Quality Assurance in Hematology Group 11

Quality Assurance in Hematology

Prepared by:Michelle PobladorJethro Camaganacan

OBJECTIVES Define and discuss terms associated with Quality

Assurance Discuss and identify possible sources of error in

testing processes Describe the use of the statistics involved in QA Discuss several methods used to monitor internal

and external quality control Discuss the role of continuing education in

maintaining a quality laboratory Discuss the role that quality control plays in QA

program

INTRODUCTION

QA is the sum of all those activities in which the laboratory is engaged to ensure that information generated by laboratory is correct.

QA is not restricted to the development and retention of quality control charts but rather includes all aspects of laboratory activities that affects the results produced, from the choice of methods, to the education of personnel, to the handling of specimens and reporting results.

Quality Control involves procedures for monitoring and evaluating the characteristics of the testing system.

QC is exercised by analyzing control samples along with patient samples and applying appropriate statistical methods to the results to establish accuracy and precision.

QC involves taking any necessary corrective actions to bring the results into conformance.

The real purpose of QA activities is to determine how correct or incorrect the results emanating from the lab are, and to allow those managing the lab to determine whether or not the lab is fulfilling its functions satisfactorily.

1) Preventive – those activities that are done prior to the examination of the specimen or sample and that are intended to establish systems conducive to accuracy in analytical testing ( e.g. preventive maintenance and calibration of instruments, testing of media, orientation and training of personnel )

2 ) Assessment – those activities that are done during testing to determine whether the test systems are performing correctly ( e.g. the use of standard and controls, maintenance of control charts )

3 ) Corrective – those activities that are done, when error is detected, to correct the system ( e.g. equipment troubleshooting, recalibration of instruments )

Three Major Activities of QA

Components of QA Program

Internal Quality AssuranceExternal Quality AssuranceStandardizationProficiency Surveillance

Accuracy - the closeness of the estimated value to the true

mean- can be checked by the use of reference materials

which have been assayed by independent methods of known precision

Precision - reproducibility of a results, whether accurate or

inaccurate within a define frame time ( e.g: within the same day, from week to week etc )

- can be controlled by replicate tests, check tests on previously measured specimens and statistical evaluation of results

Definition of Terms:

Examples of Precision and Accuracy:

Control – a material that has a predetermined assay value and typically the same matrix as the patient samples. Ideal control substance:

- specially prepared

- inexpensive

- prolonged stability

- sampled directly

- suspends easily and does not agglutinate

- should have controls of high, normal and low values

- flow characteristics similar to those of blood

- particle size and shape similar to blood

Primary Standard - reference material that is used to calibrate an instrument or prepare standard curves for normal assays. – any certified reference material that is

generally accepted or officially recognized as the unique std. for the assay, regardless of its level of purity

Secondary Standard – reference material in which the analyte concentration had been ascertained by reference to a primary standard and can be used as a primary standard

Calibrator – a preserved human or surrogate cell suspension whose hematology parameters have been determined by multiple reference laboratories and monitored daily by the distributor.

Delta Checks – comparing a patient’s current test result to a previous result for the same analyte.– monitored by analytes that have little intraindividual

variation Reliability – refers to the extent to which a method is

able to maintain accuracy and precision over time. Reference Interval – describes the range of values for

an analyte in healthy individuals. – “normal range”– should be determined for men, women and children

Statistical Description of Populations

Mean ( x ) – the total score of all the measurements divided by the

number of measurements

Standard deviation ( SD ) – variation in measurement obtained in lab tests

formula: SD = Σ ( x – x )2

n – 1 n : number of measurement

Coefficient of variation ( CV ) – relation of SD to the actual measurement

formula : CV = SD X 100% x

Reference Interval Determination

Reference sample group – individuals from the reference population used

to determine the reference interval– carefully selected as defined by a set of

predetermined criteria– minimum of 120 individuals, sexes should be

equally represented

Analysis of Data

Standard deviation of control specimens- if value assigned to a specimen a number of times,

dispersion of results around the mean will indicate the error of reproducibility

- 95% of results on the same specimen should be within ± 2 SD and 99.7% within ± 3 SD

- by chance, 1 in 20 of measurement might expected to fall outside 2 SD and only 1 in 333 outside 3 SD

– if measurement more widely dispersed, this indicates an error in the test

Control Charts- Originally described by Shewhart, 1st applied in

Clinical Chemistry by Levey and Jennings- Samples of the control specimen are included in every

batch of patients’ specimens and the results checked on a control chart

- Value has been determined reliably by a reference method, the same material can be used to check accuracy or to calibrate an instrument

- If possible, controls with high, low and normal values should be used

- Advisable to use at least one control sample per batch even if the batch is very small

- The results obtained with the control samples can be plotted on a chart

Cumulative Sum Method ( CUSUM )

- is the running total of the difference between each measurement and the established mean of the control tests

- It provides another way to display the data obtained in the precision test

- More sensitive than control chart – faulty technique or instrument

- Useful for detecting a change in performance (d/t) drift ( a consistent error in one direction ) or a slight progressive drift away from the original mean

Duplicate Tests On Patient’s Specimens

- provides another way of checking the precision of routine work

- Test 10 consecutive specimens in duplicate under careful conditions

- Calculate the differences between the pairs of results and derive the SD

- Subsequent duplicate tests should not differ from each other by more than 2 SD

- This methods will detect random errors but it is not sensitive to gradual drift nor will it detect incorrect calibration

- Impractical for routine blood counts in a busy lab- A few consecutive specimens in a batch should be

tested from time to time as a rough check

Use Of Normal Hematological Data For QC - In healthy individuals the blood count remains

virtually constant day by day- It is possible to use observations on healthy

individuals for quality control in routine lab- Analyze 5-10 healthy subjects at intervals and

calculating mean and SD for MCV, MCH and MCHC- On each occasion the mean should not vary by more

than 2 SD and the SDs should remains constant- A significant difference in mean indicates a constant

error (e.g. incorrect calibration)- A random error will result in an increase in SD

although the mean may be unaffected

Clinical Efficacy Measurements

Diagnostic sensitivity

Is the proportion of patients with the disease who have a positive test result.

Formula: Sensitivity= (TP ÷ [TP + FN]) x 100.

Where: TP is # true positive, and FN is # of false negatives.

Used when a normal result serves to rule out a suspected disease. Describes the lowest amount of a substance that can be detected

accurately by a test method

Diagnostic specificity

Is the proportion of patients who are identified correctly by the test as not having the disease.

Formula: Specificity= (TN ÷ [TN + FP]) x 100.

Where: TN is # of true negatives, and FP is # of false positives.

Used when an abnormal result serves to confirm the presence of the disease.

Describes how well a test method can detect a particular substance rather than similar ones.

Positive Predictable Value (PPV)

Is the proportion of patients with the disease who have a positive test result compared with all the patients who have a positive test result.

Formula: PPV= TP ÷ (TP + FP) x 100.

Where: TP is the # of true positives, and FP is the # of false positives

Used to assess the diagnostic reliability of a positive test result. Predicts the probability that an individual with a positive test result

actually has the disease.

Negative Predictable Value (NPV)

Is the proportion of patients without a disease who have a negative test result compared with all the patients who have a negative test result.

Formula: NPV= TN ÷ (TN + FN)x 100.

Where: TN is the # of true negatives, and FN is the # of false negatives.

Used to assess the diagnostic reliability of a negative test result. Predicts the probability that an individual with a negative test result

does not have the disease.

Types of Analytical Errors:

Errors can occur at any stage of the testing process: before analysis (preanalytical), during analysis (analytical), and after analysis ( post analytical).

Systematic Errors: Errors within the test system or method. These may be caused by: incorrect calibration procedures,

malfunctioning component, or failure of some part of the testing process to perform precisely.

This type of error affects the accuracy of the test method. Systematic error is subdivided into constant and proportional

systematic errors.

Types of Systematic Errors:

Constant systematic errors: Errors in the test system in which the magnitude of an error remains

constant throughout the range of the test measurements. Also called as constant bias (e.g., all hemoglobin values read 2 g/dl

higher than the true value).

Proportional systematic errors: Errors in the test system in which the magnitude of an error increases

with the concentration of the substance being measured. E.g., at hemoglobin level 8 g/dl, the error is 1g; at 9 g/dl, it is 1.5

g/dl; at 10 g/dl, it is 2.

Random Errors:

Are mistakes that occur without prediction or regularity.

Maybe caused by instability of the instrument, change in temperature, or operator variability.

It affects the precision and accuracy of a test method.

Sources of Errors:

Preanalytical errors: Are those that occur before actual analysis. Preanalytical errors includes misinterpreted physician test orders,

patient misidentification, incorrect patient preparation for specimen collection, incorrect sampling technique, improper collection container, and improper method of sample transport or handling.

Postanalytical Errors: Are those that affect the handling of the test result after the analysis

has taken place. It includes incorrect result entry, failure to notify the physician of

critical results, results placed in the wrong patient chart, and miscommunication of results telephoned to nursing units or physician.

Internal Quality Control

Based on monitoring the haematology tests procedures that are performed in the lab.

Includes measurements on specially prepared materials, and repeated measurements on routine specimens, statistical analysis and day by day data obtained from the tests which have been routinely carried out.

Is intended to ensure that there is continual evaluation of the reliability of the work of the lab and that control is exercised over the release of the results.

It is primarily a check of precision but not necessarily accuracy. includes measurements on CONTROLS & is intended to ensure that

there is continual evaluation of the reliability of the work of the lab and that control is exercised over the release of the results.

Levey-Jennings Control Charts

Nomal Distribution


Deviation from this distribution indicates the occurrence of an analytical systemic error.

Approx. 65% of the repeated values are between the ± 1s ranges and distributed evenly on either side of the mean.

In a properly operating system, 95 % of the values should fall between the ± 2s ranges and 99 % between the ± 3s limits.

This means that 1 data point in 20 should be located between either of the 2s and 3s limits.

And 1 data point should occur outside of the 3s limits once in every 100 analyses.

± 2s limits are considered warning limits. Values that exceed the 2s and 3s limits indicate that the analysis

must be repeated, 3s limits are rejection limits.


Shift

A shift is a drift of values from one level of the control chart to the other.

Maybe sudden or gradual. Considered as constant systemaic error.


Trend

A trend is the continuous movement of values in one direction over six or more consecutive values.

In hematology trend has something to deal with deterioration of reagents or problems with pump tubing or light sources.

Multirule (Westgard) Analysis

12s -refers to the control rule that is commonly used with a Levey-

Jennings chart when the control limits are set as the mean plus/minus 2s. In the original Westgard multirule QC procedure, this rule is used as a warning rule to trigger careful inspection of the control data by the following rejection rules.


13s-refers to a control rule that is commonly used with a Levey-Jennings

chart when the control limits are set as the mean plus 3s and the mean minus 3s. A run is rejected when a single control measurement exceeds the mean plus 3s or the mean minus 3s control limit.


22s - reject when 2 consecutive control measurements exceed the same

mean plus 2s or the same mean minus 2s control limit.


R4s - reject when 1 control measurement in a group exceeds the mean

plus 2s and another exceeds the mean minus 2s.


41s - reject when 4 consecutive control measurements exceed the same

mean plus 1s or the same mean minus 1s control limit.


10x - reject when 10 consecutive control measurements fall on one side

of the mean.


Multirule QC uses a combination of decision criteria, or control rules, to decide whether an analytical run is in-control or out-of-control.

Standardization

Refers to both materials and methods A material standard or reference preparation is used to calibrate

analytic instruments and to assign a quantitative value to calibrators A reference method is an exactly defined technique which provides

sufficiently accurate and precise data for it to be used to assess the validity of other methods

International reference preparations are not freely available for routine use but are intended to act as standards for assigning values to commercial ( or lab produced ) ‘secondary standard’ or calibrators

Proficiency surveillance (External Q.C)

Implies critical supervision of all aspects of laboratory tests

( collection, labelling, delivery, storage of specimens before the tests are preformed and of reading and reporting of results )

Also includes maintenance and control of equipment and apparatus

It is necessary for correct interpretation of test results, for the lab to establish normal reference values that are valid for their test methods and their local population

Continuing Education

“The best prevention of errors is a well-trained and conscientious technologist.”

Certified clinical laboratory scientists and technicians A system of competency testing

– (e.g. the hematology supervisor may maintain a file of blood films that the applicant correctly analyzes at hiring)

Regularly scheduled re-testing Competency assessments Ongoing education program

Quality Assurance Plan

To monitor and evaluate the appropriateness of medical services

To correct problems and recognize clinical situations that require improvement

Helps to focus quality assurance activities Include goals, objectives, sources, a monitoring

activity calendar, corrective action, periodic evaluation, and methods of communication

Focus on high frequency problems Should improve the laboratory’s service, rather than

hinder it

Test requests

Timeliness Legibility Stat orders Order accuracy Order completeness

Specimen collection

Success rate of phlebotomy draws Patient availability Patient identification Patient preparation Timing of collection Labeling

Other indicators

Delta check follow-ups Repeated testing Turnaround time Critical test results Charting Telephone calls Computer errors Patient satisfaction surveys

QA Program must be comprehensive, including all sections and shifts

QA must be ongoing with evidence of continual quality assurance activity

Studies should be documented/summarized

Formation of a laboratory quality assurance team is crucial

Summary

Quality assurance is the coordinated effort to staff to enhance care of patients through monitoring, evaluation, and improvement of all aspects of laboratory service.

The goal of quality assurance is to verify that the quality of services contributes to overall delivery of excellent medical care.

Quality control is the component of quality assurance that involves the process of monitoring the characteristics of the testing system.

Quality control includes internal and external components, neccesary to corrective actions, and continuing education to maintain technical performance.

The distributions of many medical laboratory measurements in populations approximate a Gaussian curve.

Diagnostic sensitivity and specificity of tests influence how a test should be used when there is clinical suspicion of a disease.

Analytical error is a test system or method maybe constant systematic, proportional systematic, or random.

Sources of error may come not only from analytical functions, but also from preanalytical and postanalytical activities.

Levey-jennings control charts allow a laboratory professional to detect shifts or trend in a testing system.

Westgard rules can be used to determine the type of error that has been occurred.

Before a new assay may be implemented into the laboratory to obtain patient test results, it must be validated to ensure that it can produce quality test results.

Staff competence can be maintained and controlled through participation in continuing education programs.

THE END!

Thank you for listening!

Documents

Quality Assurance in Hematology Group 11