The data for this assignment come from the Hospital Compare web site (http://hospitalcompare.hhs.gov) run by the U.S. Department of Health and Human Services. The purpose of the web site is to provide data and information about the quality of care at over 4,000 Medicare-certified hospitals in the U.S. This dataset es- sentially covers all major U.S. hospitals. This dataset is used for a variety of purposes, including determining whether hospitals should be fined for not providing high quality care to patients (see http://goo.gl/jAXFX for some background on this particular topic).
The Hospital Compare web site contains a lot of data and we will only look at a small subset for this assignment. The zip file for this assignment contains three files
A description of the variables in each of the files is in the included PDF file named Hospital_Revised_Flatfiles.pdf. This document contains information about many other files that are not included with this programming assignment. You will want to focus on the variables for Number 19 (Outcome of Care Measures.csv
) and Number 11 (Hospital Data.csv
). You may find it useful to print out this document (at least the pages for
Tables 19 and 11) to have next to you while you work on this assignment. In particular, the numbers of the variables for each table indicate column indices in each table (i.e. Hospital Name
is column 2 in the outcome-of-care-measures.csv file).
best <- function(state, outcome) {
## Read outcome data
## Check that state and outcome are valid
## Return hospital name in that state with lowest 30-day death
## rate
}
The function should check the validity of its arguments. If an invalid state value is passed to best, the function should throw an error via the stop function with the exact message invalid state. If an invalid outcome value is passed to best, the function should throw an error via the stop function with the exact message
invalid outcome. Here is some sample output from the function.
> source("best.R")
> best("TX", "heart attack")
[1] "CYPRESS FAIRBANKS MEDICAL CENTER"
> best("TX", "heart failure")
[1] "FORT DUNCAN MEDICAL CENTER"
> best("MD", "heart attack")
[1] "JOHNS HOPKINS HOSPITAL, THE"
> best("MD", "pneumonia")
[1] "GREATER BALTIMORE MEDICAL CENTER"
> best("BB", "heart attack")
Error in best("BB", "heart attack") : invalid state
> best("NY", "hert attack")
Error in best("NY", "hert attack") : invalid outcome
>
Save your code for this function to a file named best.R.
setwd("~/Desktop/Coursera Data science/R_Programming/Hospital Quality/rprog_data_ProgAssignment3-data") best <- function(state, outcome) { #read outcome data and convert necessary columns to numeric hospital_data <- read.csv("hospital-data.csv") outcome_data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") suppressWarnings(outcome_data[, 11] <- as.numeric(outcome_data[, 11])) suppressWarnings(outcome_data[, 17] <- as.numeric(outcome_data[, 17])) suppressWarnings(outcome_data[, 26] <- as.numeric(outcome_data[, 26])) possible_outcomes <- c("heart attack", "heart failure", "pneumonia") if(any(outcome_data[,7]==state) == FALSE) { stop("invalid state") } if(any(possible_outcomes==outcome) == FALSE) { stop("invalid outcome") } if(outcome == "heart attack") { state_subset <- outcome_data[outcome_data[,7] == state,] best_value <- min(state_subset[,11],na.rm = T) hospital_names <- subset(state_subset[,2],state_subset[,11]==best_value) hospitals_sorted <- sort(hospital_names) #only want one hospital, take first alphabetically best_hospital <- hospitals_sorted[1] best_hospital } else if(outcome == "heart failure") { state_subset <- outcome_data[outcome_data[,7] == state,] best_value <- min(state_subset[,17],na.rm = T) hospital_names <- subset(state_subset[,2],state_subset[,17]==best_value) hospitals_sorted <- sort(hospital_names) #only want one hospital, take first alphabetically best_hospital <- hospitals_sorted[1] best_hospital } else if(outcome == "pneumonia") { state_subset <- outcome_data[outcome_data[,7] == state,] best_value <- min(state_subset[,26],na.rm = T) hospital_names <- subset(state_subset[,2],state_subset[,26]==best_value) hospitals_sorted <- sort(hospital_names) #only want one hospital, take first alphabetically best_hospital <- hospitals_sorted[1] best_hospital } } best("TX", "heart attack")
## [1] "CYPRESS FAIRBANKS MEDICAL CENTER"
best("TX","heart failure")
## [1] "FORT DUNCAN MEDICAL CENTER"
best("MD", "heart attack")
## [1] "JOHNS HOPKINS HOSPITAL, THE"
best("MD", "pneumonia")
## [1] "GREATER BALTIMORE MEDICAL CENTER"
best("BB", "heart attack")
## Error in best("BB", "heart attack"): invalid state
best("NY", "hert attack")
## Error in best("NY", "hert attack"): invalid outcome
Write a function called rankhospital that takes three arguments: the 2-character abbreviated name of a state (state), an outcome (outcome), and the ranking of a hospital in that state for that outcome (num). The function reads the outcome-of-care-measures.csv file and returns a character vector with the name of the hospital that has the ranking specified by the num argument. For example, the call
rankhospital("MD", "heart failure", 5)
would return a character vector containing the name of the hospital with the 5th lowest 30-day death rate for heart failure. The num argument can take values best
, worst
, or an integer indicating the ranking (smaller numbers are better). If the number given by num is larger than the number of hospitals in that state, then the function should return NA. Hospitals that do not have data on a particular outcome should be excluded from the set of hospitals when deciding the rankings.
Handling errors. It may occur that multiple hospitals have the same 30-day mortality rate for a given cause of death. In those cases ties should be broken by using the hospital name. For example, in Texas (TX
), the hospitals with lowest 30-day mortality rate for heart failure are shown here.
> head(texas)
Hospital.Name Rate Rank
3935 FORT DUNCAN MEDICAL CENTER 8.1 1
4085 TOMBALL REGIONAL MEDICAL CENTER 8.5 2
4103 CYPRESS FAIRBANKS MEDICAL CENTER 8.7 3
3954 DETAR HOSPITAL NAVARRO 8.7 4
4010 METHODIST HOSPITAL,THE 8.8 5
3962 MISSION REGIONAL MEDICAL CENTER 8.8 6
Note that Cypress Fairbanks Medical Center and Detar Hospital Navarro both have the same 30-day rate (8.7). However, because Cypress comes before Detar alphabetically, Cypress is ranked number 3 in this scheme and Detar is ranked number 4. One can use the order function to sort multiple vectors in this manner (i.e. where one vector is used to break ties in another vector). The function should use the following template.
rankhospital <- function(state, outcome, num = "best") {
## Read outcome data
}
## Check that state and outcome are valid
## Return hospital name in that state with the given rank
## 30-day death rate
The function should check the validity of its arguments. If an invalid state value is passed to rankhospital, the function should throw an error via the stop function with the exact message invalid state
. If an invalid outcome value is passed to rankhospital, the function should throw an error via the stop function with the exact message invalid outcome
.
Here is some sample output from the function.
> source("rankhospital.R")
> rankhospital("TX", "heart failure", 4)
[1] "DETAR HOSPITAL NAVARRO"
> rankhospital("MD", "heart attack", "worst")
[1] "HARFORD MEMORIAL HOSPITAL"
> rankhospital("MN", "heart attack", 5000)
[1] NA
rankhospital <- function(state, outcome, num) { #read outcome data and convert necessary columns to numeric hospital_data <- read.csv("hospital-data.csv") outcome_data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") suppressWarnings(outcome_data[, 11] <- as.numeric(outcome_data[, 11])) suppressWarnings(outcome_data[, 17] <- as.numeric(outcome_data[, 17])) suppressWarnings(outcome_data[, 26] <- as.numeric(outcome_data[, 26])) possible_outcomes <- c("heart attack", "heart failure", "pneumonia") if(any(outcome_data[,7]==state) == FALSE) { stop("invalid state") } if(any(possible_outcomes==outcome) == FALSE) { stop("invalid outcome") } if(outcome == "heart attack") { state_subset <- outcome_data[outcome_data[,7] == state,] state_subset_nas <- state_subset[order(state_subset[,11],na.last = NA,state_subset[,2]),] #sort and remove hospitals with no data if(nrow(state_subset_nas) < num && is.numeric(num)) { NA #return NA if seleted rank is out of range } else if(num == "worst") { selected_hospital <- state_subset_nas[,2][length(state_subset_nas[,2])] selected_hospital } else if(num == "best"){ selected_hospital <- state_subset_nas[,2][1] selected_hospital } else { selected_hospital <- state_subset_nas[,2][num] selected_hospital } } else if(outcome == "heart failure") { state_subset <- outcome_data[outcome_data[,7] == state,] state_subset_nas <- state_subset[order(state_subset[,17],na.last = NA,state_subset[,2]),] #sort and remove hospitals with no data if(nrow(state_subset_nas) < num && is.numeric(num)) { NA #return NA if seleted rank is out of range } else if(num == "worst") { selected_hospital <- state_subset_nas[,2][length(state_subset_nas[,2])] selected_hospital } else if(num == "best"){ selected_hospital <- state_subset_nas[,2][1] selected_hospital } else { selected_hospital <- state_subset_nas[,2][num] selected_hospital } } else if(outcome == "pneumonia") { state_subset <- outcome_data[outcome_data[,7] == state,] state_subset_nas <- state_subset[order(state_subset[,26],na.last = NA,state_subset[,2]),] #sort and remove hospitals with no data if(nrow(state_subset_nas) < num && is.numeric(num)) { NA #return NA if seleted rank is out of range } else if(num == "worst") { selected_hospital <- state_subset_nas[,2][length(state_subset_nas[,2])] selected_hospital } else if(num == "best"){ selected_hospital <- state_subset_nas[,2][1] selected_hospital } else { selected_hospital <- state_subset_nas[,2][num] selected_hospital } } } rankhospital("TX", "heart failure", 4)
## [1] "DETAR HOSPITAL NAVARRO"
rankhospital("MD", "heart attack", "worst")
## [1] "HARFORD MEMORIAL HOSPITAL"
rankhospital("MN", "heart attack", 5000)
## [1] NA
Write a function called rankall that takes two arguments: an outcome name (outcome) and a hospital rank- ing (num). The function reads the outcome-of-care-measures.csv file and returns a 2-column data frame containing the hospital in each state that has the ranking specified in num. For example the function call rankall(heart attack, best) would return a data frame containing the names of the hospitals that are the best in their respective states for 30-day heart attack death rates. The function should return a value for every state (some may be NA). The first column in the data frame is named hospital, which contains the hospital name, and the second column is named state, which contains the 2-character abbreviation for the state name. Hospitals that do not have data on a particular outcome should be excluded from the set of hospitals when deciding the rankings.
Handling ties. The rankall function should handle ties in the 30-day mortality rates in the same way that the rankhospital function handles ties.
The function should use the following template.
rankall <- function(outcome, num = "best") {
## Read outcome data
}
## Check that state and outcome are valid
## For each state, find the hospital of the given rank
## Return a data frame with the hospital names and the
## (abbreviated) state name
NOTE: For the purpose of this part of the assignment (and for efficiency), your function should NOT call the rankhospital function from the previous section.
The function should check the validity of its arguments. If an invalid outcome value is passed to rankall, the function should throw an error via the stop function with the exact message invalid outcome. The num variable can take values best, worst, or an integer indicating the ranking (smaller numbers are better). If the number given by num is larger than the number of hospitals in that state, then the function should return NA.
Here is some sample output from the function.
> head(rankall("heart attack", 20), 10)
hospital state
AK AK
AL D W MCMILLAN MEMORIAL HOSPITAL AL
AR ARKANSAS METHODIST MEDICAL CENTER AR
AZ JOHN C LINCOLN DEER VALLEY HOSPITAL AZ
CA SHERMAN OAKS HOSPITAL CA
CO SKY RIDGE MEDICAL CENTER CO
CT MIDSTATE MEDICAL CENTER CT
DC DC
DE DE
FL SOUTH FLORIDA BAPTIST HOSPITAL FL
> tail(rankall("pneumonia", "worst"), 3)
hospital state
WI MAYO CLINIC HEALTH SYSTEM - NORTHLAND, INC WI
WV PLATEAU MEDICAL CENTER WV
WY NORTH BIG HORN HOSPITAL DISTRICT WY
> tail(rankall("heart failure"), 10)
hospital state
TN WELLMONT HAWKINS COUNTY MEMORIAL HOSPITAL TN
TX FORT DUNCAN MEDICAL CENTER TX
UT VA SALT LAKE CITY HEALTHCARE - GEORGE E. WAHLEN VA MEDICAL CENTER UT
VA SENTARA POTOMAC HOSPITAL VA
VI GOV JUAN F LUIS HOSPITAL & MEDICAL CTR VI
VT SPRINGFIELD HOSPITAL VT
WA HARBORVIEW MEDICAL CENTER WA
WI AURORA ST LUKES MEDICAL CENTER WI
WV FAIRMONT GENERAL HOSPITAL WV
WY CHEYENNE VA MEDICAL CENTER WY
rankall <- function(outcome, num="best") { if(num == "best"){num=1} #read outcome data and convert necessary columns to numeric hospital_data <- read.csv("hospital-data.csv") outcome_data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") suppressWarnings(outcome_data[, 11] <- as.numeric(outcome_data[, 11])) suppressWarnings(outcome_data[, 17] <- as.numeric(outcome_data[, 17])) suppressWarnings(outcome_data[, 26] <- as.numeric(outcome_data[, 26])) possible_outcomes <- c("heart attack", "heart failure", "pneumonia") if(any(possible_outcomes==outcome) == FALSE) { stop("invalid outcome") } outcome_data <- outcome_data[order(outcome_data[,7]),] #need to order by state, not in alpha order yet state_names <- unique(outcome_data[,7]) final_table <- data.frame(row.names = state_names) hospitals = c() states = c() if(outcome == "heart attack") { for(i in state_names){ state_temp <- outcome_data[outcome_data[,7]==i,] state_temp_ordered <- state_temp[order(state_temp[,11],na.last = NA,state_temp[,2]),] #sort and remove hospitals with no data if(num=="worst"){ state_temp_selected <- state_temp_ordered[,2][length(state_temp_ordered[,2])] hospitals <- append(hospitals,state_temp_selected[1]) }else { state_temp_selected <- state_temp_ordered[num,2] hospitals <- append(hospitals,state_temp_selected[1]) } } }else if(outcome == "heart failure") { for(i in state_names){ state_temp <- outcome_data[outcome_data[,7]==i,] state_temp_ordered <- state_temp[order(state_temp[,17],na.last = NA,state_temp[,2]),] #sort and remove hospitals with no data if(num =="worst"){ state_temp_selected <- state_temp_ordered[,2][length(state_temp_ordered[,2])] hospitals <- append(hospitals,state_temp_selected[1]) } else { state_temp_selected <- state_temp_ordered[num,2] hospitals <- append(hospitals,state_temp_selected[1]) } } } else if(outcome == "pneumonia") { for(i in state_names){ state_temp <- outcome_data[outcome_data[,7]==i,] state_temp_ordered <- state_temp[order(state_temp[,26],na.last = NA,state_temp[,2]),] #sort and remove hospitals with no data if(num =="worst"){ state_temp_selected <- state_temp_ordered[,2][length(state_temp_ordered[,2])] hospitals <- append(hospitals,state_temp_selected[1]) } else { state_temp_selected <- state_temp_ordered[num,2] hospitals <- append(hospitals,state_temp_selected[1]) } } } final_table$hospital <- hospitals final_table$state <- state_names final_table } head(rankall("heart attack", 20), 10)
## hospital state ## AK <NA> AK ## AL D W MCMILLAN MEMORIAL HOSPITAL AL ## AR ARKANSAS METHODIST MEDICAL CENTER AR ## AZ JOHN C LINCOLN DEER VALLEY HOSPITAL AZ ## CA SHERMAN OAKS HOSPITAL CA ## CO SKY RIDGE MEDICAL CENTER CO ## CT MIDSTATE MEDICAL CENTER CT ## DC <NA> DC ## DE <NA> DE ## FL SOUTH FLORIDA BAPTIST HOSPITAL FL
tail(rankall("pneumonia", "worst"), 3)
## hospital state ## WI MAYO CLINIC HEALTH SYSTEM - NORTHLAND, INC WI ## WV WELCH COMMUNITY HOSPITAL WV ## WY NORTH BIG HORN HOSPITAL DISTRICT WY
tail(rankall("heart failure"), 10)
## hospital state ## TN WELLMONT HAWKINS COUNTY MEMORIAL HOSPITAL TN ## TX FORT DUNCAN MEDICAL CENTER TX ## UT VA SALT LAKE CITY HEALTHCARE - GEORGE E. WAHLEN VA MEDICAL CENTER UT ## VA SENTARA POTOMAC HOSPITAL VA ## VI GOV JUAN F LUIS HOSPITAL & MEDICAL CTR VI ## VT SPRINGFIELD HOSPITAL VT ## WA HARBORVIEW MEDICAL CENTER WA ## WI AURORA ST LUKES MEDICAL CENTER WI ## WV FAIRMONT GENERAL HOSPITAL WV ## WY CHEYENNE VA MEDICAL CENTER WY