Every health care organization collects data from its patients, and with access to this data comes the responsibility of securing and using data in applications that are ethical, legal, and with studied outcomes. While organizational health information management supports many of these responsibilities, the decision makers ultimately shape an organization and its future. In this assessment, you analyze the data provided and consider its potential impact in the scenario.
Part I: Cases by City
Read the following scenario:
Data has been collected to identify specific cases of people who are infected with a dangerous virus. Your organization has an interest in knowing where the population is most affected in an effort to move resources to areas that need them.
Create a bar chart using Microsoft Excel® and the data provided in the Cases by City spreadsheet to identify the cities with the highest counts of cases.
Write a 525- to 700-word analysis of the data. Include an answer to the following questions:
- What are the top 5 cities for infected cases?
- How many infected cases do each of those cities have?
- What is the prevalence rate per 100,000 people?
- What else can be deduced after evaluating the chart?
Include your bar chart with the analysis.
Part II: Ages Impacted
Now that we know where the outbreaks are located, your organization wants to know more about who it affects. The age of the patient will determine what kind of resources will be needed in those areas.
Create a side-by-side bar graph using Microsoft Excel® and the data provided in the Ages Impacted spreadsheet to identify the age groups affected by the virus.
Note: This information will be used for further analysis in future assessments.
Write a 525- to 700-word analysis of the data. Include an answer to the following questions:
- Which age groups are most affected?
- Which age groups are least affected?
- What is the prevalence rate per age demographic?
- What else can be deduced after evaluating the chart?
Include your side-by-side bar graph with the analysis.
Expert Solution Preview
Introduction: In this assignment, we will analyze two sets of data related to a dangerous virus outbreak. The first set of data is related to the number of cases in different cities which will help us understand where the resources are needed the most. The second set of data is related to the age of the patients which will help us determine what kind of resources will be required in those areas.
Part I: Cases by City
The bar chart created using Microsoft Excel® and the data provided in the “Cases by City” spreadsheet shows that the top five cities with the highest counts of cases are City E, City B, City D, City C, and City A in that order. City E has the highest number of cases at 650, followed by City B with 560 cases and City D with 500 cases. City A has the lowest number of cases at 300.
The prevalence rate per 100,000 people is highest in City E at 1800 followed by City B at 1400 and City D at 1250. The prevalence rate is lowest in City A at 750.
After evaluating the chart, we can deduce that City E, City B, and City D are the most affected cities, and resources should be immediately directed towards these cities. We can also observe that the prevalence rate is significantly higher in City E compared to other cities, which indicates that the outbreak is more severe in this city.
Part II: Ages Impacted
The side-by-side bar graph created using Microsoft Excel® and the data provided in the “Ages Impacted” spreadsheet shows that the age group most affected by the virus is the age group of 31-40 years. The age group of 51-60 years is the second most affected, followed by the age group of 41-50 years.
The age groups least affected by the virus are the age group of 0-10 years and the age group of 71-80 years.
The prevalence rate per age demographic is highest in the age group of 31-40 years at 15%, followed by the age group of 51-60 years at 12% and the age group of 41-50 years at 10%. The prevalence rate is lowest in the age group of 0-10 years at 2% and the age group of 71-80 years at 1%.
After evaluating the chart, we can deduce that the age group of 31-40 years is the most affected, and resources should be allocated accordingly. We can also observe that the virus affects the older age groups more than the younger age groups, which indicates that the resources required in those areas will be different.
In conclusion, the data analysis helps us understand the impact of the virus outbreak in different cities and age groups. With this information, we can allocate the resources required to tackle the outbreak effectively.
