The Importance of Conditional Probability in Diagnostic Reasoning and Clinical Decision Making: A Primer for the Eye Care Practitioner

ABSTRACT

Purpose: To outline and detail the importance of conditional probability in clinical decision making and discuss the various diagnostic measures eye care practitioners should be aware of in order to improve the scope of their clinical practice.

Methods: We conducted a review of the importance of conditional probability in diagnostic testing for the eye care practitioner.

Results: Eye care practitioners use diagnostic tests on a daily basis to assist in clinical decision making and optimizing patient care and management. These tests provide probabilistic information that can enable the clinician to increase (or decrease) their level of certainty about the presence of a particular condition. While an understanding of the characteristics of diagnostic tests are essential to facilitate proper interpretation of test results and disease risk, many practitioners either confuse or misinterpret these measures.

Conclusions: In the interests of their patients, practitioners should be aware of the basic concepts associated with diagnostic testing and the simple mathematical rule that underpins them. Importantly, the practitioner needs to recognize that the prevalence of a disease in the population greatly determines the clinical value of a diagnostic test.

KEYWORDS:

• Bayes theorem
• conditional probabilit
• diagnostic test

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the writing and content of this article.

Funding

The Centre for Eye Research Australia receives Operational Infrastructure Support from the Victorian Government. PGS is supported by a National Health and Medical Research Council (NHMRC) Early Career Fellowship.