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HIV Testing Quality Assurance and Quality Control

HIV Testing Quality Assurance and Quality Control

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HIV Testing Quality Assurance and Quality Control

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  1. HIV Testing Quality Assurance and Quality Control Eligius Lyamuya MD, MMed, PhD Department of Microbiology and Immunology Muhimbili University of Health and Allied Sciences

  2. Disposition • HIV Diagnosis • HIV Testing techniques • Tests • Strategies • Algorithms • Quality Issues • Quality management • QC • QA • Quality improvement • Quality system

  3. HIV Diagnosis

  4. Requirements for Laboratory diagnosis of HIV infection • Standard Laboratory facility • Suitable physical structure • Well equipped with essential facilities • Human resources • Well trained • Adequate number • Test kits • Acceptable quality • Constant supply • Financial resources • Quality management

  5. Diagnosis of HIV/AIDS • Clinical criteria • WHO and CDC criteria • Laboratory Techniques • Isolation of the virus in culture • Detection of viral antigens e.g. p24 ag • Detection of viral nucleic acid by polymerase chain reaction (PCR) • Detection of specific antibody to HIV antigens

  6. HIV Testing Techniques

  7. HIV testing Campaign in Tanzania 31/10/2014 7

  8. HIV Testing • Antibody tests • Enzyme-Linked Immunosorbent Assays (EIA) • Western Blot • Rapid tests • Antigen tests • EIA P24 tests • Nucleic acid detection by Polymerase Chain Reaction (PCR)

  9. Time from Infection to Detection of HIV-1 Markers NO DETECTION KEY: EARLIEST POSSIBLE DETECTION OF HIV Antibody assays p24 DNA PCR RNA PCR 5 15 20 25 30 35 10 Detection of HIV: Days after infection

  10. HIV diagnosis in Adults and Children >18 months • Antibody-based tests (detection) • Most commonly used assays: • ELISA • Rapid Tests • Western Blot

  11. HIV Diagnosis in Children <18 months • Antibody detection cannot be used due to presence of maternal antibodies • p24 antigen detection test is used • HIV nucleic acid (DNA or RNA) detection by PCR

  12. HIV Testing - ELISA • Quantitative assay to measure HIV antibodies • Some assays can detect both HIV antibody and HIV antigen (reduce window period) • Issues: • Skilled lab technician • Availability of reader, washer, incubator • Properly maintained equipment required • Power • Ideal for large volume testing

  13. HIV Testing – Rapid Tests • Qualitative assays to detect HIV antibodies • Most detect both HIV 1 and HIV 2 • As reliable as ELISA • Provide same-day results • Do not require additional equipment • Issues: • Small volumes • Validation of use • Appropriate training

  14. Testing Strategies • Testing approach used to meet a specific need, such as: • Blood Safety • Surveillance • Diagnosis

  15. WHO HIV Testing Strategies: Criteria • Criteria for choosing HIV testing strategy • Test objective: surveillance, blood screening, diagnosis • Sensitivity and specificity of the test(s) • HIV prevalence in the population NB: The HIV test strategy must be validated for use by each country

  16. WHO HIV Testing Strategies-1 • Strategy I • Requires one test • For diagnosis where prevalence among persons with clinical signs is >30% • For surveillance where HIV prevalence is >10%

  17. WHO HIV Testing Strategies-2 • Strategy II • Requires up to two tests • For diagnosis where prevalence among persons with clinical signs is 30% or >10% among asymptomatic persons • For surveillance where HIV prevalence is 10%

  18. WHO HIV Testing Strategies-3 • Strategy III • Requires up to three tests • For diagnosis where prevalence among asymptomatic is 10%

  19. HIV Testing Strategies • Serial testing • Samples tested by a first test • Result of first test determines whether additional testing is required • Parallel testing • Samples are tested simultaneously by two different tests

  20. Testing Algorithm • The combination and sequence of specific tests used in a given strategy • An HIV Positive status is based upon the outcome of 2 or more tests • When two test results disagree (one is reactive, the other non-reactive), the finding is called “indeterminate.” In this case, a third test (tie- breaker) must be performed

  21. HIV testing algorithms • EIA screen followed by Western blot confirmation • Multiple EIAs screen and confirmation • Multiple rapid tests screen and confirmation UNAIDS, WHO and CDC have recommended and set guidelines for the use of HIV tests in screening and confirmatory algorithms

  22. Current National HIV Rapid Testing Algorithm Blood Sample Bioline Non-reactive Result Report: Negative Reactive Result Determine Reactive Result Report: Positive Non-reactive Result Unigold Reactive Result Report: Positive Non-reactive Result Report: Negative

  23. Quality Issues

  24. Laboratory quality management • All activities of the overall management function that determine quality policy objectives and implement them within a system • Components: • quality control • quality assurance • quality improvement

  25. Quality Control-1 • Operational techniques and activities used fulfill requirements for quality • Internal QC: set of procedures for continuously assessing laboratory work and emergent results • running “QC” samples • reading the “control” line • evaluating signal to cutoff ratios for QC samples • having another technologist review test interpretations, calculations, etc

  26. Quality Control-2 • External QC: of evaluating the performance of a laboratory in testing samples sent by an external laboratory • running proficiency testing samples • retesting a proportion of samples

  27. Quality Assurance • A dynamic and ongoing process of monitoring a system for reliability and reproducibility of results that permits corrective action when established criteria are not met • Takes into consideration pre-analytical, analytical and post-analytical phases

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

  29. QA: Pre-analytic • Select the best test and testing strategy • which test • what algorithm • which laboratories • Assess testing services before starting testing • Designate responsibilities and make clear the decision making process • Make sure each testing site has reagents and supplies • Have standard operating procedures in place (SOPs)

  30. QA: Analytic • Provide every testing site with instructions and training for: • laboratory safety • sample receipt (sample assessment and rejection criteria, logging-in process and forms) • sample storing • how to do testing • how to perform internal QC and external QA and/or proficiency testing • how to monitor other testing parameters (e.g., strength of signal for a QC sample) • Perform competency checks of laboratory personnel who manage samples and do testing • on-site audits • competency evaluation panels • review recent proficiency testing data

  31. QA: Post-testing • Set up a process for evaluating test results and QC indicators before releasing test results • Establish corrective actions to take when indicators are of control indicators • Establish a review process to assure accurate results transcription and reporting • Store samples properly for retesting and/or referral

  32. Quality Improvement • Determination of causes or sources of problems identified by QC and QA

  33. Quality System • Organizational structure, resources, processes and procedures needed to implement quality management

  34. Quality System Essentials • Organization • Personnel • Equipment • Purchasing and inventory • Process control • Information management • Documents and Records • Occurrence management • Internal assessment • Process improvement • Service and satisfaction • Facilities and safety

  35. Quality System Quality Assurance Quality Control

  36. Take Home Messages • Not paying attention to QA is like starting a journey without knowing how to drive, without doing routine maintenance and without adding fuel • If QA and QC is done correctly, troubleshooting will be a rare event and easy to do • Laboratories without QC never make mistakes, because they never detect them • Even simple tests, require some QA • The fewer the steps in a process the simpler the QA.