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LABORATORY QUALITY CONTROLBy DR.P.PASUPATHI Ph.D., FLS (UK).,E-mail: drppasupathi@gmail.com : 

LABORATORY QUALITY CONTROLBy DR.P.PASUPATHI Ph.D., FLS (UK).,E-mail: drppasupathi@gmail.com

Contents : 

Contents Quality Control Quality Control Characteristics Quality Control Chart Normal Distribution Westgard rules Errors in measurement: Quality Assurance Quality Assessment

Quality Control : 

Quality Control Quality control is designed to detect, reduce, and correct deficiencies in a laboratory's internal analytical process prior to the release of patient results and improve the quality of the results reported by the laboratory. Quality control is a measure of precision or how well the measurement system reproduces the same result over time and under varying operating conditions.

Quality Control : Characteristics : 

Quality Control : Characteristics They should have the same matrix as patient specimens, including viscosity, turbidity, composition, and color. Quality control material should be simple to use. Liquid controls are more convenient than lyophilized controls because they do not have to be reconstituted minimize pipetting error. Controls should have minimal vial to vial variability, because variability could be misinterpreted as systematic error in the method or instrument. Quality control materials should be stable for long periods of time. Controls with short shelf lives necessitate frequent recording and verification against the outgoing material, creating more unnecessary work.

Quality Control : 

Quality Control Interpretation of quality control data involves both graphical and statistical methods. Quality control data is most easily visualized using a Levey-Jennings control chart.

Uses of Control charts : 

Uses of Control charts It is a proven technique for improving productivity. It prevents unnecessary process adjustments. It provides diagnostic information. It provides information about process capability.

Quality Control : 

Quality Control With a correctly operating system, repeat testing of the same control sample should produce a Gaussian distribution. That is, approximately 66% of values should fall between the +/- 1 s ranges and be evenly distributed on either side of mean. Ninety five percent of values should lie between the +/- 2 s ranges and 99% between the +/- 3 s limits.

Quality Control : 

Quality Control This means that 1 data point in 20 should fall between either of the 2 s and 3 s limits and 1 data point in 100 will fall outside the 3 s limits in a correctly operating system. In general, the +/- 2 s limits are considered to be warning limits. Values falling between 2 s and 3 s indicates the analysis should be repeated. The +/-3 s limits are rejection limits. When a value falls outside of these limits the analysis should stop, patient results held, and the test system investigated.

Slide 9: 

http://www.medicine.uiowa.edu/cme/clia/modules.asp?testID=17

Westgard rules : 

Westgard rules The formulation of Westgard rules were based on statistical methods. Westgard rules are commonly used to analyse data in Shewhart control charts. Westgard rules are used to define specific performance limits for a particular assay and can be use to detect both random and systematic errors. Westgard rules are programmed in to automated analyzers to determine when an analytical run should be rejected. These rules need to be applied carefully so that true errors are detected while false rejections are minimized. The rules applied to high volume chemistry and hematology instruments should produce low false rejection rates.

Warning rules: : 

Warning rules: Warning 12SD : It is violated if the IQC value exceeds the mean by 2SD. It is an event likely to occur normally in less than 5% of cases. Warning 22SD : It detects systematic errors and is violated when two consecutive IQC values exceed the mean on the same side of the mean by 2SD. Warning 41SD : It is violated if four consecutive IQC values exceed the same limit (mean  1SD) and this may indicate the need to perform instrument maintenance or reagent calibration.

In the original Westgard multirule QC procedure, this rule is used as a warning rule : 

In the original Westgard multirule QC procedure, this rule is used as a warning rule

22s - reject when 2 consecutive control measurements exceed the same mean plus 2s or the same mean minus 2s control limit. : 

22s - reject when 2 consecutive control measurements exceed the same mean plus 2s or the same mean minus 2s control limit.

41s - reject when 4 consecutive control measurements exceed the same mean plus 1s or the same mean minus 1s control limit. : 

41s - reject when 4 consecutive control measurements exceed the same mean plus 1s or the same mean minus 1s control limit.

A run is rejected when a single control measurement exceeds the mean plus 3s or the mean minus 3s control limit. : 

A run is rejected when a single control measurement exceeds the mean plus 3s or the mean minus 3s control limit.

10x violation : 

10x violation

Variables that affect the quality of results: : 

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.

TYPES OF ERRORRandom Error : 

TYPES OF ERRORRandom 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.

Random Errors : 

Random Errors

Systematic Error : 

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.

Systematic Errors : 

Systematic Errors

Slide 22: 

http://www.medicine.uiowa.edu/cme/clia/modules.asp?testID=17

Slide 23: 

http://www.medicine.uiowa.edu/cme/clia/modules.asp?testID=17 http://www.medicine.uiowa.edu/cme/clia/modules.asp?testID=17

Quality Assurance : 

Quality Assurance Quality Assurance - QA is defined as the overall program that ensures that the final results reported by the laboratory are correct. “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”

Quality Assessment : 

Quality Assessment Quality Assessment - quality assessment (also known as proficiency testing) is a means to determine the quality of the results generated by the laboratory. Quality assessment is a challenge to the effectiveness of the QA and QC programs. Quality Assessment may be external or internal, examples of external programs include NEQAS, HKMTA, and Q-probes.

THANK YOU : 

THANK YOU

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