1. Biochemistry Clinical practice CLS 432 Dr. Samah Kotb Lecturer of Biochemistry 2015 Introduction to Quality Control

2. Chapter 3 Introduction to Quality Control

3. 3  At the end of this module, participants should be able to:  Define quality control and describe its relationship to the overall quality management system.  Describe differences in quantitative, qualitative, and semi-quantitative examinations. Learning Objectives

4. Quality control in the medical laboratory is a statistical process used to monitor and evaluate the analytical process that produces patient results. 4 What is Quality Control?

5. Quality control refers to the measures that must be included during each assay run to verify that the test is working properly. What is Quality Control?

6. 6 QC is examining “control” materials of known substances along with patient samples to monitor the accuracy and precision of the complete examination (analytic) process. Quality Control

7. Introduction to Quality Control-Module 67 The goal of QC is to detect errors and correct them before patients’ results are reported. Purpose of QC

8. Kinds of quality control Kinds of quality control Quality control is two kinds: a) Internal quality control, the procedure making use of results of only one laboratory for quality control. b) External quality control: in which the results of several laboratories which analyze the same sample(s) are used. 8

9. Outside laboratory Within laboratory Sample handling Patient preparation Requisition Sample receiving Sample Collection Sample Transport Patient Doctor Analysis Reports Results 9 Factors influencing internal quality

10. When a Diagnostic test is performed in the medical laboratory, the outcome of the test is a result. The result may be a patient result or it may be a quality control (QC) result.

11. The result may be quantitative (a number) or qualitative (positive or negative) or semi- quantitative (limited to a few different values).

12. 12 Measure the quantity of a particular substance in a sample Quantitative Examinations

13. 13 Examinations that do not have numerical results:  growth or no growth  positive or negative  reactive or non-reactive  color change Qualitative Examinations

14. 14 Results are expressed as an estimate of the measured substance: “trace amount”, “moderate amount,” or “1+, 2+, or 3+” number of cells per microscopic field. Titres and dilutions in serologic tests. Semi-quantitative Examination Methods

15. Two major types of errors may occur in a laboratory: 1-Random errors that arise due to inadequate control on pre-analytical variables, patient identity, sample labeling, sample collection, handling and transport, measuring devices etc. 2- Systemic errors that occur due to inadequate control on analytical variables; e.g. due to error in calibration, impure calibration material, unstable/ deteriorated calibrators, unstable reagent blanks etc. 15 Types of Errors

16. Accuracy How well a measurement agrees with an accepted value Precision How well a series of measurements agree with each other 16 Accuracy vs. Precision

17. The degree of fluctuation in the measurements is indicative of the “precision” of the assay. The closeness of measurements to the true value is indicative of the “accuracy” of the assay. Quality Control is used to monitor both the precision and the accuracy of the assay in order to provide reliable results. 17 Accuracy vs. Precision

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19. Data Quality Control Quality Assurance – Activities to ensure quality of data before data collection. Quality Control – Monitoring and maintaining the quality of data during the conduct of the study. Data Management Handling and processing of data throughout the study.

20. Data and Lab Management Safety Customer Service Patient/Client Prep Sample Collection Sample Receipt and Accessioning Sample Transport Quality Control Record Keeping Reporting Personnel Competency Test Evaluations Testing 20 The Quality Assurance Cycle QUALITY PROCESS

21. 1) Specimen 2) Collection technique 3)Storage and transportation 4) Quantity 5) Labeling 6) Mismatch of sample 21 Factors influencing quality: Pre-analytical

22. EQUIPMENT RELIABILITY REAGENTS STABILITY, INTEGRITY AND EFFICIENCY SPECIFICITY & SENSITIVITY OF SELECTED TEST PROFICIENCY OF PERSONNEL: Education, Training, USE OF APPROPRIATE CONTROLS DOCUMENTATION 22 Factors influencing quality: Analytical

23. Steps in Quality Assurance 1) Specify the study hypothesis. 2) Specify general design to test study hypothesis  Develop an overall study protocol. 3) Choose or prepare specific instruments.

24. Steps in Quality Assurance 4) Develop procedures for data collection and processing  Develop operation manuals. 5) Train staff  Certify staff. 6) User certified staff, pretest and pilot-study data collection and processing instruments and procedures.

25. Quality Assurance: Training of Staff Aim to make each staff person thoroughly familiar with procedures under his/her responsibility. Training certification of the staff member to perform a specific procedure.

26. Quality Assurance: Pretesting and Pilot testing Pretesting – Involves assessing specific procedures on a sample in order to detect major flaws. Pilot Testing – Formal rehearsal of study procedures. – Attempts to reproduce the whole flow of operations in a sample as similar as possible to study participants.

27.  If you have not documented it, you have NOT done it …  If you have not documented, it is a RUMOUR !!! Documentation

28. Data Management: Handling of Data Entering data – Use professional data entry program like EpiDataEpiData

29. Backing up vs Archiving Backing up – Everyday activity. – Purpose to able you to restore your data and documents in case of destruction or loss of data. – Not only datasets, but also command files modifying your data, written documents such as the protocol, log book and other documenting information.

30. Archiving – Takes place once or a few times during the life of the project. – Purpose is to preserve your data and documents for a more distant future, maybe to even allow other researchers access to the information.

31. 31 Important part of quality management system. Goal is to identify errors and eliminate them before reporting patient results. Different methods applied for quantitative, qualitative, and semi-quantitative results QC Summary