5. →
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
6. →
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
7. The Quality Assurance Cycle
Patient/Client Prep
Sample Collection
Reporting
•Data and Lab
Management
•Safety
•Customer
Service
Personnel Competency
Test Evaluations
Sample Receipt
and Accessioning
Record Keeping
Quality Control
Testing
Sample Transport
8. Quality Assurance vs. Quality
Control
Quality Assurance
An overall
management plan to
guarantee the
integrity of data
(The “system”)
Quality Control
A series of
analytical
measurements used
to assess the
quality 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”
9. →
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
10. •
Support provision of high
quality health-care
→ Reduce morbidity
→ Reduce mortality
→ Reduce economic loss
•
Ensure credibility of lab
•
Generate confidence in
lab results
15. PROFICIENCY OF
PERSONNEL:
Education, Training, Aptitu
de, Competence, Commitm
ent, Adequate
number, CME, Supervision,
Motivation
USE OF APPROPRIATE
CONTROLS:
• Internal: Labs, Calibrated
against national
• External: Supplied by
manufacturer, National,
International
Assessment
REAGENTS
STABILITY, INTEGRITY AND
EFFICIENCY:
Stable, Efficient, Desired
quality, Continuously
available, Validated
DOCUMENTATION:
All the written
policies, plans, procedures, inst
ructions and records, quality
control procedures and recorded
test results involved in providing
a service or the manufacture of a
product
EQUIPMENT RELIABILITY:
Meet technical needs, Compatible,
User & maintenance friendly, Cost
effective, Validated
SPECIFICITY & SENSITIVITY
OF SELECTED TEST:
Adequate ST, Sufficient
SP, cost effective, compatible
with, available infrastructure
and
expertise, interpretable, meets
the needs/
objectives, validated
Procedural
reliability using
Standard
Operating
Procedures
16.
If you have not documented it,
you have NOT done it …
If you have not documented,
it is a RUMOUR !!!
17. •
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
18. It is a comprehensively
written document that
describes the laboratory
procedure and all other
related issues
Essential for ensuring
uniformity in laboratory
procedures
20. True Value
The known,
accepted value
of a
quantifiable
property
Measured Value
The result of an
individual’s
measurement of
a quantifiable
property
22. •
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.
23.
24.
25.
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).
26. •
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.
27. Systematic Error
Random Errors
Avoidable error
due to
controllable
variables in a
measurement.
Unavoidable errors
that are always
present in any
measurement.
Impossible to
eliminate
28.
29. •
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.
30.
31.
32.
33. •
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
35. 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
X
Frequency
•
68.2%
95.5%
99.7%
-3s-
2s
-1s
Mean
+1s
+2s
+3s
36. •
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
39. •
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
40. •
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
41. •
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
42. •
“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
43. 12S
rule
13S rule
22S rule
R4S rule
41S rule
10X rule
Used when 2 levels of
control material are
analyzed per run.
44. •
“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
48. •
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
49. 22S Rule = Reject the run when 2 consecutive control
measurements exceed the same
+2SD or -2SD control limit
+3SD
+2SD
+1SD
Mean
22S rule
violation
-1SD
-2SD
-3SD
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Day
50. •
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
52. •
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
55. •
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
56.
57.
58.
59.
60.
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
61.
62. •
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
TAKEN!!!!!
AND
CORRECTIVE
ACTIONS