Exploratory Graphing - Medical Coverage by State and Illnesses
You will be looking at a subset of a United States medical expenditures dataset with information on costs for different medical conditions and in different areas of the country.
You should do the following:
Make a plot that answers the question: what is the relationship between mean covered charges (Average.Covered.Charges) and mean total payments (Average.Total.Payments) in New York? Make a plot (possibly multi-panel) that answers the question: how does the relationship between mean covered charges (Average.Covered.Charges) and mean total payments (Average.Total.Payments) vary by medical condition (DRG.Definition) and the state in which care was received (Provider.State)?
download <- download.file("https://d18ky98rnyall9.cloudfront.net/_e143dff6e844c7af8da2a4e71d7c054d_payments.csv?Expires=1477785600&Signature=Bt~7TUHJAZWMzAjg6cMaQDvRWHhKjOEYWo-tNlLFOtwxOeO2g~mitUM1R9SGe371rHFU3HbgIFJFps772qmMaB2MoPEh9-fBub~Y59KtZd4h40~kkGXeltDL5FzEKprFQmtk~cNvll3cRd-0M-KR-sebeijKeU2K0IuHQ4PLts0_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A",destfile = "temp")
data <- read.csv("temp")
unlink("temp")
head(data)## DRG.Definition Provider.Id
## 1 194 - SIMPLE PNEUMONIA & PLEURISY W CC 50242
## 2 194 - SIMPLE PNEUMONIA & PLEURISY W CC 100061
## 3 194 - SIMPLE PNEUMONIA & PLEURISY W CC 100062
## 4 194 - SIMPLE PNEUMONIA & PLEURISY W CC 100181
## 5 194 - SIMPLE PNEUMONIA & PLEURISY W CC 100183
## 6 194 - SIMPLE PNEUMONIA & PLEURISY W CC 100187
## Provider.Name Provider.Street.Address Provider.City
## 1 DOMINICAN HOSPITAL 1555 SOQUEL DRIVE SANTA CRUZ
## 2 MERCY HOSPITAL INC 3663 S MIAMI AVE MIAMI
## 3 MUNROE REGIONAL MEDICAL CENTER 1500 SW 1ST AVE OCALA
## 4 LARKIN COMMUNITY HOSPITAL 7031 SW 62ND AVE SOUTH MIAMI
## 5 CORAL GABLES HOSPITAL 3100 DOUGLAS RD CORAL GABLES
## 6 PALMETTO GENERAL HOSPITAL 2001 W 68TH ST HIALEAH
## Provider.State Provider.Zip.Code Hospital.Referral.Region.Description
## 1 CA 95065 CA - Santa Cruz
## 2 FL 33133 FL - Miami
## 3 FL 34474 FL - Ocala
## 4 FL 33143 FL - Miami
## 5 FL 33134 FL - Miami
## 6 FL 33016 FL - Miami
## Total.Discharges Average.Covered.Charges Average.Total.Payments
## 1 96 60386.84 9175.01
## 2 32 33432.12 7389.15
## 3 96 25886.77 5419.63
## 4 74 39932.79 8326.00
## 5 35 74303.31 8241.82
## 6 54 65354.05 8504.90
## Average.Medicare.Payments
## 1 8250.46
## 2 6414.65
## 3 4542.18
## 4 7615.60
## 5 7097.31
## 6 7773.37library(ggplot2)g <- ggplot(data, aes(x=Average.Total.Payments,y=Average.Covered.Charges))+geom_point()+stat_smooth()
g
g2 <- ggplot(data, aes(x=Average.Total.Payments,y=Average.Covered.Charges, group=Provider.State))+geom_point()+stat_smooth(aes(colour=Provider.State,fill=Provider.State))
g2
g3 <- ggplot(data, aes(x=Average.Total.Payments,y=Average.Covered.Charges, group=DRG.Definition))+geom_point()+stat_smooth(aes(colour=DRG.Definition,fill=DRG.Definition))
g3+theme(legend.position="bottom")
g4 <- ggplot(data, aes(x=Average.Total.Payments,y=Average.Covered.Charges, group=DRG.Definition))+geom_point()+stat_smooth(aes(colour=DRG.Definition,fill=DRG.Definition))+facet_grid(. ~ Provider.State)
g4+theme(legend.position="bottom") + theme(axis.text.x = element_text(angle = 90, hjust = 1))
See more at my website.