How does social justice and health inequities influence population health care provision? Why is this critical information for the provision of evidence-based care?
Population-based nursing is the provision of evidence-based care to targeted groups of people with similar needs in order to improve health, or stated otherwise, to improve health. In order to provide this care providers must consider health inequities and social justice in order to improve health care for all people. Population health is typically interested in high risk aggregates(subpopulations) which means looking at those health inequities and using social justice theory to integrate health promotion and disease prevention interventions for those high risk aggregates.
Is screening a tertiary intervention? If yes, why, if not, what is it?
No. Screening are a secondary intervention. Tertiary interventions focus on alleviating disability and are strategies done in middle or late stages of diseases. An example of a tertiary intervention would be cardiac rehab or physical therapy after a hip replacement
How does a provider determine the usefulness, appropriateness, of a screening test? Where would a NP look to find a screening test? What determines if a screening test should be used?
The target population needs to be identifiable and accessible and the disease should affect a sufficient number of people. The screening test should be sensitive enough to detect most cases and be specific enough to limit the number of false positives. Screening tests should be relatively inexpensive, easy to administer, and have minimal side effects. The validity of the screening test is the ability to accurately identify those that have the disease.
Determining if a screening test should be used can be evaluated by the success of a screening tool. Does the screening tool do what it was intended to do and reduce overall mortality, decrease case fatality, increase early detection, reduce complications or increase quality of life?
APNs can look for screening test through the U.S Preventative Services Task
Can you explain what “descriptive epidemiology” means? What is the purpose? How is it used?
Concerned with characterizing the amount and distribution of health and disease within a population. Through the process of looking at rates, incidence, prevalence, mortality, survival, and prognosis we have and understanding of a disease and knowledge of how illnesses and diseases are distributed, what populations are impacted, and how populations differ. Also what interventions would be best for who.
How are causation and descriptive epidemiology related, how do they work together to aid evidence-based care?
Descriptive epidemiology is used to determine causation. Applying strong epidemiologic methods with a sound application and interpretation of statistics are the foundation for evidence-based practice. Practitioners cannot just collect data but also look at the theoretical issues associated with explaining the relationships among variables.
What does “causation” mean? Can you relate causation to primary, secondary and tertiary interventions?
Causation means the conditions that play an essential part in producing the occurrence of a disease or identifying the cause of a disease both modifiable and nonmodifiable in order to prevent the disease or its consequences. Understanding the causation of a disease provides APNs with the knowledge that is required to design programs or interventions that target populations at risk, or developing primary, secondary, and tertiary interventions for specific disease processes.
Are you able to discuss “surveillance” and its relationship to “causation”?
Surveillance is the collection, analysis, and dissemination of data pertaining to the occurrence of a disease. In order to know what causes diseases, we must use surveillance.
Can you talk about the ways bias shows up in a study design (such as, selection bias) etc.?
Bias occurs when the selected subjects are not representative of the population of interest or representative of the comparison group. This bias(selection of subjects) can make it appear that there is or is not an association between an exposure and an outcome.
Selection bias= the systematic error that occurs with “selecting a study group or groups within the study” such as nonprobability sampling where members of a target population do not share equal chances of being selected for the study or intervention/treatment group.
Volunteer Bias= where volunteers for a study may not have the same characteristics as those who do not volunteer
Exclusion Bias= when one applies different eligibility criteria to the cases and controls
Withdrawal Bias= when people of certain characteristics drop out of a group at a different rate than they do in another group or are lost to follow up at a different rate.
Information Bias- deals with how information or data are collected for a study.
What does it mean to show a causal relationship?
A causal relationship means that an increase in the causal factor or exposure causes an increase in the outcome of interest.
Four types of causal relationships:
Necessary and Sufficient- a factor is necessary (disease occurs if factor present) and sufficient (exposure always leads to disease). Relationship is rare.
Necessary but Not Sufficient- more than one factor is necessary. Factor needs to be present but just because its present doesn’t mean its sufficient enough to produce disease. Ex. When considering tuberculosis, the tubercle bacillus is a necessary factor, but its presence doesn’t always lead to disease.
Sufficient but Not Necessary- a specific factor can be sufficient to produce disease but so can other factors. Ex. Vitamin B12 can cause anemia but so could other factors
Neither Sufficient or Necessary- a specific factor can be combined with other factors to produce disease, but the disease could be produced in absence of the factor.
What is an intervention group? Where is it found?
An intervention group is a group who receives a treatment or intervention compared to a control group. Intervention groups are seen in research studies
What is meant by “scientific misconduct”?
Gift authorship, data fabrication and falsification, plagiarism, and conflict of interest. Can have an impact on researchers, patients, and populations.
Differentiate: random error, systematic error, confounding error.
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- Submitted On 15 Feb, 2020 12:59:22