Accuracy of clinical testing and interpretation of results

Research output: Contribution to journalArticlepeer-review


Objective: The purpose of this paper is to highlight the difficulties encountered by both the patient and doctor when interpreting the results of clinical tests.

Design: It is well documented that patients who have been given the news of a diagnostic test that suggests a very poor or even terminal diagnosis become quite emotional. A common question is wanting to know how much longer they have to live and what their quality of life will be. But what if the test results are incorrect? How should they be properly interpreted by the medical practitioner? What are the chances they are wrong? These aspects are uncovered by means of statistical models using various case studies.

Materials and Methods: Statistical models are provided to better understand and interpret the results of diagnostic tests.

Results: In the case of diagnostic testing, additional tests can be conducted with further evidence of a patient having or not having a disease becomes available, with the posterior odds being further updated in the process. The more information that can be obtained, the less chance there is of a calamity.

Conclusion: It is essential that medical practitioners understand what it means for a clinical test to have a certain specificity and sensitivity. Being aware of the ramifications of misinterpreting a test result can have on a patient and providing more accurate information can lead to better patient satisfaction all around.
Original languageEnglish
Pages (from-to)346-348
Number of pages3
JournalInternational Medical Journal
Issue number3
Publication statusPublished - Jun 2020


  • Bayes theorem
  • conditional probability
  • diagnostic testing
  • sensitivity
  • specificity


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