Pakistan Society of Chemical Pathologists Zoom Series of Lectures ZT 25. Quality Management 2 Brig Aamir Ijaz MCPS, FCPS, FRCP (Edin), MCPS-HPE HOD and Professor Chemical Pathology AFIP Rawalpindi

Specific Learning Outcome At the end of this lecture the students will be able to describe the processes involved in Quality Management.

Laboratory Errors

Types of Lab Errors Pre-analytical Random Errors Systematic Errors Trend Shift Analytical Post-analytical

Random Error Imprecision of the test system causing a scatter or spread of control values around the mean

D. Fluctuation in power supply MCQ No 4 Which of the following is mostly a cause of Random Error? Change in reagent or calibrator lot numbers Deterioration of reagents or calibrators Fluctuation in power supply Improperly prepared reagents Wrong calibrator values D. Fluctuation in power supply

Causes of Random Error Air bubbles in reagent Improperly mixed reagents Faut in reagent lines, sampling, or reagent syringes Improperly fitting pipette tips Clogged or imprecise pipetter Fluctuations in power supply

Systematic Error Systematic change in the test system resulting in a displacement of the mean from the original value Systematic error of an analytic system is predictable and causes shifts or trends on control charts that are consistently low or high

Causes of Systematic Error Change in reagent or calibrator lot numbers Wrong calibrator values Improperly prepared reagents Deterioration of reagents or calibrators Inappropriate storage of reagents or calibrators Variation in sample or reagent volumes due to pipettor misalignments Variation in temperature or reaction chambers Deterioration of photometric light source Variation in procedure between technologists

Accuracy and Precision The degree of fluctuation in the measurements is indicative of the precision of the assay. Precision-refers to the ability to get the same (but not necessarily ‘true’) result time after time. The closeness of measurements to the true value is indicative of the accuracy of the assay. Accuracy - An accurate result is one that is the ‘true’ result.

What this Diagram Indicates?

Accuracy and Precision Precise and inaccurate Imprecise and inaccurate Random Error Systematic Error

Shifts and Trends Shift QC data results are distributed on one side of the mean for 6-7 consecutive days Trend Consistent increase or decrease of QC data points over a period of 6-7 days

Bias Bias – the amount by which an analysis varies from the correct result. Example, If the Expected Value is 50 units, and the result of an analysis is 47, the bias is 3 units.

Westgard Multirule System Multi-rule system developed by Dr. James O. Westgard based on statistical concepts Combination of decision criteria or rules to assess if a system is in control Used when at least 2 levels of control are run with the examination run Cannot be used with only one control Dr. Westgard 8-5 16

12s Rule 12s refers to the control rule that is commonly used with a Levey-Jennings chart when the control limits are set as the mean plus/minus 2s. In the original Westgard multirule QC procedure, this rule is used as a warning rule to trigger careful inspection of the control data by the following rejection rules.

13s Rule 13s refers to a control rule that is commonly used with a Levey-Jennings chart when the control limits are set as the mean plus 3s and the mean minus 3s. A run is rejected when a single control measurement exceeds the mean plus 3s or the mean minus 3s control limit.

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

R4s Rule R4s - reject when 1 control measurement in a group exceeds the mean plus 2s and another exceeds the mean minus 2s.

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

10X Rule 10x - reject when 10 consecutive control measurements fall on one side of the mean.

Task No 2 Identify the rule at: 3,4,7,9,10,11,12,14,20 Name type of error High: mean=250 and s=5) Low: mean=200 and s=4

Run 3 Both control results exceed their respective +2s limits, therefore there is a 22s rule violation across materials. A systematic error is most likely occurring and is affecting the results throughout the critical analytical range from at least 200 to 250 mg/dL.

Run 4 The high control result is below its -2s limit, which is a warning of a possible problem. Inspection with the 13s, 22s, and R4s rejection rules that can be applied within the run do not confirm a problem. Note that the across-runs rules would not be applied because the previous run was rejected.

Run 7 a. The high control result exceeds its +3s limit, therefore there is a 13s control rule violation. b. This most likely indicates random error.

Run 9 The high control result is below its -2s limit. Inspection of the control results by the rejection rules does not confirm a problem.

Run 10 The control chart for the high control material shows that the last two measurements have both exceeded the -2s limit, therefore a 22s rule violation has occurred within material and across runs. This situation would be consistent with a loss of linearity that is beginning to affect the high end of the analytical range.

Run 11 There is a 12s warning on the high level control material, but inspection doesn't show any other rule violations, therefore, the patient test results in this run can be reported.

Run 12 The control charts for the high and low materials show that the last four control observations have exceeded their respective +1s limits, therefore a 41s rule violation appears to have occurred across materials and across runs.

Run 14 The control results for the high material exceeds its +2s limit and the control result for the low material exceeds its -2s limit, therefore an R4s rule violation has occurred. This most likely indicates a random error.

Run 20 The last five control results on the high material and the last five results on the low material all are lower than their respective means, giving a total of ten consecutive control results on one side of the mean. There is a 10x rule violation across runs and across materials It indicates that a systematic error most likely has occurred.

Summary of Westgard System

MCQ No 3 In a tertiary care hospital a Consultant Chemical Pathologist has joined the department after getting training from Japan. He launches a new programme for a marked reduction of the lab errors and sets a target of < 3.4 errors per million. Which of the following QM procedure he is trying to introduce in his lab: Delta Check External Quality Assurance Internal Quality Control Quality Planning Six Sigma E. Six Sigma

MCQ No 4 Six Sigma Matrix are commonly used in Medical Field to assess overall quality programme. Following is a list of error logs of various laboratories in terms of Six Sigma. Which lab is performing the best:  Lab No. 1 is 3.5 Lab No. 2 is 5.8 Lab No. 3 is 2.2 Lab No. 4 is 3.9 Lab No. 5 is 4.7 B. Lab No. 2 is 5.8

MCQ No 5 D. Lean Management Which of the following quality processes is integrated with Six Sigma to enhance efficiency and quality of lab work: Delta Check Human Resource Management Laboratory Certification Lean Management Proficiency Testing D. Lean Management

Six Sigma Companies 1980 First developed by Motorola Company - Adapted six sigma strategy After 4 years saved $2.2 billion Improved elimination of wastes and reruns Jack Welch made it a central focus of his business strategy at General Electric – 1995 Sony American Express Today it is used in different sectors of industry

Why It Is Called So? Sigma is the Greek letter representing the standard deviation of a population of data Sigma is a measure of variation (the data spread) σ μ

What Does Variation Mean? Variation means that a process does not produce the same result every time Some variation will exist in all processes Variation directly affects customer experiences

The pizza delivery example . . Customers want their pizza delivered fast! Guarantee = “30 minutes or less” We measured performance and found an average delivery time of 23.5 minutes? On-time performance is great, right? Our customers must be happy with us, right?

how often are we delivering on time? answer: look at the variation! 30 min. or less Managing by the average doesn’t tell the whole story. The average and the variation together show what’s happening. s x 10 20 30 40 50

Introduction to six sigma Statistical measure of quality Based on rigorous process based performance Process for continuous improvement To improve process in any business Changes ways of thinking Creates a special infrastructure of people within the organization Defects per million 1 million =1000,000

Relating sigma to defect levels DPMO (Defects per million opportunities) Error free rate Six sigma 3.4 99.9997% Five sigma 233 99.977% Four sigma 6210 99.4% Three sigma 66810 93% Two sigma 308500 69% One sigma 691500 31%

In short Processes that operate with "six sigma quality" over the short term are assumed to produce long-term defect levels below 3.4 defects per million opportunities

Six Sigma And Clinical Laboratories Higher sigma values indicate better performance Lower values indicate a greater number of defects per unit Quality is assessed on the σ scale with a criterion of 3 σ as the minimum allowable sigma for routine performance and a sigma of 6 being the goal for world-class quality

Six Sigma And Clinical Laboratories Laboratory performance can be appraised with the application of six sigma in laboratory functions When the method sigma is ≥6, stringent internal QC rules need not be adopted In such cases, false rejections can be minimized by relaxing control limits up to 3s A method sigma below 3 calls for the adoption of a newer and better method as quality of the test cannot be assured even after repeated QC runs

Six Sigma And Clinical Laboratories Any lab process can be evaluated in terms of a sigma metric Describes how many sigma fit within the tolerance limits For laboratory measurements, the sigma performance of a method can be formulated

Thanks and Best of Luck