US health department | Assessment 1

Running Head: BIG DATA 1
US health department
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BIG DATA 2
Table of Contents
LIST OF FIGURES.........................................................................................................................3
Executive Summary.........................................................................................................................4
Background Information..................................................................................................................4
Reporting and Dashboard................................................................................................................6
DIAGNOSIS GROUP AND POPULARITY OF THE DISEASES...............................................7
DEPARTMENTS AND THE NUMBER OF PATIENTS..............................................................9
PATIENT NUMBER BY GENDER, RACE, HOSPITAL, AND DISCHARGE........................10
PATIENT NUMBER, ADMISSION, AND CITY.......................................................................12
HOSPITAL AND PATIENT NUMBER MAP.............................................................................14
Additional Visualizations..............................................................................................................15
TREND, DIAGNOSIS AND PATIENTS NUMBER BY ADMISSION DATE.........................15
Justification....................................................................................................................................17
Discussions....................................................................................................................................17
The Reflection (Individual Task)...................................................................................................18
Conclusion.....................................................................................................................................19
References......................................................................................................................................20
Appendices....................................................................................................................................21

BIG DATA 3
LIST OF FIGURES
Figure 1: ICU days and Diagnosis...................................................................................................5
Figure 2: Diagnosis and Region......................................................................................................5
Figure 3: CHF most and least popular disease................................................................................6
Figure 4: AMI most and least popular disease................................................................................7
Figure 5: COPD most and least popular disease.............................................................................7
Figure 6:Departments and number of patients.................................................................................8
Figure 7: Patient number and gender...............................................................................................9
Figure 8: Proportion of patients discharged to home.......................................................................9
Figure 9: Race and Region on patients number.............................................................................10
Figure 10: Number visists by hopsital...........................................................................................10
Figure 11: Patient number and admission date..............................................................................11
Figure 12: City by patient number.................................................................................................12
Figure 13: Admission date by gender............................................................................................12
Figure 14: Trends of patients admission date................................................................................13
Figure 15: Geomap of hospital and patients number.....................................................................14
Figure 16: Trend of patient numbers among CHF.........................................................................15
Figure 17: Trend of diagnosis group by months............................................................................15
Figure 18: Patient number, operation counts, trend by months.....................................................16

BIG DATA 4
Executive Summary
The data explored is on the public health care facilities department with a specific focus on the
facility type, services, facility name, location among others. General data visualization used
include; a horizontal graph, maps, a bar graph, and a dashboard have been used. The Acute
Myocardial Infarction (AMI) has the HIGHEST ICU DAYS while the Congestive Heart Failure
(CHF) is HIGHLY DIAGNOSED. The ICU DAYS among male patients in Acute Myocardial
Infarction (AMI) should be reduced. Heart failure in Congestive Heart Failure (CHF) is the most
popular; 92.15% while Disorders of Fluid Electrolyte is the least popular at about 0.1%. Doctors
specializing in Congestive Heart Failure (CHF) should be encouraged. In Acute Myocardial
Infarction (AMI), Pneumonia Organism Unspecified; 80.6% is the most popular while
Bronchopneumonia; 0.24% is the least popular. In Chronic Obstructive Pulmonary Disease
(COPD), Chronic Bronchitis is the leading group when it comes to popularity of the disease. In
addition, more doctors specializing in Pneumonia Organism Unspecified and Chronic Bronchitis
to adequately respond to patients leading illness conditions should be trained. The department of
heart has so many clients totaling to 770 patients compared to other departments. Neurosciences
have the least number of patients accounting for only 10 patients seen in the same period. There
is need to add more medical doctors in Heart department. On average, 64.78% of the patients are
discharged to home after the treatment. In addition, region 11 has the Highest “Black race”
patients. Highest ASTHMA patients come from Hosp 35 while Hosp 28 have the lowest
ASTHMA patients. The months with the highest admission and lowest admission are March
2012 and October – January 2012 respectively. DELRAY BEACH has the Highest Patient
numbers seen than other cities.
Background Information
Analyzing big dataset in SAS visual analytics helps to ensure that timely and accurate results are
made available to enhance data demand use. For this reason, analysis is important for every
health organization that has a specific focus in order to; enhance productivity and, therefore,
more efficiency and effectivity, various valuable health insights are gained, organization’s
reputation can be upheld, Health Organizations or business firms can remain competitive and
improve overall performance and operations.
In this assignment, the "READMIT-HISTORICAL" dataset from teradatauniversitynetwork.com
has been considered. The SAS visualization analytics have been used since it makes the general
decision-making process easy. Additionally, it helps to communicate general trend observed as
well as discovering any hidden patterns. Reasons why health industry of America is the focus:
Health Industry of America has become expensive, Development and updating of health strategic
plans on various health issues, Common diseases and availability of the medical doctors.
For the purposes of evaluating the general quality of service provided by the health industry in
general, then Big Data analysis is key. Furthermore, data of numerous hospitals especially from
June 2011 – July 2012 is huge hence visualization of health conditions via SAS Visual Analytics
can be easily interpreted. Moreover, it helps predict the future of U.S Health Services hence easy
decision making while planning for healthcare services. Health department deals with the lives of
people within US and needs continual operational improvement while addressing issues of
healthcare in general.

BIG DATA 5
Normally, data visualization comes with a wide range of benefits ranging from but not limited to
having a glance to changes exposed within a timely manner, (Yang, Li, & Zhang, 2018). For
example, dashboards can be manipulated to uncover other findings especially hidden factors
affecting the general performance of an organization. This makes the data visualizations better
than static charts which may not have additional interactions except what has been presented. As
a result, people tend to enjoy data visualizations due to its interactive measures that change the
general perception of many analytics, (Hepworth, & Canon, 2018).

BIG DATA 6
Reporting and Dashboard
 The Acute Myocardial Infarction (AMI) has the HIGHEST ICU DAYS
 In addition, the Congestive Heart Failure (CHF) is HIGHLY DIAGNOSED
Figure 1: ICU days and Diagnosis
Figure 2: Diagnosis and Region