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Midterm Exam Review: NR 503/ NR503 Epidemiology Exam Review |Complete Guide with Verified Answers (2023/ 2024 New Update)-Chamberlain $11.99   Add to cart

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Midterm Exam Review: NR 503/ NR503 Epidemiology Exam Review |Complete Guide with Verified Answers (2023/ 2024 New Update)-Chamberlain

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Midterm Exam Review: NR 503/ NR503 Epidemiology Exam Review |Complete Guide with Verified Answers (2023/ 2024 New Update)-Chamberlain Q: Is screening a tertiary intervention? If yes, why, if not, what is it? Answer: No, it is secondary. Q: How does a provider determine the usefuln...

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  • August 1, 2023
  • August 1, 2023
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  • 2023/2024
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Midterm Exam Review : NR 503 / NR503 Epidemiology Exam Review |Complete Guide with Verified Answers (2023/ 2024 New Update) -Chamberlain Q: Is screening a tertiary intervention? If yes, why, if not, what is it? Answer: No, it is secondary. Q: How does a provider determine the usefulness, appropriateness, of a screening test? Answer: Determining whether a screening test is appropriate requires the APRN to address several aspects of the disease of interest. The target population needs to be identifiable. There should be enough people to make the study cost effective. The preclinical period should be proficient to allow treatment before symptoms appear so that early diagnosis and treatment make a difference in terms of outcomes. Q: Can you explain what "descriptive epidemiology" means? What is the purpose? How is it used? Answer : It covers time place and person. First, by looking at the data carefully, the epidemiologist becomes very familiar with the data. He or she can see what the data can or cannot reveal based on the variables available, its limitations (for example, the number of records with missing information for each important variable), and its eccentricities (for example, all cases range in age from 2 months to 6 years, plus one 17-year-
old.). Second, the epidemiologist learns the extent and pattern of the public health problem being investigated — which months, which neighborhoods, and which groups of people have the most and least cases. Third, the epidemiologist creates a deta iled description of the health of a population that can be easily communicated with tables, graphs, and maps. Fourth, the epidemiologist can identify areas or groups within the population that have high rates of disease. This information in turn provides i mportant clues to the causes of the disease, and these clues can be turned into testable hypotheses. Q: How are causation and descriptive epidemiology related, how do they work together to aid evidence -based care? Answer: Causation - helps look at the cause of the issue or disease process. Descriptive epidemiology focuses on the person, place, and time. An example of how they are intertwined might be a person who was sick from E. Coli. The physician might look at what the in dividual ate to determine what made them sick. For instance, they may have decided to eat from the salad bar at a local restaurant. Q: 4 types of casual relationships Answer: 1. Necessary and sufficient (rare) - a factor is both necessary (disease will appear only if the factor is present) and sufficient (exposure always cause disease). 2. Necessary but not sufficient: more than one factor is required. Tb is a factor, but even if present not always the person get sick. 3. Sufficient but not necessary - specific fx can cause disease, but other fx can cause the same disease. Ex. anemia 4. Neither sufficient nor necessary - specific fx can be combined with other fx to produce disease. but disease can be produced without the factor. Q: What does "causatio n" mean? Can you relate causation to primary, secondary and tertiary interventions? Answer: is an increase in a casual factor or exposure causes an increase in the outcome of interest (disease). It is related to primary intervention could be the use of f lu vaccines yearly to prevent the flu from causing an illness. A secondary intervention would be to test for the influenza virus in a patient. A tertiary intervention would be giving Tamiflu to a flu positive patient. Since we know that the influenza virus causes the flu when can help to perform actions against it. Q: Are you able to discuss "surveillance" and its relationship to "causation"? Answer: is the ongoing systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice closely integrated with the timely dissemination of these data to those who need to know. Passive surveillance involves using data to look at reportable diseases while active involves using individuals such as project staff interviewing physicians about cases. Using surveillance can help identify the causation of diseases particularly in a spec ific population. Q: absolute risk Answer: the incidence of disease in a population Q: risk factors Answer: a condition that may adversely affect an individual's health Q: relative risk Answer: The ratio of the risk of disease on exposed indi viduals to the risk of disease in non -exposed individuals. Q: Odds Ratio Answer: The ratio of the odds of development of disease in non -exposed person. Q: Attributable risk Answer: How much of the risk (incidence) of the disease we hope to prevent if able to eliminate exposure to the agent in question. Q: Incidence Rate Answer: The number of new cases of a disease that occurs during a specified period of time in a population at risk for developing the disease. Q: prevalence rate Answer: Total number of people infected at one time in a population at specific time, divided by the number of persons in the population at the same time Q: What is the case -control study and how does it differ (or how is it the same) as the cohort study design? Answer: The cohort study design identifies a people exposed to a particular factor and a comparison group that was not exposed to that factor and measures and compares the incidence of disease in the two groups. A higher incidence of disease in the exposed group suggests an association between that factor and the disease outcome. This study design is generally a good choice when dealing with an out break in a relatively small, well -defined source population, particularly if the disease being studied was fairly frequent.

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