Positive Predictive Value and Negative Predictive Value

Positive Predictive Value:

Proportion of positive test results that are TRUE positive. Probability that person actually has the disease given a positive test result.

NOTE: if the prevalence of a disease in a population is low , even tests with high specificity or high sensitivity will have LOW positive predictive value.


Negative Predictive Value:

Proportion of negative test results that are true negative. Probability that person actually is disease free given negative test result.



We’ve covered test characteristics like sensitivity and specificity before, and we’ve even covered how you can use those values to make decisions about what results mean about your health. But sensitivity and specificity don’t have a meaning that people usually understand.

What people want to know are other values, what we might call the positive predictive value and negative predictive values. But there are problems with those metrics. They’re the topic of this week’s Healthcare Triage.

For those of you who want to read more, go here: http://theincidentaleconomist.com/wordpress/?p=63074

Housekeeping first:
1) You can support Healthcare Triage on Patreon: http://vid.io/xqXr Every little bit helps make the show better!
2) Check out our Facebook page: http://goo.gl/LnOq5z


John Green — Executive Producer
Stan Muller — Director, Producer
Aaron Carroll — Writer
Mark Olsen — Graphics


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