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