This document is a lecture on quality control for paramedical students. It defines key terms like specificity, sensitivity, and bias. Specificity refers to a test that measures only the intended analyte. Sensitivity indicates a test's ability to detect small concentrations. Bias is a systematic error in data collection. The lecture also discusses quality assessment, including pre-analytical, analytical, and post-analytical factors. Statistical calculations like mean, standard deviation, and coefficient of variation are explained. Quality control charts like the Levey Jennings chart are introduced to monitor accuracy and precision. Finally, systematic and random errors are distinguished.

1. Dr. Vishnu Kumar
Professor, Department of
Biochemistry, SRMSIMS, Bareilly
vkawasthi@hotmail.com
madhwapur1976@gmail.com
QUALITY CONTROL
(Second Lecture)

2. Recap of First Lecture of Quality Control
for Paramedical Students
In my first lecture of Quality Control I had
explained to you about Quality, Quality Control
Definitions, External Quality Control, Internal
Quality control, Accuracy, precision, shift and
trend error. Today in Lecture 2 on Quality
Control I will explain rest part of this topic.

3. Learning Objectives
After completion of this second
lecture of Quality Control learner
should be able to define:
 Specificity
 Sensitivity
 BIAS
 L J Chart
 Systematic and Random Error

4. SPECIFICITY`
• To determine solely the analyte proposed to be
measured. It denotes that only one substance
will answer the particular test. For example 
glucose oxidase method is specific for glucose.
If the reducing property of glucose is used for
the assay purpose (Nelson Somogyi), other
reducing agents in the blood will interfere,
hence the specificity is lowered. It is
determined by the method of analysis.

5. SENSITIVITY
• Indicates the ability of the method to detect
very small concentration of the measured
analyte. For example Biuret method is used
for solutions having a few g% of protein,
spectrophotometric method is used to detect a
few mg% of protein, where as ELISA method
is employed for solutions having a few µg %
of protein. So ELISA method is the most
sensitive.

6. BIAS
• Systematic error in collecting or interpreting
data, such that there is under estimation or
over estimation, or another form of deviation
of results. Bias may result from flaws in study
design, measurement, data collection, or the
analysis or interpretation of results.

7. QUALITY ASSESMENT
• The assurance of high quality laboratory results relies
on a commitment to all aspects of the testing system,
including attention to pre analytical, analytical and
post analytical factors.
• Pre analytical factors are those that affect laboratory
results due to handling of the specimen sample prior
to analysis (haemolysis, intake of food before
analysis, serum, plasma or whole blood, use of
tourniquet, specimen contamination, use of wrong
additives.)

8. QUALITY ASSESMENT contd.
• The analytical phase includes verification of
instrument linearity, precision, accuracy, sensitivity,
and overall reliability through the use of standard
materials, quality control samples.
• Post analytical phase includes reporting the patient
result in a timely manner and in an accepted format,
maintaining and monitoring records of patient results,
and using reference ranges and critical values.

9. STATISTICAL CALCULATION
• Mean (X) sum of observations (x¹,x², x³---
xi) divided by number (n) of observations. §x /
n = X.
• Standard deviation (SD) It is the measure of
the dispersion of a group of values around the
mean. It is used to asses precision.
• Coefficient of variation (% CV )= SD/ mean ×
100.

10. LEVEY JENNINGS CHART
• A simple graphical display in which the
observed values are plotted versus an accepted
range values. If the analytical methods are
operating properly the values will fall within
the control limits. When an accuracy problem
exists the values in a row may fall outside one
limit. When precision problem exists the
values may exceed both the upper and lower
limits.` .LOI09789-2

11. Systematic and random error
• Systematic errors are always of the same sign
and magnitude and produces biases.
It may be constant or proportional. Several
may exist at the same time. Shifts and Trends
are types of systematic error.
• Random errors are unpredictable.