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Quality Control: Analysis Of Data Pawan Angra MS Division of Laboratory Systems Public Health Practice Program Office Centers for Disease Control and Prevention How to carry out analysis of data? • Need tools for data management and analysis Basic statistics skills Manual methods Graph paper Calculator Computer helpful Spreadsheet • Important skills for laboratory personnel 2 Analysis of Control Materials • Need data set of at least 20 points, obtained over a 30 day period • Calculate mean, standard deviation, coefficient of variation; determine target ranges • Develop Levey-Jennings charts, plot results 3 Establishing Control Ranges • Select appropriate controls • Assay them repeatedly over time (at least 20 data points) • Make sure any procedural variation is represented: different operators, different times of day • Determine the degree of variability in the data to establish acceptable range 4 Measurement of Variability • A certain amount of variability will naturally occur when a control is tested repeatedly. • Variability is affected by operator technique, environmental conditions, and the performance characteristics of the assay method. • The goal is to differentiate between variability due to chance from that due to error. 5 Measures of Central Tendency • Data distribution- central value or a central location • Central Tendency- set of data 6 Measures of Central Tendency • Median = the central value of a data set arranged in order • Mode = the value which occurs with most frequency in a given data set • Mean = the calculated average of all the values in a given data set 7 Calculation of Median • Data set ( 30.0, 32.0, 31.5,45.5, 33.5, 32.0, 33.0, 29.0, 29.5, 31.0, 32.5, 34.5, 33.5, 31.5, 30.5, 30.0, 34.0, 32.0, 32.0, 35.0, 32.5.) mg/dL • Outlier: 45.5 • Arrange them in order ( 29.0, 29.5, 30.0, 30.0, 30.5, 31.0, 31.5, 31.5, 32.0, 32.0, 32.0, 32.0, 32.5, 32.5, 33.0, 33.5, 33.5, 34.0, 34.5, 35.0) mg/dL 8 Calculation of Mode • Data set (30.0, 32.0, 31.5, 33.5, 32.0, 33.0, 29.0, 29.5, 31.0, 32.5, 34.5, 33.5, 31.5, 30.5, 30.0, 34.0, 32.0, 32.0, 35.0, 32.5.) mg/ dL 9 Calculation of Mean • Data set (30.0, 32.0, 31.5, 33.5, 32.0, 33.0, 29.0,29.5, 31.0, 32.5, 34.5, 33.5, 31.5, 30.5, 30.0, 34.0,32.0, 32.0, 35.0, 32.5.) mg/ dL • The sum of the values (X1 + X2 + X3 … X20) divided by the number (n) of observations • The mean of these 20 observations is (639.5 20) = 32.0 mg/dL 10 Normal Distribution • All values are symmetrically distributed around the mean • Characteristic “bell-shaped” curve • Assumed for all quality control statistics 11 Normal Distribution 5 Frequency 4 3 2 1 0 29 29.5 30 30.5 31 31.5 32 32.5 33 33.5 34 34.5 35 Value Blood Urea mg/dL 12 Accuracy and Precision • “Precision” is the closeness of repeated measurements to each other. • Accuracy is the closeness of measurements to the true value. • Quality Control monitors both precision and the accuracy of the assay in order to provide reliable results. 13 Precise and inaccurate 14 Imprecise and inaccurate 15 Precise and accurate 16 Measures of Dispersion or Variability • There are several terms that describe the dispersion or variability of the data around the mean: Range Variance Standard Deviation Coefficient of Variation 17 Range • Range is the difference or spread between the highest and lowest observations. • It is the simplest measure of dispersion. • It makes no assumption about the central tendency of the data. 18 Calculation of Variance • Variance is the measure of variability about the mean. • It is calculated as the average squared deviation from the mean. the sum of the deviations from the mean, squared, divided by the number of observations (corrected for degrees of freedom) 19 Calculation of Variance (S2) S 2 ( X X ) n 1 2 mg/dl 2 20 Degrees of Freedom • Represents the number of independent comparisons that can be made among a series of observations. • The mean is calculated first, so the variance calculation has lost one degree of freedom (n-1) 21 Calculation of Variance (Urea level 1 control) 2 (X1 X ) 2 2 Variance (S ) mg/dl n 1 52.25/19 2.75mg/dl2 22 Calculation of Standard Deviation • The standard deviation (SD) is the square root of the variance -SD is the square root of the average squared deviation from the mean -SD is commonly used due to the same units as the mean and the original observations -SD is the principle calculation used to measure dispersion of results around a mean 23 Calculation of Standard Deviations Urea level 1 control s (X X) 2 i n 1 variance 24 Calculation of 1, 2 & 3 Standard Deviations 1s 2.75 1.66 mg/dl 2s 1.66 x 2 3.32 mg/dl 3s = 1.66 x 3 = 4.98 mg/dl 25 Standard Deviation and Probability Frequency X 68.2% 95.5% 99.7% -3s -2s -1s Mean +1s +2s +3s 26 Standard Deviation and Probability • For a data set of normal distribution, a value will fall within a range of: +/- 1 SD 68.2% of the time +/- 2 SD 95.5% of the time +/- 3 SD 99.7% of the time 27 Calculation of Range Urea level 1 control 68.2% confidence limit: (1SD) Mean + s = 32.0+1.66 mg/dl Mean - s = 32.0-1.66 mg/dl Range 33.66- 30.34 mg/dl 28 Calculation of Range Urea level 1 control 95. 5% confidence limit: (2SD) Mean + 2s = 32.0+3.32 mg/dl Mean - 2s = 32.0-3.32mg/dl Range 28.68 – 35.32 mg/dl 29 Calculation of Range Urea level 1 control 99. 7 % confidence limit: (3SD) Mean + 3s = 32.0+4.98 Mean - 3s = 32.0-4.98 Range 27.02 – 36.98 mg/dl 30 Standard Deviation and Probability • In general, laboratories use the +/- 2 SD criteria for the limits of the acceptable range for a test • When the QC measurement falls within that range, there is 95.5% confidence that the measurement is correct • Only 4.5% of the time will a value fall outside of that range due to chance; more likely it will be due to error 31 Coefficient of Variation • The Coefficient of Variation (CV) is the standard Deviation (SD) expressed as a percentage of the mean -Also known as Relative Standard deviation (RSD) • CV % = (SD ÷ mean) x 100 32 Summary • Data set of at least 20 points, obtained over a 30 day period • Calculate mean, standard deviation, coefficient of variation • Determine target range 33