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NR503: Population Health, Epidemiology, & Statistical Principles Week 2 Case analysis: Epidemiology and Biostatistics to Inform Advanced Practice Nursing CA$6.94   Add to cart
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NR503: Population Health, Epidemiology, & Statistical Principles Week 2 Case analysis: Epidemiology and Biostatistics to Inform Advanced Practice Nursing
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NR503: Population Health, Epidemiology, & Statistical Principles Week 2: Epidemiology and Biostatistics to Inform Advanced Practice Nursing TD3: Please provide a summary of the case or information you have discussed this week The ability to classify individuals into the correct disease status d...

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  • June 23, 2021
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  • 2019/2020
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  • epidemiology
  • nr503 population health
  • amp statistical principles week 2 epidemiology and biostatistics to inform advanced practice nursing

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NR 503: Population Health, Epidemiology & Statistical Principles


WEEK 2: TD3


NR503: Population Health, Epidemiology, & Statistical Principles Week 2: Epidemiology
and Biostatistics to Inform Advanced Practice Nursing
TD3: Please provide a summary of the case or information you have discussed this week


The ability to classify individuals into the correct disease status depends on the
quality, and accuracy of the screening or the diagnostic test. Ideally, a good screening test
will be able to tell us which subjects have the disease and vice versa, which will lead to
earlier treatment and that this, in turn, will lead to a better outcome.The ideal screening
test must also be valid and reliable. The validity of a test is defined as its ability to
distinguish between who has a disease and who doesnot (Gordis, 2014 p, 88).An ideal
screening test is exquisitely sensitive (high probability of identifying correctly those who
have the disease) and extremely specific (high probability that those without the disease will
screen negative). If a test is reliable, it gives consistent results with repeated tests.


When evaluating the feasibility or the success of a screening program, one should
also consider the positive and negative predictive values.Positive predictive value is the
proportion of persons with a positive test that are true positive actually have the disease
(true positive) whereas negative predictive value is the proportion of those who test
negative who do not have (Gordis, 2014 p, 100). Predictive value of a test is an important
issue. Physician used it to enhance his/her ability to make a correct diagnosis.One needs to
consider what happens to the people who had a positive screening test but turned out not
to have the disease (false positives) and to the people who had a negative screening test but
turned out to have the disease (false negatives).


Reference
Gordis, L. (2014). Epidemiology (5th ed.). Philadelphia, PA: Elsevier

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