QUALITY CONTROL Flashcards
A DEGREE TO WHICH A SET OF INHERENT CHARACTERISTICS FULFILLS REQUIREMENTS (ISO 9001:2008)
QUALITY
PART OF QUALITY MANAGEMENT FOCUSED ON FULFILLING QUALITY REQUIREMENTS (ISO 9000:2000)
QUALITY CONTROL
WHAT IS THE OTHER NAME OF QUALITY CONTROL
STATISTICAL PROCESS CONTROL
SYSTEM OF ASSURING THE QUALITY OF TOTAL LABORATORY PERFORMANCE
QUALITY CONTROL
INVOLVES SYTEMATIC MONITORING OF ANALYTIC PROCESS IN ORDER TO DETECT ANALYTIC ERRORS THAT OCCUR DURING ANALYSIS
QUALITY CONTROL
PART OF QUALITY MANAGEMENT FOCUSED ON PROVIDING CONFIDENCE THAT THE QUALITY REQUIREMENTS WILL BE FULFILLED (ISO 9000:2000)
QUALITY ASSURANCE
MONITORING OF SPECIMEN AQISISIO, TURN AROUND TIME, OR PROFICIENCY TESTING OF MATERALS
QUALITY ASSURANCE
SET OF ACTIVITIES OR PLAN THAT AIMS TO MAINTAIN THE HIGHEST DEGREE OF EXCELLENCE FOR TH DIAGNOSIS AND TREATMEN OF DISEASE AND MAINTENANCE OF HEALTH
QUALITY ASSURANCE PROGRAM
Specifies requirements for a quality management system where an organization needs to demonstrate its ability to consistently provide product that meets costumer and applicable situations
ISO 9001 : 2008
Quality management in medical Laboratories (guidelines
ISO15189
SYSTEM CONCEPTS of QUALITY CONTROL
- QCCS- Quality Control Surveillance System
- Q.C. Corrective System
- Objective Q.C. Parameters
establishes norms that must be met
QCCS
Established to offer education of why errors occur; provide a program to remedy defects
Q.C. Corrective System
Established to prove that corrective measures have produced favorable results
Objective Q.C. Parameters
Objectives of Q.C.
- check the quality of machines
- check the quality of reagents
- check technical (operational) errors
Initially applied and principle statistically analyzing QC to the clinical lab in the1950s
Control Limits ( Control Values)
ideal control limit
+/- 2SD
A substace of known concentration
Standard
More applicable to identifying when an error has occured
Quality control
more applicable to preventng an error from occuring
Quality Assurance Program
CONTROL of PRE-ANALYTICAL VARIABLES
FACTORS:
- Patient identification
- Proper preparation of patient
- Specimen collection, separation & processing
CONTROL OF ANALYTICAL VARIABLES
MAIN FACTORS:
- Choice of analytical methodology
- Calibration procedures
- Proper documentation of analytical variables
- Proper labeling & use of reagents
- Preventive maintenance of analytical instruments
- Periodic calibration of pipetting devices
- Periodic checking of °T of refrigerator & heating units
- Periodic checking of procedure manuals
- Monitoring of technical competence
- Inventory of control materials
- Control assurance that safety measures are operational
CONTROL of POST-ANALYTICAL VARIABLES
FACTORS:
- Verification of calculations of the final results
- Check test results for possible transcription errors
- Results should be easy to read & interpret
- Timeliness of reporting values to patient chart
- Procedures for informing physicians about results that require immediate attention
FACTORS Involved in QUALITY CONTROL
- standard
- control material
Substance of known composistion
Standard
Its valu is established by an analytical procedure different from that used in the clinical laboratory
Standard
Substance which resembles the unknown specimen (patient’s sample)
Control material
analyzed daily together with the unknown
Control material
the values obtained from the assays are used for that computation of the mean and the SD
Control material
types of control material
A. Commercial control sera
B. Pooled sera
Excess non-hemolyzed sera without gross lipemia are collected daily in the laboratory and
pooled for storage in the refrigerator
Pooled sera
- When 1 – 2 liters are collected, centrifuge to remove gross contamination
- Filter and divide into aliquots of 5 mL each
Pooled sera
-
Stopper and store at -20°C
-
Thaw as needed and mix well before use
Pooled sera
extent to w/c the measurement approximates the true value of the quantity being
measured
Accuracy
a.k.a reproducibility; degree to w/c repeated results agree to each other
Precision
ability of a method to detect a particular substance w/o the interference of some
other substances present in the sample
Specificity
ability of a method to detect even the smallest amount of that particular substance
tested for
Sensitivity
ability of a method to maintain its accuracy & precision over an extended period of
time
Reliability
degree to w/c the method is easily repeated
Practicability
➢ A statement of the extent of random variation in any series of measurement
➢ A measure of the distribution of values around the mean
Standard Deviation
- Square of the standard deviation
- Used to detect significant differences between groups of data
- Determine contributions of various factors to the total variation
Variance
- Percentile expression of the mean
- Measure of the relative magnitude of variability
Coefficient of variation
QUALITY CONTROL Associated Activities
- Assay of control samples
- Instrument maintenance
- Statistical Data Analysis
- Proficiency testing survey
Aspects which the laboratory should avoid or minimize
- Analytical Balance
- Random Analytical Variability
- Errors
Types of Analytical Bias
a) Proportional bias
b) Constant bias
c) Combined bias
❖ Reported values do not fall along the line of slope when graphed
❖ Reported lab results do not correspond to the correct value
Analytical Balance
- Refers to laboratory analyses that are subject to imprecision
Random Analytical Variability
Types of random analytical variability
A. Proportional variability
B. Constant variability
Problem on Accuracy (Bias)
Systematic Error
Problem on Precision (CV)
Random Error
can be systematic or personnel-related
Errors
Types of error
A. Random Errors
B. Systematic Errors
Sources cannot be completely controlled or identified
Increase the extent of variability of results
Random Errors
Causes of random errors
- Pipets & volumetric glassware w/ manufacturing variation; electronic & optical variations in
instruments (e.g. spectrophotometers) - Variations in the cuvet
- Variations in timing & °T control
- Variations in light, evaporation & °T on serum sample
- Interferences from other substances in the sample
Displace the mean value on one direction (may be up or down), but do NOT affect the overall
variability as shown by the SD value
Systematic Errors
Causes of systematic errors
- Aging phenomena – decomposition of reagents during storage
- Personal bias of the analyst
- Laboratory bias
- Inter- & intra-individual bias
- Experimental errors or changes in the methods
Types of systematic errors
- Trend
- Shift
CAUSES of UPWARD TREND:
o Expired lamps/photocells
o Denatured standard
o Contamination of reagents
CAUSES of DOWNWARD TREND
o Standards that are too concentrated
o Contamination of reagent
Series of values on the control chart that continue to increase or decrease for at least a
period of six (6) consecutive days
Trend
Values that distribute themselves on one side of the mean for at least six (6)
consecutive days
Shift
CAUSES of DOWNWARD SHIFT
o Increased concentration of standard & reagents
o Contaminated reagents
o Inaccurate timer
o Under-heating in analysis
o Contaminated glassware
CAUSES of UPWARD SHIFT
o Partial electrical failure in instrument
o New standard is over-diluted
o Denatured standard that has stabilized
o Improperly prepared reagent
o Inaccurate timer
o Deteriorated indicator
o Dirty glassware
o Overheating in °T-sensitive analysis
Q.C. procedures performed on a daily basis within individual laboratories
INTRALABORATORY / INTERNAL
INTRALABORATORY / INTERNAL Monitoring is carried out using
o Levey – Jennings Chart
o Westgard Multi-rule Chart
o CUSUM Technique (cumulative sum)
Performed on a less frequent basis (e.g. 3x a year) to compare performance b/w or among
laboratories
INTERLABORATORY / EXTERNAL
graphical representations that display the control observation as a
function or time
quality control charts
Control results are plotted on the Y-axis (ordinate) vs time on the X-axis (abscissa)
LEVEY – JENNINGS CHART
All control values are w/in ± 2SD
One outlier in 20 determinations
IN-CONTROL
Presence of two or more outliers
Presence of a Trend
Presence of a Shift
OUT-OF-CONTROL
a control value that goes beyond ±2SD
Outlier
Commercial control sera is reconsituted using
5mL of distilled H2O
dehydrated to powder
Lyophilized
Pathologic control and color red packaging
Quantipath
Green
Quantiform
3 types of studies determined by:
A. Recovery study
B. Interference study
C. Sample comparison
determines how much of the analytes can be identified in the sample
Recovery study
specific compounds affect the lab test
interference study
used to assess the presence of error in an actual patient sample
Sample comparison study
what is caused by systematic error
Inaccuracy
what is caused by random error
imprecision
measure of central tendency associated with symmetrical or normal distribution
arithmetic mean
Characteristics of a human sample
- resembles human sample
- inexpensive and stable for long periods
- no communicable disease
- no matrix effects/ known matrix effects
- with known analyte concentration
- convenient packaging for easy dispersion and storage
reported values are higher/ lower than the expected values
proportional bias
reported values are higher/ lower than expected but constant concentration
constant bias
commonly caused by a bias in volumetric dispensing of the specimen aliquot
proportonal variability
commonly observed in analytical procedures that are influenced by the turbidity of the specimen
constant variability
to prove there is proportional bias
recovery experiment
causes of outlier
- contamination of a single specimen
- faulty pipette
- incorrect dilution of test
- incorrect control sera
if value is only one but exceeded +/- 2SD
1,2 s
- method used to validate a particular measurement process
- diff. labs analyze the same sample several times in a year
proficiency testing survey
specimens that have known concentration of an analyte for the test of interest
proficiency sample
labs in a geographic region use the lots of QC specimen each day for their internal QC programs
Regional QC programs
steps in implementing quantitative QC
- obtain control material
- run each control 20 times over 30 days
- calculate mean +/- 1,2,3 SD
preferred rather than a pooled sera
Bovine QM
