For this assignment, you are to address the question(s) that follow and submit your response as per the guidelines stated in the syllabus. Please submit your document as a “.doc” or “.docx” file using the “Assignments” tab of the web course. Do not submit your response in the “Discussions” section of the course.

Discussion Question #1:

  • Using epidemiological measures, prioritize what population subgroups should be targeted in a screening program for the following health conditions: oropharyngeal cancer, testicular cancer, and skin cancer (all types).
  • What challenges do you foresee to the effectiveness of the screening programs in the subpopulations you have identified?
  • What might be some of the barriers to participation in the screening programs and how might these barriers be addressed?

Discussion Question Guidelines

• Your response to the discussion question must be of sufficient length to permit the instructor to assess your understanding of the subject matter. I would suggest a discussion posting of no less than 450 words. This assignment should include cited works as indicated with a list of references at the conclusion of the document.
• Please single-space your discussion. 
• Do not attach a cover sheet/title page with your posting.
• Please make sure your response relates to the relevant concepts explored in the question and that all components of the discussion question are addressed. 
• Discussions posted after the due date will not be graded.
• You must submit your response to the discussion question as a word document posted in the “Assignments” section of the web course. Use only .doc or .docx files; any files that cannot be opened will be returned to the student and the delay may result in a “missed” or “late” status for that assignment.
• Please remember to put your name on all documents submitted. 
• A rubric will be posted to guide your responses to the discussion questions.

Attached are the powerpoints and the article from the module in the class

10 The Nurse Practitioner • Vol. 40, No. 8

NP Insights

By Tom Bartol, APRN

Our current health-
care culture empha-
sizes evidence-based
treatment. Diagnostic
testing should also be

evidence-based. Tests are sometimes
ordered without considering the
evidence behind them. Clinicians
may order a diagnostic test out of
fear or to offer reassurance to the
patient. Ineffi cient testing can lead
to increased costs as well as unneces-
sary or unwanted treatment for
some patients. Using evidence to
guide diagnostic testing can become
part of the shared decision-making
process, giving the patients a
perspective about what the test
might mean for them. The patient
and clinician can then make a choice
that fi ts with the patient’s condition
as well as the patient’s desired goals
and values.

This process need not add
immense complexity to the decision-
making process. Four steps can
make the process more thoughtful
and effi cient. First, determine the
pretest probability of the condition
you are concerned about. If you
have no idea what you are looking
for or have no differential diagnoses,
then a test is probably not the way
to begin. Second, determine what
you want from the test. Do you want
to rule out or rule in a disease or
condition? Next, understand the
sensitivity and specifi city of the test
you want to use. Finally, think about
what you will do with the results of
the test.

■ Pre-test probability

Pretest probability is the likelihood
that a patient has the condition you
are considering prior to testing. This
can be based on the prevalence of the
condition in the population. For
example, the prevalence of colon
cancer in the average 50-year-old
female patient is about 0.1% or 1 in
1,000.1 If that female had a family
history of colon cancer, heavy
alcohol use, little physical activity, or
other factors that increase risk for
colon cancer, the pretest probability
would be higher. Frequent exercise
or a high-fi ber diet would lower
pretest risk. Pretest probability can
vary based on symptoms or clinical
conditions as well. Consider the case
of a 59-year-old male presenting
with left-sided chest pressure. The
pretest probability would be lower if
the pain is sharp and aggravated with
deep breathing and higher if the pain
is worse with exertion, accompanied
by shortness of breath, nausea, and
diaphoresis. A past history of
coronary artery disease (CAD) or a
history of hypertension and diabetes
in this patient would also increase
pretest probability.

Determining pretest probability
can sometimes be challenging. For
various types of cancer, the pretest
probability or incidence can be found
on the CDC website ( In
many cases, you will not be able to
fi nd an exact percent or number
for the pretest probability. Simply
determining if the probability is low,

Screening Tests:

A Review


Learning Objectives:

  • Understand the role of screening in the secondary prevention of disease.
  • Recognize the characteristics of diseases appropriate for screening.
  • Understand the impact of implementing screening on prevalence and incidence of disease.
  • Calculate and interpret measures of the validity of a screening test:




Learning Objectives (cont.):

  • Understand the relationship between sensitivity and specificity.
  • Calculate and interpret measures of the performance (yield) of a screening test:

-Predictive value positive (PV+)

-Predictive value negative (PV-)

  • Understand factors that influence PV+ and PV-
  • Recognize issues and sources of bias in evaluating screening programs.


Screening for Disease Control

  • Screening:
  • The application of a disease-detection test to people who are as yet asymptomatic.
  • Purpose:
  • To classify individuals with respect to their likelihood of having a particular disease.
  • A screening procedure itself does NOT formally diagnose illness.


Screening for Disease Control

  • Examination of asymptomatic people


  • Classification as unlikely

….. to have a disease


Screening for Disease Control

  • “Unlikely” referred to next screening cycle
  • “Likely” further testing for diagnosis
  • yes no

referred to next

treatment screening cycle


Screening for Disease Control

  • Screening Objective:
  • To lower morbidity and mortality of the disease in a population (the control, rather than the elimination of disease).
  • Screening provides access to the medical care system which is not an actual goal of screening, but is a benefit.


Epidemiologic Measurements: A review

Counts, ratios, proportions, and rates


NBC Nightly News, Saturday September 5, 2015
Salmonella Linked to Cucumbers from Mexico

  • Since July 3, 2015:
  • 27 states involved
  • One person has died (California) – 51 cases in this state
  • No cases reported thus far in Florida
  • 285 persons have become ill; 53 hospitalized
  • 54% of the ill persons are children younger than18; 57% are female
  • Organism: Salmonella Poona
  • Found worldwide in both cold-blooded and warm-blooded animals, and in the environment.
  • Source: Imported cucumbers from Mexico distributed by Andrew & Williamson Fresh Produce
  • Eleven illness clusters have been identified in seven states.
  • An illness cluster is defined as two or more people who do not live in the same household who report eating at the same restaurant location, attending a common event, or shopping at the same location (grocery store) in the week before becoming ill.


The facts:

  • Food may be contaminated during food processing or food handling.
  • Food may become contaminated by the unwashed hands of an infected food handler.
  • Beef, poultry, milk, and eggs are most often infected with salmonella but vegetables may also be contaminated.
  • Contaminated foods usually look and smell normal.
  • Symptoms include: diarrhea, fever, and abdominal cramps.
  • Symptoms develop 12 to 72 hours after infection
  • Illness usually lasts 4 to 7 days.
  • Most people recover without treatment; diarrhea and dehydration may be so severe that hospitalization is necessary.
  • Older adults, infants, and those who have impaired immune systems are at highest risk.


Epidemiologic measurements: The Basics
Four types of data

Description Examples
Nominal Categorical – unordered categories
Two levels – dichotomous
More than two levels – multichotomous
Sex, disease (yes, no),
race, marital status, educational status
Ordinal Categorical – ordering informative Preference rating (e.g., agree, neutral, disagree)
Discrete Quantitative – Integers Number of cases
Continuous Quantitative – Values on a continuum Dose of ionizing radiation,
temperature, tire pressure


Types of data

  • Categorical: Nominal or ordinal
  • No numeric