control of analytical variables
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Control of Analytical Variables. Dr. Roula Hamid MSc Clin Biochem Central Puplic Health Laboratory QC Chemistry. Today is not the golden age of quality in healthcare laboratories. We can & should be doing the better. James O Westgard 2003. Introduction “Nice to Know”. - PowerPoint PPT PresentationTRANSCRIPT
Control of Analytical Variables
Dr. Roula Hamid MSc Clin BiochemCentral Puplic Health LaboratoryQC Chemistry
Today is not the golden age of quality in
healthcare laboratories .We can & should be doing
the better.
James O Westgard 2003
Introduction
“Nice to Know”
Quality Planning (QP(
Quality Laboratory Process (QLP(
Quality Control (QC(
Quality Assessment (QA(
Quality Improvement (QI(
Goals, Objectives, Quality Riquirements
Total Quality Management framework for management of quality in healthcare laboratories
The “five-Q” framework defines how quality is managed objectively with the “scientific method” or the PDCA cycle
PDCAPlan, do, check &
act
QP(PLANING steps)
QLP(standard process for
the way things are DONE)
QC & QA(CHECK)
QI(mechanism through
which to ACT on those measures)
Control of Analytical Variables
Analytical Variables must be controlled
carefully to ensure accurate measurements
by analytical methods
Documentation of analytical protocols Monitoring technical competency Statistical control of analytical methods EQA New quality initiatives
Documentation of Analytical Protocols
CLSI defines a process as a set of interrelated or interacting activities that transform input into output.
CLSI document describes the following section to be included in a laboratory procedure:
A. Title: clear & conciseB. Purpose or principle: e.g. this process describes
how …., C. Procedure instructions: how to doD. Related documents: listing of other procedure E. References: source of informationF. Appendixes or attachmentsG. Auther(s): author(s) of documentH. Approved signatures
Monitoring Technical Competency
Proper training of laboratory personnel to establish uniformity in technique is important.
Statistical control of analytical methods
Control materials General principles of control chart Performance characteristics of a control
procedures Westgard multirule chart Identifying sources of analytical errors
Control materials
Specimens that are analyzed for QC purposes are known as control materials
They need to be available 1) In a stable form2) In vial or aliquots3) & for analysis over an extended period of
time
General principles of control chart
A common method used to compare the values observed for control materials with their known values is the use of control charts
Figure: Gaussian frequency distribution
Control limit
Control limit
a) Stable performance
b) Accuracy problem; shift in mean
c) Precision problem; increase in standard deviation
Figure: Conceptual basis of control charts. Frequency distributions of control observations for different error conditions
0 5 10 15 20 25 30 35
-1.5
-1
-0.5
0
0.5
1
1.5
Figure: Conceptual basis of control charts. Frequency distributions of control observations for different error
conditions
Performance characteristics of a control procedures
The knowledge of performance characteristics of control procedures is necessory to select
the control rules that detect relevent laboratory problems without causing too
many false alarms
Westgard multirule chart
The probability of false rejection is kept low through selection of only those rules with low
The probabilities for error detection is improved through selection of those rules that are
particularly sensitive to random & systemic errors.
The use of multirule procedure is similar to the use of a Levey-Jennings chart, but the data
interpretation is more structured.
Figure: Decision path for QC program
To use the multirule procedure, the following steps are used:
C- 2 control samples are introduced into each analytical run
B- computer software; control values on y-axis ±4s, horizontal lines for 1s,2s & 3s, & x-axis for days
A- 20 days, 2 different materials, mean & SD are calculated for both.
D-
Analytical run is accept & patient results reported
Control observations fall within 2s limits
The analytical run is rejected & the patients results are not reported
If any is out
Additional rules are applied e.g. 13s.2 2s,R 4s & 10x
Patient results are held
One of control observations exceed 2s limits
E -
The analysis of the entire run repeated including both control & patient samples
The problem is corrected
Looking for the source of that error
The type of error is determined based on the control rule that have been violated
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30130
135
140
145
150
155
160
165
170
High Concentration Control Material
Run Number
Obs
erve
d Co
ntro
l Con
cent
ratio
n
Figure : Westgard multirule chart with control limit drawn at the mean ± 1s, 2s & 3s. Chart for high concentration
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 3084
88
92
96
100
104
108
112
116
Low Concentration Control MaterialO
bser
ved
Cont
rol C
once
ntra
tio
Figure : Westgard multirule chart with control limit drawn at the mean ± 1s, 2s & 3s. Chart for low concentration
Identifying sources of analytical errors
ERRORS
Systemic Random
Inspection OR Checklist
Analytical methods Equipments Reagents Specimens
Alerted to a control problem
Systemic Errors
Impure calibration materials
Improper preparation of calibrating solution
Erroneous set points & assigned valuesUnstable calibrating
solutions
Contaminated solutions
Inadequate calibration technique
Nonlinear or unstable calibration function
Inadequate sample blank
Unstable reagent blanks
Random Errors
Lack of reproducibility in the pipettingof samples & reagents
Dissolving of reagents tablets & mixing of sample & reagents
Lack of stability of temperature baths, timing regulation, &
photometric & other sensors
EQA
Procedures used to compare the performance of different laboratories
(EQA)
IQC & EQA are complementary
IQC
•For daily monitoring of accuracy
•For daily monitoring of precision
EQA
•Maintenance of long term accuracy of the analytical methods
Features of External Quality Assessment Programs EQA program available to the clinical
laboratories by professional societies & manufactures of control materials
All the participating laboratories analyzing the same lot of control material
Results are tabulated periodically & sent to the sponsering group for data analysis
The reports often includes extensive data analysis, statesical sumaries & plots
The mean of values of all laboratories is taken as the true or correct value & is used for comparision with the indivisual laboratory’s mean
Different approaches for data anaalysis e.g. t-test, SDI,Youden plots & Levey-Jennings plots
New quality initiatives
The six sigma processLean productionISO 9000
The six sigma process The six sigma control is an evolution in quality
management
6 sigma or 6 SD of process variation should fit within the tolerance limits for the process
- 6s -5s -4s -3s -2s -1s 0s 1s 2s 3s 4s 5s 6s
+Tolerance specification
-Tolerance specification
Target
Figure : Six sigma goal for process performance “ tolerance specification” represents the quality requirements
Lean production
It is a quality process that is focused on creating more value by eliminating activities that are considered waste
e.g. Lean team at Saint Mary’s Hospital used lean production to improve the efficiency of its paper ordering system for lab work in their ICU.
Six sigma process
Improve quality
Management of health care facilities & clinical laboratories
Lean Production
Increase efficiency
ISO 9000
The International Standard Organization (ISO) has developed the ISO 9000 standards
It is a set of 4 standards (ISO 9001-9004) enacted to ensure quality management & QA.
ISO 9000 represents an international consequence on the essential features of a QS to ensure the effective operation of an organization
Joint Committee for traceability in Laboratory Medicine
The traceability of values assigned to calibrators &/or control materials must be assured
through available reference measurement procedures &/or available reference materials
of a higher order
Definitive method
Method validation
Primary reference material
Reference method
Method validation, external quality
control
Field method
Control material IQC
True value
Observed value
traceability
Figure: Structure of an accuracy based measurement system showing relationships among reference methods & materials
Secondary reference method
References
Burtis,C.A., Ashwood,E.R. & Br uns,D.E. Fundamentals of Clinical Chemistry. 2008. .6th.ed. SAUNDERS ELSEVIER. P:249-262.
Arneson,W. & Brichell,J. Clinical Chemistry ‘A Laboratory Perspective’. 2007. F. A. Davis Company. P:53-72.
Westgard,J.O. Internal Quality Control: Planning & Implementation Strategies. 2003. Ann Clin Biochem. 40; 593-611.
Thank you