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merge_AN_and_FQHC_lists_2019_medicare.R
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merge_AN_and_FQHC_lists_2019_medicare.R
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library(methods)
source("e:/CT_APCD/Sai/data-organization/R/utils.R")
pkgs <- c("data.table", "tidyverse", "reshape2", "readxl",
NULL)
need.packages(pkgs)
outdir <- output_dir("NPI-Attribution/")
cols <- c("NPI",
# "LastName",
# "FirstName",
"Taxonomy1",
"spec0",
# "Specialty",
"entityName")
## FQHC
fqhcdir <- input_dir("E:/CT_APCD/Sai/MedicareProvider_ Lists_2018_2019/2019Lists_ForAttribution/2019Lists_ForAttribution/FQHC_Commercial_Medicare_2019/")
fqhcfiles <- list.files(fqhcdir)
## 1
fqhcfiles[1]
fqhc1 <- data.table(readxl::read_excel(paste0(fqhcdir,
"CHCINC_2018_2019_FinalForAttribution.xlsx")))
names(fqhc1)
fqhc1[, `:=` (NPI = as.character(`Clinician NPI (Type 1) (Required)`),
entityName = "CHCINC",
Taxonomy1 = taxo)]
fqhc1 <- fqhc1[, cols, with = FALSE]
head(fqhc1)
## 2
fqhcfiles[2]
fqhc2 <-data.table(readxl::read_excel(paste0(fqhcdir,
"CHSHartford_2019_FinalForAttribution.xlsx")))
names(fqhc2)
fqhc2[, `:=` (NPI = as.character(NPI),
entityName = "CHSHartford",
Taxonomy1 = taxo)]
fqhc2 <- fqhc2[, cols, with = FALSE]
head(fqhc2)
## 3
fqhcfiles[3]
fqhc3 <-data.table(readxl::read_excel(paste0(fqhcdir,
"CHWTorrington_Provider Listing 2019_FinalForAttribution.xls")))
names(fqhc3)
fqhc3[, `:=` (NPI = as.character(NPI),
entityName = "CHWTorrington",
Taxonomy1 = taxo)]
fqhc3 <- fqhc3[, cols, with = FALSE]
head(fqhc3)
## 4
fqhcfiles[4]
fqhc4 <-data.table(readxl::read_excel(paste0(fqhcdir,
"CIFC Danbury_HealthCare Quality Scorecard_2019_FinalForAttribution.xlsx")))
names(fqhc4)
fqhc4[, `:=` (NPI = as.character(`Provider NPI`),
entityName = "CIFC",
Taxonomy1 = taxo)]
fqhc4 <- fqhc4[, cols, with = FALSE]
head(fqhc4)
## 5
fqhcfiles[5]
fqhc5 <-data.table(readxl::read_excel(paste0(fqhcdir,
"CornellScottHC Medical Providers 2019_FinalForAttribution.xlsx")))
names(fqhc5)
fqhc5[, `:=` (NPI = as.character(NPI),
entityName = "CornellScottHC",
Taxonomy1 = taxo)]
fqhc5 <- fqhc5[, cols, with = FALSE]
head(fqhc5)
## 6
fqhcfiles[6]
fqhc6 <-data.table(readxl::read_excel(paste0(fqhcdir,
"Fair Haven Provider List 2019_FinalForAttributio.xlsx")))
names(fqhc6)
fqhc6[, `:=` (NPI = as.character(`Clinician NPI (Type 1) (Required)`),
entityName = "Fairhaven",
Taxonomy1 = taxo)]
fqhc6 <- fqhc6[, cols, with = FALSE]
head(fqhc6)
## 7
fqhcfiles[7]
fqhc7 <-data.table(readxl::read_excel(paste0(fqhcdir,
"FQHC Provider NPI Lists by Entity_CharterOak_FirstChoice_2017_UseFor_2018_2019 (1).xlsx")))
names(fqhc7)
fqhc7[, `:=` (NPI = as.character(NPI),
entityName = "CharterOak",
Taxonomy1 = taxo,
spec0 = new.spec0)]
fqhc7 <- fqhc7[, cols, with = FALSE]
head(fqhc7)
## 8
fqhcfiles[8]
fqhc8 <-data.table(readxl::read_excel(paste0(fqhcdir,
"Generations_2019_FinalForAttribution.xlsx")))
names(fqhc8)
fqhc8[, `:=` (NPI = as.character(`Clinician NPI (Type 1) (Required)`),
entityName = "Generations",
Taxonomy1 = taxo)]
fqhc8 <- fqhc8[, cols, with = FALSE]
head(fqhc8)
## 9
fqhcfiles[9]
fqhc9 <-data.table(read_excel(paste0(fqhcdir,
"Intercommunity_primary providers for 2018 2019_FinalForAttribution.xlsx")))
names(fqhc9)
fqhc9[, `:=` (NPI = as.character(NPI),
entityName = "Intercommunity",
Taxonomy1 = taxo)]
fqhc9 <- fqhc9[, cols, with = FALSE]
head(fqhc9)
## 10
fqhcfiles[10]
fqhc10 <-data.table(read_excel(paste0(fqhcdir,
"MPS_2019_FinalForAttribution.xlsx")))
names(fqhc10)
fqhc10[, `:=` (NPI = as.character(`NPI #`),
entityName = "MPS",
Taxonomy1 = taxo)]
fqhc10 <- fqhc10[, cols, with = FALSE]
head(fqhc10)
## 11
fqhcfiles[11]
fqhc11 <-data.table(read_excel(paste0(fqhcdir,
"Norwalk_2019_FinalForAttribution.xlsx")))
names(fqhc11)
fqhc11[, `:=` (NPI = as.character(`Clinician NPI (Type 1) (Required)`),
entityName = "Norwalk",
Taxonomy1 = taxo)]
fqhc11 <- fqhc11[, cols, with = FALSE]
head(fqhc11)
## 12
fqhcfiles[12]
fqhc12 <-data.table(read_excel(paste0(fqhcdir,
"OptimusProvider List_2019_FinalForAttribution.xlsx")))
names(fqhc12)
fqhc12[, `:=` (NPI = as.character(`Clinician NPI (Type 1) (Required)`),
entityName = "Optimus",
Taxonomy1 = taxo)]
fqhc12 <- fqhc12[, cols, with = FALSE]
head(fqhc12)
## 13
fqhcfiles[13]
fqhc13 <-data.table(read_excel(paste0(fqhcdir,
"SouthwestCHC providers List_2019_FinalForAttribution.xlsx")))
names(fqhc13)
fqhc13[, `:=` (NPI = as.character(`Clinician NPI (Type 1) (Required)`),
entityName = "SouthwestCHC",
Taxonomy1 = taxo)]
fqhc13 <- fqhc13[, cols, with = FALSE]
head(fqhc13)
## 14
fqhcfiles[14]
fqhc14 <-data.table(read_excel(paste0(fqhcdir,
"StaywellOnline Healthcare Quality Scorecard Provider Lists_2019_FinalForAttribution.xlsx")))
names(fqhc14)
fqhc14[, `:=` (NPI = as.character(NPI),
entityName = "Staywell",
Taxonomy1 = taxo)]
fqhc14 <- fqhc14[, cols, with = FALSE]
head(fqhc14)
## 15
fqhcfiles[15]
fqhc15 <-data.table(read_excel(paste0(fqhcdir,
"UCFSHealthcare_2019_FinalForAttribution.xlsx")))
names(fqhc15)
fqhc15[, `:=` (NPI = as.character(`Clinician NPI (Type 1) (Required)`),
entityName = "UCFS",
Taxonomy1 = taxo)]
fqhc15 <- fqhc15[, cols, with = FALSE]
head(fqhc15)
## 16
fqhcfiles[16]
fqhc16 <-data.table(read_excel(paste0(fqhcdir,
"Wheeler_2019_FinalForAttribution.xlsx")))
names(fqhc16)
fqhc16[, `:=` (NPI = as.character(npi),
entityName = "Wheele",
Taxonomy1 = taxo)]
fqhc16 <- fqhc16[, cols, with = FALSE]
head(fqhc16)
## all fqhc
fqhc <- rbind(fqhc1, fqhc2, fqhc3, fqhc4, fqhc5, fqhc6, fqhc7, fqhc8, fqhc9, fqhc10,
fqhc11, fqhc12, fqhc13, fqhc14, fqhc15, fqhc16)
fqhc[, entityName := paste0("FQHC_", entityName)]
## AN
andir <- input_dir("E:/CT_APCD/Sai/MedicareProvider_ Lists_2018_2019/2019Lists_ForAttribution/2019Lists_ForAttribution/AN_Medicare_2019/")
anfiles <- list.files(andir)
length(anfiles)
## 1
anfiles[1]
an1 <- data.table(readxl::read_excel(paste0(andir,
"2019 Middlesex Providers_FinalForAttribution.xlsx")))
names(an1)
an1[, `:=` (NPI = as.character(NPI),
entityName = "Middlesex",
Taxonomy1 = taxo)]
an1 <- an1[, cols, with = FALSE]
head(an1)
## 2
anfiles[2]
an2 <-data.table(readxl::read_excel(paste0(andir,
"AllianceWaterbury_2019_FinalForAttribution.xlsx")))
names(an2)
an2[, `:=` (NPI = as.character(NPI),
entityName = "AllianceWaterbury",
Taxonomy1 = taxo)]
an2 <- an2[, cols, with = FALSE]
head(an2)
## 3
anfiles[3]
an3 <-data.table(readxl::read_excel(paste0(andir,
"CMG_2019_Commercial_Medicare_FinalForAttribution.xls")))
names(an3)
an3[, `:=` (NPI = as.character(NPI),
entityName = "CMG",
Taxonomy1 = taxo)]
an3 <- an3[, cols, with = FALSE]
head(an3)
## 4
anfiles[4]
an4 <-data.table(readxl::read_excel(paste0(andir,
"DAYKIMBALL_ Provider NPI Lists_CommericalMedicare2019_FinalForAttribution.xlsx")))
names(an4)
an4[, `:=` (NPI = as.character(NPI),
entityName = "DAYKIMBAL",
Taxonomy1 = taxo)]
an4 <- an4[, cols, with = FALSE]
head(an4)
## 5
anfiles[5]
an5 <-data.table(readxl::read_excel(paste0(andir,
"EasternCTHealthNetwork_2019_FinalForAttribution.xlsx")))
names(an5)
an5[, `:=` (NPI = as.character(NPI),
entityName = "ECHN",
Taxonomy1 = taxo)]
an5 <- an5[, cols, with = FALSE]
head(an5)
## 6
anfiles[6]
an6 <-data.table(readxl::read_excel(paste0(andir,
"GriffinProviders_2018_2019_FinalForAttribution.xlsx")))
names(an6)
an6[, `:=` (NPI = as.character(`NPI #`),
entityName = "Griffin",
Taxonomy1 = taxo_Uconn,
spec0 = spec0_Uconn)]
an6 <- an6[, cols, with = FALSE]
head(an6)
## 7
anfiles[7]
an7 <-data.table(readxl::read_excel(paste0(andir,
"HHCICP_C_MC_2019_FinalForAttribution.xlsx")))
names(an7)
an7[, `:=` (NPI = as.character(NPI),
entityName = "HHCIC",
Taxonomy1 = taxo)]
an7 <- an7[, cols, with = FALSE]
head(an7)
## 8
anfiles[8]
an8 <-data.table(readxl::read_excel(paste0(andir,
"MPS_2019_FinalForAttribution.xlsx")))
names(an8)
an8[, `:=` (NPI = as.character(`NPI #`),
entityName = "MPS",
Taxonomy1 = taxo)]
an8 <- an8[, cols, with = FALSE]
head(an8)
## 9
anfiles[9]
an9 <-data.table(read_excel(paste0(andir,
"NEMedicalGroup_C_MC_2019_FinalForAttribution.xlsx")))
names(an9)
an9[, `:=` (NPI = as.character(NPI),
entityName = "NEMG",
Taxonomy1 = taxo)]
an9 <- an9[, cols, with = FALSE]
head(an9)
## 10 ## Practitioner NPI
anfiles[10]
an10 <-data.table(read_excel(paste0(andir,
"ProHealth_PCPs as of 12.31.2019_FinalForAttribution.xlsx")))
names(an10)
an10[, `:=` (NPI = as.character(`Practitioner NPI`),
entityName = "ProHealth",
Taxonomy1 = taxo)]
an10 <- an10[, cols, with = FALSE]
head(an10)
## 11
anfiles[11]
an11 <-data.table(read_excel(paste0(andir,
"Soundview__CommericalMedicare_2019_FinalForAttribution.xlsx")))
names(an11)
an11[, `:=` (NPI = as.character(NPI),
entityName = "Soundview",
Taxonomy1 = taxo)]
an11 <- an11[, cols, with = FALSE]
head(an11)
## 12 # No NPI
anfiles[12]
an12 <-data.table(read_excel(paste0(andir,
"Stamford_2019_FinalForAttribution.xlsx")))
names(an12)
an12[, `:=` (NPI = as.character(NPI),
entityName = "Stamford",
Taxonomy1 = taxo_Uconn)]
an12 <- an12[, cols, with = FALSE]
head(an12)
## 13
anfiles[13]
an13 <-data.table(read_excel(paste0(andir,
"Starling_2019_FinalForAttribution.xlsx")))
names(an13)
an13[, `:=` (NPI = as.character(NPI),
entityName = "Starling",
Taxonomy1 = taxo)]
an13 <- an13[, cols, with = FALSE]
head(an13)
## 14
anfiles[14]
an14 <-data.table(read_excel(paste0(andir,
"STFrancis Provider List 2018_19_FinalForAttribution.xlsx")))
names(an14)
an14[, `:=` (NPI = as.character(NPI),
entityName = "STFrancis",
Taxonomy1 = taxo)]
an14 <- an14[, cols, with = FALSE]
head(an14)
## 15
anfiles[15]
an15 <-data.table(read_excel(paste0(andir,
"StMary_2018_2019_Medicare_FinalForAttribution.xlsx")))
names(an15)
an15[, `:=` (NPI = as.character(NPI),
entityName = "StMary",
Taxonomy1 = taxo)]
an15 <- an15[, cols, with = FALSE]
head(an15)
## 16
anfiles[16]
an16 <-data.table(read_excel(paste0(andir,
"STVincent_C_MC_2019_FinalForAttribution.xlsx")))
names(an16)
an16[, `:=` (NPI = as.character(NPI),
entityName = "STVincen",
Taxonomy1 = taxo)]
an16 <- an16[, cols, with = FALSE]
head(an16)
## 17
anfiles[17]
an17 <-data.table(read_excel(paste0(andir,
"WesternCTHealthNetwork_Medicare_2019_FinalForAttibution.xlsx")))
names(an17)
an17[, `:=` (NPI = as.character(NPI),
entityName = "WCHN",
Taxonomy1 = taxo)]
an17 <- an17[, cols, with = FALSE]
head(an17)
## 18
anfiles[18]
an18 <-data.table(read_excel(paste0(andir,
"WestMedHistorical Roster 2019_FinalForAttribution.xlsx")))
names(an18)
an18[, `:=` (NPI = as.character(`NPI #`),
entityName = "WestMedHistorical",
Taxonomy1 = taxo)]
an18 <- an18[, cols, with = FALSE]
head(an18)
## 19
anfiles[19]
an19 <-data.table(read_excel(paste0(andir,
"Yale_Commerical_Medicare_2019_FinalForAttribution.xlsx")))
names(an19)
an19[, `:=` (NPI = as.character(NPI_NUMBER),
entityName = "Yale",
Taxonomy1 = taxo, spec0 = Spec0)]
an19 <- an19[, cols, with = FALSE]
head(an19)
## all an
an <- rbind(an1, an2, an3, an4, an5, an6, an7, an8, an9, an10,
an11, an12, an13, an14, an15, an16, an17, an18, an19)
an[, entityName := paste0("AN_", entityName)]
## combine two tables
datall <- rbind(an, fqhc)[, value := 1]
datall <- datall[!is.na(NPI)]
datall <- datall[NPI != 0]
entitynames <- as.character(datall[, unique(entityName)])
othercolnames <- c("NPI",
"Taxonomy1")
dat_wide <- dcast(datall,
NPI + Taxonomy1 + spec0 ~ entityName) %>%
data.table
dat_wide[, Total := rowSums(.SD, na.rm = TRUE),
.SDcols = entitynames,
by = othercolnames]
dat_wide[is.na(dat_wide)] <- 0
# nps <- fread("E:/CT_APCD/shared/intermediate_data/APCD_modified/provider/nppes_1129.csv",
# colClasses = "character",
# select = c("NPI",
# "Taxonomy1"))
# tmp <- nps[NPI %in% dat_wide[Taxonomy1 == 0]$NPI]
# dat_wide[Taxonomy1 == 0] <- nps[dat_wide[Taxonomy1 == 0], on = "NPI"]
fwrite(dat_wide,
file = paste0(outdir, "NPI_WholeSet_2019_mc.csv"))
## modify nppes
nppes <- fread("E:/CT_APCD/shared/intermediate_data/APCD_modified/provider/nppes_0613.csv",
colClasses = "character",
header = TRUE,
encoding = "UTF-8")
add1 <- datall[!NPI %in% nppes$NPI]
add_names1 <- names(add1)[names(add1) %in% names(nppes)]
add1 <- add1[, add_names1, with = FALSE]
nppes_new <- rbind(nppes, add1, fill = TRUE)
fwrite(nppes_new,
file = "E:/CT_APCD/shared/intermediate_data/APCD_modified/provider/nppes_1129.csv")
## modify nppes
provider <- fread("E:/CT_APCD/shared/intermediate_data/APCD_modified/provider/provider_0613.csv",
colClasses = "character",
header = TRUE,
encoding = "UTF-8")
add2 <- datall[!NPI %in% provider$NPI]
add_names2 <- names(add2)[names(add2) %in% names(provider)]
add2 <- add2[, add_names2, with = FALSE]
provider_new <- rbind(provider, add2, fill = TRUE)
fwrite(provider_new,
file = "E:/CT_APCD/shared/intermediate_data/APCD_modified/provider/provider_1129.csv")