How to Model Risk and Cost of False Laboratory Tests

Use the interactive risk calculator to model the risk and cost of false laboratory tests based on the prevalence of true positive samples, Percent Positive Agreement (PPA, sensitivity), and Percent Negative Agreement (PNA, specificity) of the test.

It’s interactive! Select tests and change values if you like.

In the graphs, you can toggle any of the series off or on. This is helpful to understand the impact of prevalence, PPA, and PNA on both absolute numbers and probabilities.

You can also toggle costs off and on, change the values and currency symbol.

The videos below demonstrate the theory of how prevalence, PPA and PNA drive the numbers, probability and cost of false positive and negative results.

Send comments and questions to zoe@awesome-numbers.org

The video series below illustrates the theory of how prevalence, PPA and PNA drive the probability that test results are true or false, and resultant costs to the healthcare system and patients.

Understanding Numbers, Probabilities and Cost of Covid-19 Tests

Part 1:  A simpler view.

This 5 minute video uses graduated cylinders filled with positive and negative test results to illustrate how:

1.  Prevalence drives the number of positive and negative samples in the test population.

2.  PPA (Percent Positive Agreement / Sensitivity) determines the number of positive samples that receive true-positive and false-negative tests.

3.  PNA (Percent Negative Agreement / Specificity) determines the number of negative samples that receive true-negative and false-positive tests.

Prevalence, PPA and PNA combine to drive the probability that a reported result is true or false.

Presented by Zoe Brooks, AWEsome Numbers Inc. July 2020

 

Part 2:  Clinical Interpretation and Cost.

This 4-minute video explains how PPA (Percent Positive Agreement or Sensitivity) and PNA (Percent Negative Agreement or Specificity) drive absolute numbers of false negative and positive results and their resultant patient and healthcare costs.  You can toggle costs off and on, change symbol and amounts in the calculator.

The three risk drivers of prevalence, PPA, and PNA combine to determine the probability of false-positive and negative results, which drive the clinical interpretation of test results.

Presented by Zoe Brooks, AWEsome Numbers Inc. July 2020

Part 3:  Review, Costs and Caution

This 3-minute video summarizes the impact of the risk drivers of prevalence, PPA (sensitivity) and PNA (specificity) on the numbers, probability and cost of false positive and false-negative test results.

It highlights the problem that false-positive results outweigh true-positives when prevalence is low.  Even at a prevalence of 4%, the number of false-positive tests outweighs true-positive tests – with the baseline values of PPA and PNA for molecular tests.  These values change for antigen and antibody tests with lower PPA.

Presented by Zoe Brooks, AWEsome Numbers Inc. July 2020