Data Visualization Analysis of Public Health Department in the United States

Running Head: DATA VISUALIZATION 1
The public health department in the United States
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Student ID:
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DATA VISUALIZATION 2
List of figures 3
Executive summary 4
Background Information 5
Analysis and Reporting 6
ICU days and Group of diagnosis 6
Most and Least Popular Diseases 7
The number of patients seen per department 8
Region, race, diagnosis and where patients are discharged to 9
Trend, diagnosis and patients’ number by admission date 11
Admission month, the city where patients come from, admin date, gender and the number of
patients in general 12
Hospital and patient number map 14
Additional Visualizations 16
Justification 18
Dashboard 19
Discussions 20
The Reflection (Individual Task) 21
Conclusion 21
References 22
Appendices 23

DATA VISUALIZATION 3
List of figures
Figure 1: ICU days and Group of diagnosis---------------------------------------------------------------5
Figure 2: Diagnosis by region-------------------------------------------------------------------------------5
Figure 3: Disease popularity---------------------------------------------------------------------------------6
Figure 4: Department and number of patients seen-------------------------------------------------------8
Figure 5: Number of female patients by gender----------------------------------------------------------8
Figure 6: Places where patients are discharged to--------------------------------------------------------9
Figure 7: Race and region------------------------------------------------------------------------------------9
Figure 8: Hospital number of visits and diagosis--------------------------------------------------------10
Figure 9: Patient's trend and diagnosis--------------------------------------------------------------------10
Figure 10: Operation counts per deprtment--------------------------------------------------------------11
Figure 11: Patient's number and admission--------------------------------------------------------------12
Figure 12: Distribution of patients by cities--------------------------------------------------------------12
Figure 13: Admission dates based on gender basis-----------------------------------------------------13

DATA VISUALIZATION 4
Executive summary
According to the results, the highest ICU days among males is high in region 11 for both Acute
Myocardial Infarction and COPD. In addition, regions 10 and 11 have the highest diagnosis of
Congestive Heart Failure. The least and most popular diseases are the COPD/disorders of disease
electrolyte and Congestive Heart Failure/Heart failure respectively. Similarly, Pneumonia
Organism Unspecified and Bronchopneumonia are the least and most popular diseases as well.
Chronic Bronchitis under the COPD is also considered as the most popular disease. The highest
department with many patients is heart followed by general medicine department. On the other
hand, the Neurosciences is the department with lowest patients seen over the same period. On
race, the highest number of patients in region 8 belongs to the “Black race”. Hospital 35 also saw
the highest patients suffering from ASTHMA. At least, COPD and AMI recorded the highest
number of patients in January 2012. At the same time, many admissions of the patients occurred
during March 2012 with few admissions seen from October to January 2012. Based on these
results, the following recommendations are made; Courses on Congestive Heart Failure should
be offered in the US medical colleges given that these are the most diagnosed diseases. There is
need to deploy doctors in Region 10 and 11 specializing in CHF due to its popularity in these
regions.

DATA VISUALIZATION 5
Background Information
Health organizations like the public health department in the United States normally deal with a
big dataset due to its large population. Therefore, data visualization analysis plays an important
role in the public health department. These roles include but not limited to the general
improvement of the productivity of the department as a whole, (Hashem, Yaqoob, Anuar, Mokhtar,
Gani, and Khan, 2015). As a result, the department operates in a more effective and efficient
manner by presenting deep and easy to understand valuable insights that at the end of the day
have the ability to improve the organization’s reputation thus making the public health
department to remain competitive and relevant. This data visualization analytics, as a result,
improves the overall performance of the organization.
For the purposes of accomplishing this assignment, the "READMIT-HISTORICAL" dataset
from teradatauniversitynetwork.com was considered. Generally, SAS visualization analytics is
important in making data visualization analytics in many ways. For instance, these visualizations
produced from the SAS analytics help the organizational management to make effective and
relevant decisions that are reliable and inform improvement in the general services being offered
to the populations. In addition, these visualizations have the ability to communicate the existing
trends as well as an earthing the presence of hidden patterns within the dataset. As a result,
decision-making processes become easy now that the results can easily be viewed and
understood by just having a glance at the charts. The main reason for focusing on these analytics
is based on the fact that health industry as a whole has become expensive in the States and
therefore, there is need to ensure that these data are timely analyzed so that actions can be taken
based on the data collected, (Groves, Kayyali, Knott, and Kuiken, 2016). These findings furthermore
contribute to the development of strategic plans while addressing health issues in the States.
In the current world, big data analysis has continued to gain momentum due to the fact that it has
the potential to evaluate general services being offered to the population especially in the
healthcare sector in general, (Iqbal, Doctor, More, Mahmud, and Yousuf, 2018). At the same time
data has continued to grow like in the case of June 2011 – July 2012 huge data of numerous
hospitals within the states. This data needs to be analyzed in a timely manner so that effective
actions for improving healthcare can be made. Furthermore, through the SAS visualization
analytics, there is easy to predict the future of healthcare with the United States. Given the fact
that the US health departments are dealing with lives, they need timely reports from data
visualization analytics to continue offering improved healthcare services.
Some of the benefits of data visualization include easy understanding and interpreting of the
results at a glance. For example, by the use of dashboards, managers can easily manipulate by
adding more datasets to the source data and observe the results. In addition, with the use of
visualizations, the level of accuracy is highly unlike to tables especially if they are overcrowded,
it becomes difficult to check accuracy. Moreover, visualizations like bar charts can be arranged
in ascending or descending orders thus making them be easily interpreted without necessary
going through many bars. The presentation through visualizations is also appealing to the eye
and this makes many people enjoy dashboards even if they do not have statistical backgrounds,
(Hepworth, & Canon, 2018).

DATA VISUALIZATION 6
Analysis and Reporting
ICU days and Group of diagnosis
Figure 1: ICU days and Group of diagnosis
Figure 2: Diagnosis by region