Assignment: Downtime Plan Analysis

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Assignment: Downtime Plan Analysis

Assignment: Downtime Plan Analysis

Assignment: Downtime Plan Analysis

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Assignment: Downtime Plan Analysis
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Week 5 Downtime Plan Analysis Paper Analyze the current downtime plan for scheduled upgrades that will support workflow, clinical processes, and data recovery in your organization. Utilizing scholarly resources, write a two- to three-page paper that discusses your recommendations for editing or amending the current downtime plan. In addition to course resources, a minimum of two outside resources must be used. Examples of scholarly sources include professional journal articles and books obtained from library databases, national guidelines, and informatics organizations, published within the last five years.Conduct bivariable analyses:
i. Display the data in two-variable tables:
Sometimes the characterization of the population can be extended to
two-variable tables, such as age by sex. For surveys in which the
objective is to estimate prevalence, the data are often analyzed by
population characteristics. For example, you can use two-variable
tables to determine whether the prevalence varies by sex or
education level. For analytic studies in which the objective is to
quantify associations between exposures and outcomes, the twovariable table displays the core result, with rows representing levels
of exposure and columns representing presence or absence of the
ii. Compute and interpret measures of association:
Determine the magnitude of association between an exposure
variable and an outcome variable. If there are two or more
populations, consider comparing their demographic data to determine
whether they were different before the study/analysis was conducted.
iii. Calculate confidence intervals and/or statistical significance:
Utilize confidence intervals to quantify the variability of the data in
your analysis. Use t-tests for continuous data, chi-square tests for
categorical data, and other statistical tests as appropriate for the data
to determine whether the results are “statistically significant.”
iv. Assess for effect measure modifcation:
Effect measure modification (also known as “effect modification”) is
present when an effect measure such as sex, age or geographic
location is different at several levels in an exposure-disease
relationship. This is evaluated through statistical assessment of
interaction between variables.
v. Assess the effect of potential confounders:
Confounding is an apparent association between disease and
exposure resulting from a third factor that was not considered. A
confounder is an independent risk factor for the disease that also
happens to be associated with the exposure variable under
3. Conduct multivariable analyses:
Use your literature review and previous experience to decide on a
multivariable analysis and modeling technique to address the
hypotheses presented. Utilize the results of the bivariable analysis in
implementing your modeling strategy to determine a final model or set of
models that best explain your data.
Before learning how to create an analysis plan, let us review common types
of statistical data by completing the exercise below.

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