Decision Making for eHealth

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Questions and Answers

What is the primary reason for the surprising result that a person who tests positive for HIV has only a 50% chance of actually having the disease?

  • The test is biased towards giving false positives
  • The prevalence of HIV in the population is low (correct)
  • The test is not suitable for the population being tested
  • The PCR test is not 100% accurate

Which of the following is an example of a prior probability?

  • The prevalence of a disease in a population (correct)
  • The probability of a false positive test result
  • The probability of a person testing positive for a disease
  • The probability of a disease given a positive test result

What is the purpose of the second stage of the diagnostic process?

  • To make a definitive diagnosis
  • To gather more information to reduce uncertainty (correct)
  • To calculate the prior probability of a disease
  • To determine the reliability of the test

What is the role of decision support systems in the diagnostic process?

<p>To provide additional information to support diagnosis (B)</p> Signup and view all the answers

In the context of Bayes' theorem, what does the term P(A) refer to?

<p>The prior probability of a disease (A)</p> Signup and view all the answers

What is the primary application of computational methods in the diagnostic process?

<p>To reduce the uncertainty of the diagnosis (A)</p> Signup and view all the answers

What is the goal of combining prior probability with test results in Bayes' theorem?

<p>To generate a high posterior probability (B)</p> Signup and view all the answers

What happens to the posterior probability if the prior probability is very low and a positive test result is obtained?

<p>It increases only into the intermediate range (D)</p> Signup and view all the answers

What is the assumption of Bayes' theorem when applied sequentially to two tests?

<p>That the tests are conditionally independent (B)</p> Signup and view all the answers

What can happen if the prior probability is unreliable in Bayes' theorem?

<p>The theorem is of little value (B)</p> Signup and view all the answers

What is the effect of a positive test result on the probability of disease?

<p>It increases the probability of disease (A)</p> Signup and view all the answers

What is the role of Bayes' theorem in decision making for eHealth?

<p>To update the probability of disease based on test results (C)</p> Signup and view all the answers

What is the essence of good medicine according to Peabody?

<p>Clear comprehension of probability and possibilities of a case (A)</p> Signup and view all the answers

What is the purpose of testing all potential blood donors for HIV?

<p>To ensure the blood supply is safe (C)</p> Signup and view all the answers

What would be a potential issue with using PCR to diagnose HIV?

<p>It may produce false positives or false negatives (B)</p> Signup and view all the answers

In the context of medical decision making, what is the importance of understanding probability?

<p>To understand the possibilities and probabilities of a case (C)</p> Signup and view all the answers

Why is it important to consider the imperfections of clinical data?

<p>To acknowledge the uncertainty of medical decision making (D)</p> Signup and view all the answers

What percentage of the time will the PCR test correctly identify individuals who do not have HIV?

<p>99%</p> Signup and view all the answers

According to the example, what percentage of the population has HIV?

<p>1%</p> Signup and view all the answers

What is the probability of a true positive, given that a person has HIV?

<p>0.99</p> Signup and view all the answers

What is the formula used to calculate the probability of having HIV given a positive PCR test?

<p>P(H|P) = [P(P|H) * P(H)] / P(P)</p> Signup and view all the answers

What is the total probability of a positive test, according to the example?

<p>P(P) = P(P and H) + P(P and not H) = (0.99 * 0.01) + (0.01 * 0.99)</p> Signup and view all the answers

What percentage of healthy individuals will incorrectly test positive for HIV?

<p>1%</p> Signup and view all the answers

What is the significance of considering prior probabilities in diagnostic test results, as demonstrated by the HIV diagnosis example?

<p>Considering prior probabilities is important because they can greatly impact the accuracy of test results, as seen in the HIV diagnosis example where a 99% accurate test yields only a 50% chance of actually having HIV due to the low prevalence of the disease.</p> Signup and view all the answers

How does the relatively low prevalence of HIV in the population affect the interpretation of the PCR test results?

<p>The low prevalence of HIV in the population (1%) affects the interpretation of the PCR test results by reducing the accuracy of the test, resulting in a 50% chance of actually having HIV even with a 99% accurate test.</p> Signup and view all the answers

What is the role of Bayes' theorem in combining prior probabilities with test results in the diagnostic process?

<p>Bayes' theorem plays a crucial role in combining prior probabilities with test results to calculate the posterior probability of a disease, enabling a more accurate diagnosis.</p> Signup and view all the answers

What is the implication of a 99% accurate PCR test yielding a 50% chance of actually having HIV in a patient who tests positive?

<p>The implication is that the test is prone to false positives, and the result should be interpreted in the context of the low prevalence of HIV in the population.</p> Signup and view all the answers

How does the sensitivity and specificity of a diagnostic test affect the reliability of the test results?

<p>The sensitivity and specificity of a diagnostic test are crucial in determining the reliability of the test results, as they impact the accuracy of the test in detecting true positives and true negatives.</p> Signup and view all the answers

What is the significance of the first stage of the diagnostic process, which involves making an initial judgment about whether a patient is likely to have a disease?

<p>The first stage of the diagnostic process involves making an initial judgment about the likelihood of a patient having a disease, which sets the prior probability for further testing and diagnosis.</p> Signup and view all the answers

In a diagnostic test, what is the difference between a false positive and a false negative?

<p>A false positive is when the test result is positive but the person does not have the disease, while a false negative is when the test result is negative but the person actually has the disease.</p> Signup and view all the answers

How does Bayes' theorem calculate the posterior probability of a disease given a positive test result?

<p>Bayes' theorem calculates the posterior probability by combining the prior probability with the test results, using the formula P(A|B) = P(B|A) * P(A) / P(B).</p> Signup and view all the answers

What is the significance of the 50% probability of actually having HIV despite testing positive?

<p>This result highlights the importance of considering the prior probability of a disease, as well as the accuracy of the test, when making a diagnosis.</p> Signup and view all the answers

What factors can affect the accuracy of PCR tests in diagnosing HIV?

<p>PCR test accuracy can be affected by factors such as contamination, sample quality, and the presence of inhibitors.</p> Signup and view all the answers

Why is conditional independence an important assumption in applying Bayes' theorem sequentially to two tests?

<p>If the tests are not conditionally independent, applying Bayes' theorem sequentially will result in inaccurate posterior probabilities.</p> Signup and view all the answers

What is the goal of combining prior probability with test results in Bayes' theorem?

<p>The goal is to generate a high posterior probability that can inform a diagnosis with increased confidence.</p> Signup and view all the answers

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