To Test or Not to Test I: The Value of Perfect Information
2018
In this video, Professor Myriam Hunink asks students to think beyond a decision to treat or not to treat, and to consider a third alternative or option - to test and get more information. In this case, the test information is assumed to be perfect. Students are reminded of the influential factors in clinical decision making, such as the prior probability of disease, the benefits of treatment, and the harms of treatment.
Access the video. To Test or Not to Test I: The Value of Perfect Information (~15 min)
Students are prompted to consider a hypothetical patient with exertional chest pain that presents to a clinical practice. As the clinician decides whether to test or not test, they incorporate what they learn from the history and physical exam with what they know about the underlying probability of disease in similar patients, and weigh the potential benefits and risks of doing a diagnostic test.
The diagnostic test you are asked to consider is perfect but it will pose a small but real risk. Professor Hunink uses a white board mounted on a bulletin board with colored strings to geometrically display and derive the no treat-test threshold and the test-treat threshold for a test that provides perfect information.
This video is one of a series developed by Professor Myriam Hunink during an immersion residency at the Center for Health Decision Science (CHDS) Media Hub. The video series reflect experiments to augment brick and mortar teaching with multimedia materials that emphasize visualization of basic concepts.
To Test or Not to Test I: The Value of Perfect Information
Source:
To Test or Not to Test I: The Value of Perfect Information. Teaching Pack: Teaching Prototypes for Decision Analysis. Center for Health Decision Science, Harvard T.H. Chan School of Public Health 2018. https://vimeo.com/236607962