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- Your Instructor: Paulo Pereira, Ph.D.

- In 10 lessons, you will learn the theory, tools, and applications of selection, verification, and validation of qualitative tests


- The course will take around 40 hours, depending on the training level of the trainee.


- All materials can be downloaded, including HD videos*.

*Videos are for offline use only by the trainee, they are protected by copyright.


- Material: Video presentations (1920×1080)

- Lesson handouts

- Self-assessment quizzes

- Spreadsheets


- Terminology and vocabulary

- References


- List of abbreviations and acronyms, and


- Final exam



- This is a comprehensive exam covering all 10 lessons and comprises 40 multiple-choice questions

- The student will have three attempts to have a minimum score of 70 values

- Trial questions are chosen at random

- The test must be completed within 2 hours


Please allow 1 to 3 business days for us to review and confirm your enrollment in the course.


The course is housed on a Moodle portal.


You will receive additional emails once access has been granted and your information has been transferred over to the portal.


Course Lesson

1. Introduction to qualitative tests quality control

  • In this lesson, we introduce evidence-based medicine into laboratory logic.
  • Briefly discuss the importance of regulating in vitro diagnostic (IVD) medical devices for confidence in laboratory results.

2. Principles and guidelines

  • In this lesson, you will learn the principles behind QC.
  • We will review some of the major milestones in laboratory quality control over time.
  • Briefly discusses the importance of the dynamics of quality cycles and associated practices.
  • Introduces harmonized vocabularies to the medical laboratory.
  • Finally, discuss some of the most important QC guides.

3. ISO compliance

  • In this lesson, you will learn which ISO 15189 and ISO 9001 requirements are applicable in the QC of qualitative tests.
  • Primary introduction to ISO 15189 global guideline focused on selection, validation, and verification of qualitative med lab tests.
  • Interpretation of ISO 9001 in fulfilling technical requirements in qualitative tests.
  • Some myths associated with ISO standards and their application in the medical laboratory will be discussed.

4. Causes of uncertainty in qualitative tests

  • In this lesson, you will learn the principal sources of error that can cause untrue binary results
  • The impact of the analytical error on the cutoff trueness is discussed, as well as the effect of the analytical error on the accuracy of the classification of binary results
  • The importance of the “gray zone” and the associated trinary classification to minimize the impact of analytical error in the results is debated

5. Sampling principles

  • In this lesson, you will learn the pro and cons of sampling
  • Introduction to the epidemiological prevalence
  • Techniques for collecting statistically and clinically representative samples

6. Performance of binary classification tests

  • In this lesson, we move to the discussion and application of models for calculating the accuracy of the condition, such as diagnostic accuracy
  • We will focus on clinical sensitivity and clinical specificity
  • However, we will also discuss the physician's perspective through predictive values
  • The importance of the confidence interval will also be discussed. We explore misevaluations implications

7. Agreement of binary classification tests

  • In this lesson, we concentrate on the computation of binary results agreement
  • The determination should only occur when it is not possible to calculate the condition's accuracy
  • The misinterpretation can lead to weakly sustained decisions. For example, when referring to "clinical sensitivity" in real cases of agreement of positive results

8. Condition accuracy by analyzing numerical data

  • In this lesson, you learn the importance of delta value assessment to differentiate mainly tests with identical clinical accuracy
  • The delta value is associated with different levels of misclassification risk of binary results

9. Seronegative window period

  • In this lesson, we introduce the seroconversion window period using a binary and trinary results logic
  • Recognize the seroconversion period as a primary source of biological bias

10. Limit of detection in nucleic acid amplification tests

  • In this lesson, we introduce the evaluation of the limit of detection in nucleic acid amplification tests (NAAT).
  • The statistical models are based on logit regression, probit regression, and hit rate.

Training: Selection, verification and validation of qualitative laboratory tests

SKU: 2
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