Objectives

Using the spatial visualization techniques, explore this data set on Pennsylvania hospitals (http://www.arcgis.com/home/item.html?id=eccee5dfe01e4c4283c9be0cfc596882). Create a series of 5 maps that highlight spatial differences in hospital service coverage for the state of PA.

library(ggplot2)
library(ggmap)
## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.
## Please cite ggmap if you use it! See citation("ggmap") for details.
library(foreign)
dat <- read.dbf("C:/Users/Richy/Downloads/pennsylv.dbf")

The dataset contains a number of variables about each hospital, many of them are clear and straight forward.

names(dat)
##   [1] "acc_trauma" "air_amb"    "als"        "arc_street" "arc_zone"  
##   [6] "bas_ls"     "bassinets"  "bb_id"      "bc_beds"    "bc_sus_bed"
##  [11] "beds_sus"   "birthing_r" "bone_marro" "burn_car"   "burn_care" 
##  [16] "card_beds"  "card_surge" "card_sus_b" "cardiac"    "cardiac_ca"
##  [21] "cardio_reh" "chemo"      "city"       "clin_lab"   "clin_psych"
##  [26] "county"     "countyname" "ct_scan"    "cty_key"    "cystoscopi"
##  [31] "deliv_rms"  "dental"     "detox_alc_" "diag_radio" "diag_xray" 
##  [36] "doh_hosp"   "doh_phone"  "emer_dept"  "endoscopie" "fac_id"    
##  [41] "facility"   "flu_old"    "fred_con_1" "fred_conta" "fred_email"
##  [46] "fred_fax"   "fred_hosp"  "fred_pager" "fred_phone" "gamma_knif"
##  [51] "gen_outpat" "gene_counc" "heart_tran" "helipad"    "hemodial_c"
##  [56] "hemodial_m" "hosp_id"    "hospice"    "hyper_cham" "icu"       
##  [61] "icu_beds"   "icu_sus_be" "inpat_flu_" "inpat_pneu" "kidney_tra"
##  [66] "labor_rms"  "lic_beds"   "lic_dent"   "lic_dos"    "lic_mds"   
##  [71] "lic_pod"    "linear_acc" "lithotrips" "liver_tran" "loc_method"
##  [76] "ltc"        "mcd"        "mcd_key"    "mcd_name"   "medical"   
##  [81] "mob_ccu"    "mob_icu"    "mri"        "ms1"        "neo2_beds" 
##  [86] "neo2_sus_b" "neo3_beds"  "neo3_sus_b" "neuro_surg" "neurology" 
##  [91] "obs_gyn"    "occ_ther"   "optometry"  "organ_bank" "ped_trauma"
##  [96] "pediatric"  "pet"        "pharmacy"   "phys_med"   "phys_ther" 
## [101] "podiatry"   "providerid" "psych"      "psych_inpa" "reg_trauma"
## [106] "resp_ther"  "so_flu_65u" "social_wor" "speech_pat" "street"    
## [111] "surgical"   "surgical_s" "thera_radi" "typ_org"    "typ_serv"  
## [116] "ultrasound" "x"          "y"          "zip"

I focussed on accident trauma hospitals in the Pennsylvania dataset.

Accident Trauma Hospitals in PA

There are around 32 hospitals spread around PA that have accident trauma care, with a higher concentration around Philadelphia.

subset1 <- subset(dat, acc_trauma == "Y")
qmplot(x, y, data = subset1, source = "google", maptype = "roadmap", legend = "none", colour = I("red"), mapcolor = "color", extent = "panel", main = "Accident Trauma Hospitals in PA", xlab = "Longitute", ylab = "Latitude", zoom = 7, , size = I(3))
## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.995052,-77.505472&zoom=7&size=640x640&scale=2&maptype=roadmap&language=en-EN&key=xxx-_9A77SuWa663qWHVIE9PZTupA

Accident Trauma Hospitals in Philly

Looking deeper at Philly, there are 8 accident trauma hospitals, with 4 hospitals around the downtown area.

subset2 <- subset(subset1, county == "Philadelphia")
qmplot(x, y, data = subset2, source = "google", maptype = "roadmap", legend = "none", colour = I("red"), mapcolor = "color", extent = "panel", main = "Accident Trauma Hospitals in Philly", xlab = "Longitute", ylab = "Latitude", zoom = 11, size = I(3))
## Source : https://maps.googleapis.com/maps/api/staticmap?center=40.009619,-75.087825&zoom=11&size=640x640&scale=2&maptype=roadmap&language=en-EN&key=xxx-_9A77SuWa663qWHVIE9PZTupA

Typically in accident trauma cases, MRI and surgery are important steps, followed by physical therapy to complete rehabilitation. Hence, I focussed on these 3 aspects in the data.

Accident Trauma Hospitals with MRI Facilities in Philly

7 out of 8 accident trauma hospitals had MRI facilities.

subset3 <- subset(subset2, mri == "Y")
qmplot(x, y, data = subset3, source = "google", maptype = "roadmap", legend = "none", colour = I("red"), mapcolor = "color", extent = "panel", main = "Accident Trauma Hospitals with MRI Facilities in Philly", xlab = "Longitute", ylab = "Latitude", zoom = 12, size = I(3))
## Source : https://maps.googleapis.com/maps/api/staticmap?center=39.992417,-75.159234&zoom=12&size=640x640&scale=2&maptype=roadmap&language=en-EN&key=xxx-_9A77SuWa663qWHVIE9PZTupA

Accident Trauma Hospitals with Surgical Facilities in Philly

5 out of 8 accident trauma hospitals had surgical facilities.

subset4 <- subset(subset2, surgical == "Y")
qmplot(x, y, data = subset4, source = "google", maptype = "roadmap", legend = "none", colour = I("red"), mapcolor = "color", extent = "panel", main = "Accident Trauma Hospitals with Surgical Facilities in Philly", xlab = "Longitute", ylab = "Latitude", zoom = 12, size = I(3))
## Source : https://maps.googleapis.com/maps/api/staticmap?center=39.992417,-75.16827&zoom=12&size=640x640&scale=2&maptype=roadmap&language=en-EN&key=xxx-_9A77SuWa663qWHVIE9PZTupA

Accident Trauma Hospitals with Physical Therapy Facilities in Philly

7 out of 8 accident trauma hospitals had physical therapy facilities.

subset5 <- subset(subset2, phys_ther == "Y")
qmplot(x, y, data = subset5, source = "google", maptype = "roadmap", legend = "none", colour = I("red"), mapcolor = "color", extent = "panel", main = "Accident Trauma Hospitals with Physical Therapy Facilities in Philly", xlab = "Longitute", ylab = "Latitude", zoom = 12, size = I(3))
## Source : https://maps.googleapis.com/maps/api/staticmap?center=39.992417,-75.159234&zoom=12&size=640x640&scale=2&maptype=roadmap&language=en-EN&key=xxx-_9A77SuWa663qWHVIE9PZTupA

Accident Trauma Hospitals with MRI, Surgical and Physical Therapy Facilities in Philly

5 out of 8 accident trauma hospitals had MRI, surgical and physical therapy facilities. I would suggest these 5 hospitals as they have a complete set of facilities to treat and rehab accident trauma patients.

subset6 <- subset(subset2, phys_ther == "Y" & surgical == "Y" & mri == "Y")
qmplot(x, y, data = subset6, source = "google", maptype = "roadmap", legend = "none", colour = I("red"), mapcolor = "color", extent = "panel", main = "Accident Trauma Hospitals with MRI, Surgical and Physical Therapy Facilities in Philly", xlab = "Longitute", ylab = "Latitude", zoom = 12, size = I(3))
## Source : https://maps.googleapis.com/maps/api/staticmap?center=39.992417,-75.16827&zoom=12&size=640x640&scale=2&maptype=roadmap&language=en-EN&key=xxx-_9A77SuWa663qWHVIE9PZTupA