0.1 Context

The Affordable Care Act (ACA) is the name for the comprehensive health care reform law and its amendments which addresses health insurance coverage, health care costs, and preventive care. The law was enacted in two parts: The Patient Protection and Affordable Care Act was signed into law on March 23, 2010 by President Barack Obama and was amended by the Health Care and Education Reconciliation Act on March 30, 2010.

0.2 Content

The visualizations depicts health insurance coverage data for each state and the United States as a whole, including variables such as the uninsured rates before and after Obamacare, estimates of individuals covered by employer and marketplace healthcare plans, and enrollment in Medicare and Medicaid programs. The data set comes from kaggle.

0.3 Acknowledgements

The health insurance coverage data was compiled from the US Department of Health and Human Services and US Census Bureau.

0.4 Variables

Some of the variables in the data set are:

0.5 Data Cleaning

colnames(aca) <- c("State", 
                   "Uninsured_Rate_2010", 
                   "Uninsured_Rate_2015",
                   "Uninsured_Rate_Ch_2010_2015", 
                   "Health_Ins_Cov_Ch_2010_2015",
                   "Empl_Ins_Cov_Ch_2010_2015", 
                   "Mktpl_Ins_Cov_Ch_2010_2015",
                   "Mktpl_Tx_Credits", 
                   "Avg_Mo_Tx_Credit", 
                   "State_Medicaid_Exp", 
                   "Medicaid_Enroll_2013", 
                   "Medicaid_Enroll_2016",
                   "Medicaid_Enroll_Ch_2013_2016", 
                   "Medicare_Enroll_2016")



# convert character percentage rates to numeric
aca$Uninsured_Rate_2010 <- as.numeric(sub("%", "", aca$Uninsured_Rate_2010))/100
aca$Uninsured_Rate_2015 <- as.numeric(sub("%", "", aca$Uninsured_Rate_2015))/100
aca$Uninsured_Rate_Ch_2010_2015 <- as.numeric(sub("%", "", aca$Uninsured_Rate_Ch_2010_2015))/100

# convert $ to numeric
aca$Avg_Mo_Tx_Credit <- as.numeric(gsub("[^0-9]", "", aca$Avg_Mo_Tx_Credit))

# convert state to a factor
aca$State <- as.factor(aca$State)




# the value for the US in Uninsured_Rate_Ch_2010_2015 is incorrect.  we'll fix it
aca$Uninsured_Rate_Ch_2010_2015 <- aca$Uninsured_Rate_2015 - aca$Uninsured_Rate_2010

# create a data frame with just the US summary info and a set with just the states
aca_state <- aca[!aca$State == "United States", ]
aca_us <- aca[aca$State == "United States", ]

# drop unused factor levels
aca_state$State <- factor(aca_state$State)
aca_us$State <- factor(aca_us$State)

0.6 Summary Statistics

Let’s run some basic functions to understand the structure and schema of the data set.

 summary(aca_us)
##            State   Uninsured_Rate_2010 Uninsured_Rate_2015
##  United States:1   Min.   :0.155       Min.   :0.094      
##                    1st Qu.:0.155       1st Qu.:0.094      
##                    Median :0.155       Median :0.094      
##                    Mean   :0.155       Mean   :0.094      
##                    3rd Qu.:0.155       3rd Qu.:0.094      
##                    Max.   :0.155       Max.   :0.094      
##  Uninsured_Rate_Ch_2010_2015 Health_Ins_Cov_Ch_2010_2015
##  Min.   :-0.061              Min.   :19304000           
##  1st Qu.:-0.061              1st Qu.:19304000           
##  Median :-0.061              Median :19304000           
##  Mean   :-0.061              Mean   :19304000           
##  3rd Qu.:-0.061              3rd Qu.:19304000           
##  Max.   :-0.061              Max.   :19304000           
##  Empl_Ins_Cov_Ch_2010_2015 Mktpl_Ins_Cov_Ch_2010_2015 Mktpl_Tx_Credits 
##  Min.   :172292000         Min.   :11081330           Min.   :9389609  
##  1st Qu.:172292000         1st Qu.:11081330           1st Qu.:9389609  
##  Median :172292000         Median :11081330           Median :9389609  
##  Mean   :172292000         Mean   :11081330           Mean   :9389609  
##  3rd Qu.:172292000         3rd Qu.:11081330           3rd Qu.:9389609  
##  Max.   :172292000         Max.   :11081330           Max.   :9389609  
##  Avg_Mo_Tx_Credit State_Medicaid_Exp Medicaid_Enroll_2013
##  Min.   :291      Length:1           Min.   :56392477    
##  1st Qu.:291      Class :character   1st Qu.:56392477    
##  Median :291      Mode  :character   Median :56392477    
##  Mean   :291                         Mean   :56392477    
##  3rd Qu.:291                         3rd Qu.:56392477    
##  Max.   :291                         Max.   :56392477    
##  Medicaid_Enroll_2016 Medicaid_Enroll_Ch_2013_2016 Medicare_Enroll_2016
##  Min.   :73532931     Min.   :16106157             Min.   :57149984    
##  1st Qu.:73532931     1st Qu.:16106157             1st Qu.:57149984    
##  Median :73532931     Median :16106157             Median :57149984    
##  Mean   :73532931     Mean   :16106157             Mean   :57149984    
##  3rd Qu.:73532931     3rd Qu.:16106157             3rd Qu.:57149984    
##  Max.   :73532931     Max.   :16106157             Max.   :57149984

Our summary shows the Unites States as whole had an uninsured rate of 15.5% in 2010 and an uninsured rate of 9.4% in 2015 which means the unisured rate dropped by 6.1% in that period. Medicaid enrollment in 2013 was 56,392,477 and in 2016 the number jumped to 73,532,931. There was a net increase of 16,106,157 enrollments from 2013-2016. Medicare enrollment in 2016 stood at 57,149,984.

Our first visualization shows that citizens of Massachusetts and Maine had the most uninsured rate drop to around 1% while citizens of Oregon and Nevada had a drop in uninsured rate to around 10 percent from 2010-2015

## [1] 2

The state of California had the biggest Medicaid enrollment change from 2013-2016 while the states of Oklahoma, Nebraska and Wyoming had the least Medicaid enrollment change and that’s because those states did not implement the Medicaid Expansion program.

The state of California had the biggest Health insurance change from 2013-2015 while the states of Wyoming, South Dakota, North Dakota had the least insurance change in the same period

The state of Alaska had the highest average monthly tax credit at around 750$ while the state of New York had the least at around 180$.