BIOCHEMISTRY

PRACTICALS
PHLEBOTOMY

BC 14.20: Describe & Identify Pre-Analytical (especially order of draw, tourniquet technique),
Analytical, Post Analytical errors.

Objectives:

 Describe & identify the various errors in the clinical laboratory pre-analytical, analytical, post-
analytical phases

 Explain the order of draw of blood sample

 Explain the proper phlebotomy technique Teaching

Method: Small group

 Phlebotomy is a procedure in which blood sample is taken from a vein. It is of two types –
1. Diagnostic phlebotomy – This type of phlebotomy is used to diagnose diseases,
conditions or various factors in blood.
2. Therapeutic phlebotomy – This type of phlebotomy is used to treat certain health
conditions. For example – Removing blood in polycythemia helps to prevent
complications such as clotting and blood thickening. Removing blood in
hemochromatosis helps reduce excess iron which damages organs if left untreated.
 Three phases of lab tests are pre-analytical, analytical and post-analytical.
1. Pre analytical phase - comprises of al the processes from the time a lab request is
made by a physician until the specimen is analysed.
2. Analytical phase – refers to sample testing, quality control and data interpretation.
3. Postanalytical phase – refers to reporting and interpreting test reports for clinical
use.
 Pre-analytical variables are factors and conditions that can affect the quality and accuracy
of a laboratory test result before the actual analysis of the sample takes place.
 These variables are crucial because they account for a large portion of laboratory errors and
can lead to false or misleading results if not controlled.
 Pre-analytical variables can be modifiable and non-modifiable.
1. Non-modifiable variables – age, gender, race, geography of location of residence,
seasonal variations. These affect the quality of blood investigations.
 2. Modifiable variables –
a. Physiological – posture, exercise, diet, smoking, alcohol consumption,
hospitalisation.
b. Collection related – type of sample, type of analyte, use of anticoagulants,
tourniquet, endogenous interferents.
 Endogenous interferents –
o Hemolysis (Ruptured Red Blood Cells):
Cause: Hemolysis can occur due to rough handling, incorrect needle size, or
improper sample collection and storage.
 Effect on Tests: Hemolysis releases intracellular components like potassium,
lactate dehydrogenase (LDH), and hemoglobin into the sample, potentially leading
to falsely elevated results in these and other tests.
o Lipemia (High Fat Content in Blood):
 Cause: Lipemia usually results from high triglycerides, often after a patient eats a
fatty meal or in individuals with lipid metabolism disorders.
 Effect on Tests: Lipemia makes the blood sample appear milky, which can
interfere with photometric (light-based) assays by scattering light, leading to
inaccurately high or low readings, especially in tests involving spectrophotometry.
o Icterus (High Bilirubin Levels):
Cause: Icterus, or jaundice, is often due to liver disease or hemolysis and leads to
elevated bilirubin in the blood.
 Effect on Tests: High bilirubin levels cause the sample to have a yellowish tint,
which can interfere with colorimetric assays and lead to inaccurate results for tests
that measure substances in a similar spectral range as bilirubin.
o Paraproteins (Abnormal Proteins):
 Cause: Paraproteins, like those seen in multiple myeloma, are abnormal proteins
produced in certain blood disorders.
 Effect on Tests: Paraproteins can increase blood viscosity and interfere with
various assays, leading to inaccurate measurements, particularly in immunoassays
and some coagulation tests.
 Effect of posture –
1. Prolonged standing or change in position from lying to standing can affect serum
concentrations of albumin, thyroxine, triglycerides etc.
2. Lying down to standing causes increased hydrostatic pressure, decreased plasma
volume, decreased GFR and increase in concentration of bigger molecules (IgG, IgM,
IgA, albumin), increase in Ca, bilirubin, catecholamines, aldosterone, AND, renin,
enzymes (ASL, ALT, amylase).
 Effect of exercise –
1. Short term – increase in coagulation, muscle enzymes, Free fatty acids, lactate.
 2. Long term – increase in muscle enzymes, thyroxine, cortisol and decrease in
gonadotrophins, sex hormones, LDL (Low Density Lipoprotein)
 Effect of diet –
1. Vegetarians – Decreased LDL, VLDL (Very Low Density Lipoprotein)
2. Non – vegetarians – Increased urea, ammonia, uric acid.
 Effect of caffeine or alcohol – Increase in free fatty acids, catecholamines.
 Concentration of analytes –
1. It varies between choice of the sample.
2. Plasma samples have higher levels of albumin, transferrin, protein and fibrinogen.
3. Serum samples have higher levels of potassium, phosphate, lactate dehydrogenase.
4. Capillary glucose testing is a method used to measure the concentration of glucose
(sugar) in a small blood sample obtained from a capillary site, typically a fingertip or,
in infants, the heel.
5. Capillary glucose is 2 % high in plasma than in serum because serum remains after
coagulation of blood and plasma, anti-coagulants are added which influence
concentration.
 The tourniquet technique is a method used primarily in venipuncture (the process of
drawing blood from a vein) to facilitate the collection of blood samples.
 The tourniquet creates pressure on the veins, causing them to become more prominent and
easier to access for the needle insertion.
 Extended application of torniquet can cause movement of water, small molecules out of the
blood vessel (vein) leaving large molecules and bound molecules (bilirubin, Ca2+) causing
hemoconcentration.
 Preventive measures for pre-analytical errors:
1. Implementing an automated system for identifying, storing and tracking blood
samples.
2. Store and transport samples under appropriate conditions (temperature, light
protection).
3. Immediately label samples with patient identifiers, date, and time of collection.
4. Train healthcare personnel on correct venipuncture and sample collection techniques.
5. Provide clear instructions regarding fasting and medication restrictions.
 Order of draw is the sequence in which blood collection tubes should be filled during a
venipuncture procedure to prevent cross contamination of additives between tubes. It is
crucial for ensuring accurate test results.
 Sodium citrate Non additives
Blood culture
(blue cap) (red cap)

Gel seprator
EDTA (lavendar Heparin (green
tube (yellow
cap) cap)
cap)

Oxidatives,
fluorides (grey
cap)

 Analytical errors refer to those errors that occur during the testing process and culminates in
the verification and interpretation of results.
 Causes of analytical errors –
1. Incorrect calibration
2. Environmental changes in lab
3. Dilution and process of pipetting
 4. Incorrect reagents preparation
5. Improper instrument maintenance
6. Results reported when control values are out of range.
 Preventive measures for analytical errors –
1. Implementation of manuals, defining policy, procedure and process
2. Provision of clinical training and competency sample
3. Automation of instrument calibration and tracking
4. Maintain records relating to lab environment.
 Post analytical error refers to errors that occur in final stage of testing, i.e, report generation
and release.
 Causes of post analytical error –
1. Transcription errors in reporting
2. Report sent to wrong individual
3. Illegible reports
4. Results are unreported
5. Delayed turnaround time for results.
 Preventive measures for post-analytical errors–
1. Implementation of barcode system for identification
2. Automated transmission of reports
3. Develop a trouble shooting plan.

 Workflow pattern of phlebotomy in order-

1. Physicians’ advice for testing
2. Receiving patients and verifying
3. Instructions to patients
4. Barcode generation
5. Sample collection
6. Labelling vacutainers
7. Transport to lab.
 Importance of phlebotomy –
1. Diagnosis of Medical Conditions
2. Monitoring Health Status
3. Guiding Treatment Decisions
4. Research and Clinical Trials
5. Therapeutic Procedures
 Drawing blood from a patient –

Patient is seated in Pateint makes fist for

Hand hygiene correct posture with clear identification of
comfortable position nerve

The area is sterilised by Torniquet is placed 4

The needle is punctured
using alcohol cotton inches above the place of
into the vein
swab venipuncture

The syringe is lifted

The tourniquet is
towards out for vacuum Disposing used materials
removed and cotton is
effect so that blood rises properly
kept to stop bleeding
into the syringe
 QUALITY CONTROL AND LJ CHARTS

BC 14.21 Describe Quality control and identify basic L J charts in Clinical lab

Objectives :

 Explain the concept of quality control system in clinical laboratory

 Interpret quality control data based on charts such as LJ charts

 Explain the concept of accuracy and precision

 Explain the terminologies – random error and systematic error Teaching

Method: Small Group

 Automation in clinical chemistry –

1. An analytical instrument performs many tests with only minimal involvement of analyst.
2. Modern clinical laboratory uses high degree of automation.
 Importance of automation in laboratories –
1. Increase the number of tests by one person in a given period of time.
2. Minimise variations in results from one person to another.
3. Minimises errors
4. Use less sample and reagent for each test.
5. Permits the operator to focus on tasks that cannot be readily automated
6. Increases efficiency and capacity.
 Pre-analytical process includes sample identification, labelling, scheduling for analysis,
centrifugation, sample sorting, sample transport.
 Analytical phase includes spectrophotometry, reflective photometry, fluorometer,
luminometer, turbidimetry, nephrometer, infrared detection, potentiometry – concentration
selective electrodes, fluorescence polarisation immunoassay, near infrared particle
immunoassay.
 Post analytical process includes data acquisition and calculation, monitoring, display,
control, data storage, communication.
 Accuracy refers to how close a measured value is to the true or accepted value. In other
words, it indicates the correctness of a measurement.
 If a blood glucose test returns a result of 100 mg/dL, and the true value (the actual blood
glucose level) is also 100 mg/dL, the measurement is considered accurate.
 Accuracy can be assessed by comparing test results to a known standard or reference
material. In laboratory settings, quality control samples with known concentrations are often
used to evaluate accuracy.
 Precision refers to the consistency or reproducibility of measurements. It indicates how close
multiple measurements of the same sample are to each other, regardless of whether they are
close to the true value.
 If a blood glucose test is performed multiple times on the same sample and yields results of
98 mg/dL, 99 mg/dL, and 97 mg/dL, the measurements are considered precise because they
are very close to one another.
 Precision is typically evaluated using statistical measures such as the standard deviation or
coefficient of variation, which quantify the variability of repeated measurements.
 Quality in a laboratory ensures –
1. Choosing right test
2. Collecting right specimen
3. Testing by right method
4. Reporting the right based on repetitive values at right time and price
 Quality control refers to monitoring a measurement procedure to verify that results for the
patient samples meet performance specifications appropriate for patient care.
 Quality assurance refers to is a systematic process and set of activities designed to ensure
that a product, service, or system meets specified requirements and standards.
 Internal quality control –
1. For continuous and immediate monitoring of daily lab work.
2. Samples re measures at intervals along with patient samples
3. To verify that a procedure is working correctly and results for patients can be reported
4. Plans number of controls, frequency at which it is to be measured and rules to determine
if quality set are consistent with expected measurement.
 Control materials –
1. Specimens analysed for QC purposes
2. Known concentration of analyte
3. Used to validate reliability of the test system
4. Matrix similar to the test specimen.
 Norman / Gaussian distribution – is a continuous probability distribution characterized by
its bell-shaped curve.
o Symmetrical around the mean, with the highest point at the mean.
o The curve is defined by two parameters: the mean (µ) and the standard deviation (σ).
o In a normal distribution, the mean, median, and mode are all equal and located at the
centre of the distribution.
o Approximately 68% of the data falls within one standard deviation (± 1SD ).
o About 95% falls within two standard deviations (± 2SD).
o Roughly 99.7% falls within three standard deviations (± 3SD)
 Monitoring Quality control data –
o Use of control charts – plot control values each run and make decision regarding
acceptability of run.
o Monitor over time to evaluate the precision and accuracy of repeated measurements.
o Other quality control charts are – Youden plot, CUSUM chart (Cumulative Sum
Control Chart), EWMA chart (Exponentially Weighted Moving Average).
 Levey-Jennings Chart
o Record time on X – axis and control values on Y – axis.
o A horizontal line representing the average (mean) of the test results.
 Westgard rules –
o 1-2s Rule:
 Description: A single control measurement exceeds the mean by more than 2
standard deviations (SD) from the mean.
 Action: Indicates a possible systematic error; immediate investigation is warranted.

o 1-3s Rule:
 Description: A single control measurement exceeds the mean by more than 3 SD
from the mean.
 Action: Strong indication of a significant error; the test run should be rejected.
o 2-2s Rule:
 Description: Two consecutive control measurements exceed the mean by more
than 2 SD in the same direction.
 Action: Suggests a systematic error; investigate and consider rejecting the test run.

o R-4s Rule:
 Description: The range (difference) between two control measurements exceeds 4
SD.
 Action: Indicates a problem with the testing process; investigate further.

o 4-1s Rule:
  Description: Four consecutive control measurements exceed the mean by more
than 1 SD in the same direction.
 Action: Suggests a trend; investigate and take corrective action.

o 10-x Rule:
 Description: Ten consecutive control measurements fall on one side of the mean
(either above or below).
 Action: Indicates a potential bias; immediate investigation is necessary.

o Importance of Westgard Rules

 Quality Control: These rules help laboratories maintain the accuracy and
reliability of test results, ensuring that patients receive the correct diagnoses and
treatments.
 Early Detection: By applying these rules, laboratories can detect issues in the
testing process before they lead to widespread errors.
 Regulatory Compliance: Following Westgard Rules can assist laboratories in
meeting accreditation and regulatory requirements.
 External quality control –
o For periodic and retrospective monitoring of results by an independent agency.
 o Indicates the lab and its staff the accuracy or bias in their system and methods.
o Lab can know its shortcomings and change their internal quality assurance procedures.
o Procedures used to compare the performance of different labs (compared with peer lab, a
graph is obtained and awarded)
o Maintain the long-term accuracy of analytical methods.
 Standard Deviation (SD) is a statistical measure that quantifies the amount of variation or
dispersion in a set of data values.
Lab result−group mean
 Standard deviation or Z score =
Group standard deviation
 If standard deviations are –
o 0 – ideal
o Upto ± 1 – satisfactory
o ± 1 < ± 2 – likely to be unacceptable in future
o > ± 2 – system error
 Random error is defined as dispersion of independent test results obtained under specified
conditions.

 Some common causes of random errors in a lab setting:

 Sample Handling Variability: Differences in sample collection, handling, storage, or

processing, such as delays in testing or temperature fluctuations, can introduce random
error.
 Instrument Variability: Small fluctuations in lab instruments, such as slight differences
in pipette volume, reagent dispensers, or analyser settings, can cause inconsistencies in
results.
 Operator Technique: Differences in how technicians handle samples or perform tests,
even when following protocols, can lead to slight, random variations.
 Reagent Quality and Stability: Variations in the quality or stability of reagents,
especially if they are near expiration or improperly stored, can result in inconsistent
reactions and measurements.
 Environmental Factors: Temperature, humidity, and power fluctuations in the lab
environment can affect the performance of certain instruments and reagents, leading to
random errors.
 Timing Variations: Inconsistent timing during procedures, such as incubation periods or
mixing times, can introduce small but random deviations in results.
 Sample Cross-Contamination: Even minor, unintentional contamination of samples or
reagents from handling can lead to random errors, especially in highly sensitive tests.
 Systematic errors are consistent, predictable inaccuracies that occur in measurement
processes, leading to results that are consistently skewed (asymmetry in distribution of data
values) in a particular direction.
 Some common causes for systematic error –

 Calibration Issues: If lab instruments (e.g., pipettes, analyzers) are improperly

calibrated, they will consistently produce biased results, either too high or too low.
 Reagent Quality and Expiry: Using expired or degraded reagents can lead to consistent
under- or over-estimation in test results, as the chemical reactions may not occur as
expected.
 Instrument Drift: Over time, instruments may gradually lose accuracy (known as drift)
due to wear and tear, environmental conditions, or electronic changes, leading to a
systematic error if not recalibrated regularly.
 Improper Technique: If a technician consistently performs a step incorrectly (e.g.,
adding slightly too much reagent every time), it will create a systematic bias in the
results.
 Environmental Factors: Long-term shifts in lab conditions, such as sustained
temperature changes, humidity, or even consistent power fluctuations, can alter
instrument readings or reaction rates in predictable ways.
 Sample Misidentification: Consistently labelling or identifying samples incorrectly can
lead to systematic errors in patient records and diagnoses.
 Incorrect Reference Values or Standards: If the reference ranges or standards for
interpreting results are outdated, incorrect, or not regionally adapted, they can
systematically skew interpretation and diagnosis.
 Interference from External Substances: Certain medications, supplements, or
endogenous substances (e.g., hemolysis, lipemia) in patient samples can interfere with
specific assays, causing consistent over- or under-estimation in test results.

QUESTIONS

1. See the chart below, analyse and answer all the questions that follow.
 a. Identify the Westgard rule violation in the QC chart displayed above.
b. Explain the rule violation.
c. Mention few causes for random error.

2. See the chart below, analyse and answer all the questions that follow.

a. Identify the Westgard rule violation in the QC chart displayed above.

b. Explain the rule violation.
c. Mention few causes for systematic error.

3. See the chart below, analyse and answer all the questions that follow.

a. Identify the Westgard rule violation in the QC chart displayed above.

b. Explain the rule violation.
c. Define precision and accuracy.