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