PODCAST: Statistics in Health Care Finance

By Eric Bricker MD

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Specificity versus Sensitivity: https://medicalexecutivepost.com/2020/03/20/medical-laboratory-sensitivity-versus-specificity/

Correlation versus Causation: https://medicalexecutivepost.com/2021/02/05/correlation-is-not-causation/?preview_id=239347&preview_nonce=a2cdc51424&preview=true

False Positives and Negatives: https://medicalexecutivepost.com/2019/09/14/what-are-false-positive-and-false-negative-tests/

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Risk Management, Liability Insurance, and Asset Protection Strategies for Doctors and Advisors: Best Practices from Leading Consultants and Certified Medical Planners™

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Type I Errors VERSUS Type II Errors [Medical Testing]

False Positive VERSUS False Negative Tests

By Staff reporters

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What are False Positive and False Negative Tests?

Binary Test Errors

[By staff reporters]

In medical testing, and more generally in binary classification, a false positive is an error in data reporting in which a test result improperly indicates presence of a condition, such as a disease (the result is positive), when in reality it is not present, while a false negative is an error in which a test result improperly indicates no presence of a condition (the result is negative), when in reality it is present.

Assessment

These are the two kinds of errors in a binary test (and are contrasted with a correct result, either a true positive or a true negative.) They are also known in medicine as a false positive (respectively negative) diagnosis, and in statistical classification as a false positive (respectively negative) error.

A false positive is distinct from overdiagnosis, and is also different from overtesting.

Conclusion: Your thoughts are appreciated.

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