than expected)
• Test uncovered by an EQA
• Unacceptable performances in EQA schemes
• Data transcription errors (manual or LIS failure)

27. Selection of Control & Calibrators
• Has a known concentration of the substance (analyte) being measured
• Used to adjust instrument, kit, test system in order to standardize the assay
Sources of QC samples:
• Appropriate diagnostic sample ( repeated samples for consecutive days)
• Obtained from:
• Another laboratory
• EQA provider
• Commercial product
• IQC depends on the analyzers available in the lab.
• EQA depends on availability of the resources

28. Characteristics of a Good Control
• The composition of the control material should be as similar to the
patient sample as possible, reacting in the same manner
• The analyte concentration should be at medically significant levels
• Stable under storage for longer period of time prior to preparation &
even after prep
• Low vial-to-vial variability
• Requiring a minimum preparation or ready to use
• Reasonable in price

29. Storage of QC Samples
• Controls are 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

30. Monitoring QC Data
• Use Levey-Jennings chart
• Plot control values each run
• Acceptance of run
• Monitor precision and accuracy of repeated measurements
• Review charts at defined intervals, take necessary action, and
document

31. 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

33. 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”
• Atleast run 2 control samples
12S rule R4S rule
13S rule 41S rule
22S rule 10X rule

34. 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
violation

35. 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
violation

36. 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
violation

37. 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
violation

38. 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
41S rule
violation

39. 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
violation

40. Westgard Multirule QC

41. 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

42. Types of Errors
Random=Fluctuations
Temperature
Personnel
Systematic
Reagent problem
Device problem

43. Solving “out-of-control” problems

45. Quality indicators for post analytical phase
• Turn around time
• Laboratory reports
• Notifications of critical values
• Interpretative comments

46. Post-Analytical Stage
• Delta Check
• Report entry
• Report verification at 2 different levels
• Report print out
• Turn around time
• Emergency parameters: 1 hour
• Routine parameters: 2 hours
• Special immuno parameters: 2:30 hours

47. Sample storage for last 2 days at 4 degree C

48. How to get it done in the lab?
• Plan: define the course of action
• Organized process
• systematically monitored by using accurate measures
• Staff: who does what
• Lead the action
• Control the system process

49. Six sigma matrics
• Six Sigma metrics are being adopted as the universal
measure of quality to be applied to their processes and
the processes of their suppliers.
• Six Sigma provides a more quantitative framework for
evaluating process performance and more objective
evidence for process improvement.
• Two methods can be used to assess process
performance in terms of a sigma metric (+6S to -6S).
• outcomes by inspection & variation and predict process
performance.
• Sigma = (TEa − bias)/SD [TEa=allowable total error]
• Methods with Six Sigma performance are considered
“world class”; methods with sigma performance less than

50. THANK
YOU

51. Points to take away ???