R/eci.R
In caimiao0714/MiaoCom: An R package for calculating comorbidity indexes for epidemiologists
Defines functions
eci
Documented in
eci
#' To calculate the Elixhauser Comorbidity Index
#'
#' @author Miao Cai <email: miao.cai@outlook.com>
#' @description This file aims to calculate the Elixhauser Comorbidity Index.
#' @note The Elixhauser Comorbidity Index does not include age as a component of the index.
#' @param data Your data file in which Elixhauser Comorbidity Index is to be calculated
#' @param comorbidity A vector of all comorbidity variables
#' @return data: a new data.frame named "data". This data frame contains a new variable "Elix_Index": The Elixhauser Comorbidity Index, developed by Anne Elixhauser in 1998
#' @references Elixhauser, A., Steiner, C., Harris, D. R., & Coffey, R. M. (1998). Comorbidity measures for use with administrative data. Medical care, 36(1), 8-27.
#' @references van Walraven, C., Austin, P. C., Jennings, A., Quan, H., & Forster, A. J. (2009). A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Medical care, 626-633.
#' @references Quan, H., Sundararajan, V., Halfon, P., Fong, A., Burnand, B., Luthi, J. C., ... & Ghali, W. A. (2005). Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical care, 1130-1139.
#' @importFrom magrittr %>%
#' @importFrom dplyr mutate_if
#' @export eci
#'
eci <- function(data, comorbidity) {
### PART A: SUBSETTING DATA---------------------------
data_comorbidity <- subset(data, select = comorbidity)# subset the whole dataset into "data_comorbidity": subset data that only contains comorbidities
data_comorbidity %>% dplyr::mutate_if(is.factor, as.character) -> data_comorbidity # this converts factor values into characters
data_comorbidity[is.na(data_comorbidity)] <- 'NA' #imputate missing values with zeros
dim_comorbidity <- dim(data_comorbidity)# save the dimensionality of comorbidity subset data
unlisted_data <- unlist(data_comorbidity)# unlist the comorbidity subset data(converts the data into a vector. Vectorization speeds up the functions)
unlisted_data <- toupper(unlisted_data)
### PART B: FILTERING COMORBIDITIES---------------------------
##1:CHF_Elix, Congestive heart failure
bidata_com <- grepl('I09\\.9|I11\\.0|I13\\.0|I13\\.2|I25\\.5|I42\\.0|I42\\.5|I42\\.6|I42\\.7|I42\\.8|I42\\.9|P29\\.0|I43|I50', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Congestive heart failure" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$CHF_Elix <- rowSums(bidata_com)
data$CHF_Elix[data$CHF_Elix >= 1] <- 1
#2: CA_Elix, Cardiac arrhythmias
bidata_com <- grepl('I44\\.1|I44\\.2|I44\\.3|I45\\.6|I45\\.9|R00\\.0|R00\\.1|R00\\.8|T82\\.1|Z45\\.0|Z95\\.0|I47|I48|I49', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Cardiac arrhythmias" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$CA_Elix <- rowSums(bidata_com)
data$CA_Elix[data$CA_Elix >= 1] <- 1
#3:VD_Elix, Valvular disease
bidata_com <- grepl('A52\\.0|I09\\.1|I09\\.8|Q23\\.0|Q23\\.1|Q23\\.2|Q23\\.3|Z95\\.2|Z95\\.3|Z95\\.4|I05|I06|I07|I08|I34|I35|I36|I37|I38|I39', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$VD_Elix <- rowSums(bidata_com)
data$VD_Elix[data$VD_Elix >= 1] <- 1
#4\\.PCD_Elix, Pulmonary circulation disorders
bidata_com <- grepl('I28\\.0|I28\\.8|I28\\.9|I26|I27', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Pulmonary circulation disorders" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$PCD_Elix <- rowSums(bidata_com)
data$PCD_Elix[data$PCD_Elix >= 1] <- 1
#5:PVD_Elix, Peripheral vascular disorders
bidata_com <- grepl('I73\\.1|I73\\.8|I73\\.9|I77\\.1|I79\\.0|I79\\.2|K55\\.1|K55\\.8|K55\\.9|Z95\\.8|Z95\\.9|I70|I71', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$PVD_Elix <- rowSums(bidata_com)
data$PVD_Elix[data$PVD_Elix >= 1] <- 1
#6: Hypertensionun_Elix, Hypertension, uncomplicated
bidata_com <- grepl('I10', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Hypertension, uncomplicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Hypertensionun_Elix <- rowSums(bidata_com)
data$Hypertensionun_Elix[data$Hypertensionun_Elix >= 1] <- 1
#7: Hypertension_Elix, Hypertension, complicated
bidata_com <- grepl('I11|I12|I13|I15', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Hypertension, complicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Hypertension_Elix <- rowSums(bidata_com)
data$Hypertension_Elix[data$Hypertension_Elix >= 1] <- 1
#8: Paralysis_Elix
bidata_com <- grepl('G04\\.1|G11\\.4|G80\\.1|G80\\.2|G83\\.9|G83\\.0|G83\\.1|G83\\.2|G83\\.3|G83\\.4|G81|G82', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Paralysis" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Paralysis_Elix <- rowSums(bidata_com)
data$Paralysis_Elix[data$Paralysis_Elix >= 1] <- 1
#9: OND_Elix, Other neurological disorders
bidata_com <- grepl('G25\\.4|G25\\.5|G31\\.2|G31\\.8|G31\\.9|G93\\.1|G93\\.4|R47\\.0|G10|G20|G35|G41|G11|G21|G36|R56|G12|G22|G37|G13|G32|G40', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Other neurological disorders" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$OND_Elix <- rowSums(bidata_com)
data$OND_Elix[data$OND_Elix >= 1] <- 1
#10: CPD_Elix, Chronic pulmonary disease
bidata_com <- grepl('I27\\.8|I27\\.9|J68\\.4|J70\\.1|J70\\.3|J40|J60|J41|J61|J42|J62|J43|J63|J44|J64|J45|J65|J46|J66|J47|J67', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Chronic pulmonary disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$CPD_Elix <- rowSums(bidata_com)
data$CPD_Elix[data$CPD_Elix >= 1] <- 1
#11:DMun_Elix, Diabetes, uncomplicated
bidata_com <- grepl('E10\\.0|E10\\.1|E10\\.9|E11\\.0|E11\\.1|E11\\.9|E12\\.0|E12\\.1|E12\\.9|E13\\.0|E13\\.1|E13\\.9|E14\\.0|E14\\.1|E14\\.9', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Diabetes, uncomplicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$DMun_Elix <- rowSums(bidata_com)
data$DMun_Elix[data$DMun_Elix >= 1] <- 1
#12: DM_Elix, Diabetes, complicated
bidata_com <- grepl('E10\\.2|E11\\.2|E12\\.2|E13\\.2|E14\\.2|E10\\.3|E11\\.3|E12\\.3|E13\\.3|E14\\.3|E10\\.4|E11\\.4|E12\\.4|E13\\.4|E14\\.4|E10\\.5|E11\\.5|E12\\.5|E13\\.5|E14\\.5|E10\\.6|E11\\.6|E12\\.6|E13\\.6|E14\\.6|E10\\.7|E11\\.7|E12\\.7|E13\\.7|E14\\.7|E10\\.8|E11\\.8|E12\\.8|E13\\.8|E14\\.8', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Diabetes, complicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$DM_Elix <- rowSums(bidata_com)
data$DM_Elix[data$DM_Elix >= 1] <- 1
#13: Hypothyroidism_Elix
bidata_com <- grepl('E89\\.0|E00|E01|E02|E03', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Hypothyroidism_Elix" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Hypothyroidism_Elix <- rowSums(bidata_com)
data$Hypothyroidism_Elix[data$Hypothyroidism_Elix >= 1] <- 1
#14: Renal_Elix, Renal failure
bidata_com <- grepl('I12\\.0|I13\\.1|N25\\.0|Z49\\.0|Z49\\.1|Z49\\.2|Z94\\.0|Z99\\.2|N18|N19', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Renal failure" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Renal_Elix <- rowSums(bidata_com)
data$Renal_Elix[data$Renal_Elix >= 1] <- 1
#15: LD_Elix, Liver disease
bidata_com <- grepl('I86\\.4|I98\\.2|K71\\.1|K71\\.3|K71\\.4|K71\\.5|K71\\.7|K76\\.0|Z94\\.4|K76\\.2|K76\\.3|K76\\.4|K76\\.5|K76\\.6|K76\\.7|K76\\.8|K76\\.9|B18|I85|K70|K72|K73|K74', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Liver disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$LD_Elix <- rowSums(bidata_com)
data$LD_Elix[data$LD_Elix >= 1] <- 1
#16: PUD_Elix, Peptic ulcer disease excluding bleeding
bidata_com <- grepl('K25\\.7|K25\\.9|K26\\.7|K26\\.9|K27\\.7|K27\\.9|K28\\.7|K28\\.9', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Peptic ulcer disease excluding bleeding" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$PUD_Elix <- rowSums(bidata_com)
data$PUD_Elix[data$PUD_Elix >= 1] <- 1
#17: AIDS_Elix, AIDS/HIV
bidata_com <- grepl('B20|B21|B22|B24', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "AIDS/HIV" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$AIDS_Elix <- rowSums(bidata_com)
data$AIDS_Elix[data$AIDS_Elix >= 1] <- 1
#18: Lymphoma_Elix
bidata_com <- grepl('C90\\.0|C90\\.2|C81|C82|C83|C84|C85|C88|C96', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Lymphoma" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Lymphoma_Elix <- rowSums(bidata_com)
data$Lymphoma_Elix[data$Lymphoma_Elix >= 1] <- 1
#19: Metastatic_Elix, Metastatic cancer
bidata_com <- grepl('C77|C78|C79|C80', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Metastatic cancer" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Metastatic_Elix <- rowSums(bidata_com)
data$Metastatic_Elix[data$Metastatic_Elix >= 1] <- 1
#20: Solid_Elix, Solid tumor without metastasis，
bidata_com <- grepl('C00|C01|C02|C03|C04|C05|C06|C07|C08|C09|C10|C11|C12|C13|C14|C15|C16|C17|C18|C19|C20|C21|C22|C23|C24|C25|C26|C30|C31|C32|C33|C34|C37|C38|C39|C40|C41|C43|C45|C46|C47|C48|C49|C50|C51|C52|C53|C54|C55|C56|C57|C58|C60|C61|C62|C63|C64|C65|C66|C67|C68|C69|C70|C71|C72|C73|C74|C75|C76|C97', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Solid_Elix" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Solid_Elix <- rowSums(bidata_com)
data$Solid_Elix[data$Solid_Elix >= 1] <- 1
#21: Rheumatoid_Elix, Rheumatoid arthritis/collagen vascular diseases
bidata_com <- grepl('L94\\.0|L94\\.1|L94\\.3|M46\\.1|M46\\.8|M46\\.9|M12\\.0|M12\\.3|M31\\.0|M31\\.1|M31\\.2|M31\\.3|M32|M33|M34|M35|M45|M05|M06|M08|M30', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Rheumatoid arthritis/collagen vascular diseases" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Rheumatoid_Elix <- rowSums(bidata_com)
data$Rheumatoid_Elix[data$Rheumatoid_Elix >= 1] <- 1
#22: Coagulopathy_Elix
bidata_com <- grepl('D69\\.1|D69\\.3|D69\\.4|D69\\.5|D69\\.6|D65|D66|D67|D68', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Coagulopathy" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Coagulopathy_Elix <- rowSums(bidata_com)
data$Coagulopathy_Elix[data$Coagulopathy_Elix >= 1] <- 1
#23: Obesity_Elix
bidata_com <- grepl('E66', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Obesity" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Obesity_Elix <- rowSums(bidata_com)
data$Obesity_Elix[data$Obesity_Elix >= 1] <- 1
#24: Weight_Elix, Weight loss
bidata_com <- grepl('R63\\.4|E40", "E41", "E42", "E43", "E44", "E45", "E46", "R64', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Weight_Elix <- rowSums(bidata_com)
data$Weight_Elix[data$Weight_Elix >= 1] <- 1
#25: Fluid_Elix, Fluid and electrolyte disorders
bidata_com <- grepl('E22\\.2|E86|E87', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Fluid_Elix <- rowSums(bidata_com)
data$Fluid_Elix[data$Fluid_Elix >= 1] <- 1
#26: Blood_Elix, Blood loss anemia
bidata_com <- grepl('D50\\.0', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Blood_Elix <- rowSums(bidata_com)
data$Blood_Elix[data$Blood_Elix >= 1] <- 1
#27: Deficiency_Elix, Deficiency anemia
bidata_com <- grepl('D50\\.8|D50\\.9|D51|D52|D53', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Deficiency_Elix <- rowSums(bidata_com)
data$Deficiency_Elix[data$Deficiency_Elix >= 1] <- 1
#28: Alcohol_Elix, Alcohol abuse
bidata_com <- grepl('G62\\.1|I42\\.6|K29\\.2|K70\\.0|K70\\.3|K70\\.9|Z50\\.2|Z71\\.4|Z72\\.1|F10|E52|T51',
unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Alcohol abuse" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Alcohol_Elix <- rowSums(bidata_com)
data$Alcohol_Elix[data$Alcohol_Elix >= 1] <- 1
#29: Drug_Elix, Drug abuse
bidata_com <- grepl('Z71\\.5|Z72\\.2|F11|F12|F13|F14|F15|F16|F18|F19', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Drug abuse" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Drug_Elix <- rowSums(bidata_com)
data$Drug_Elix[data$Drug_Elix >= 1] <- 1
#30: Psychoses_Elix
bidata_com <- grepl('F30\\.2|F31\\.2|F31\\.5|F20|F22|F23|F24|F25|F28|F29', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Psychoses" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Psychoses_Elix <- rowSums(bidata_com)
data$Psychoses_Elix[data$Psychoses_Elix >= 1] <- 1
#31: Depression_Elix
bidata_com <- grepl('F20\\.4|F31\\.3|F31\\.4|F31\\.5|F34\\.1|F41\\.2|F43\\.2|F32|F33', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Depression" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Depression_Elix <- rowSums(bidata_com)
data$Depression_Elix[data$Depression_Elix >= 1] <- 1
# About age: age is not included in calculating the Elixhauser Comorbidity Index.
###PART D---WEIGHTED SUM---------------------------
# Refer to:
# Elixhauser, A., Steiner, C., Harris, D. R., & Coffey, R. M. (1998). Comorbidity measures for use with administrative data. Medical care, 36(1), 8-27.
# The weights refer to:
# van Walraven, C., Austin, P. C., Jennings, A., Quan, H., & Forster, A. J. (2009). A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Medical care, 626-633.
data$Elix_Index <- 7 * data$CHF_Elix + 5 * data$CA_Elix - 1 * data$VD_Elix + 4 * data$PCD_Elix + 2 * data$PVD_Elix + 0 * data$Hypertensionun_Elix + 0 * data$Hypertension_Elix + 7 * data$Paralysis_Elix + 6 * data$OND_Elix + 3 * data$CPD_Elix + 0 * data$DMun_Elix + 0 * data$DM_Elix + 0 * data$Hypothyroidism_Elix + 5 * data$Renal_Elix + 11 * data$LD_Elix + 0 * data$PUD_Elix + 0 * data$AIDS_Elix + 9 * data$Lymphoma_Elix + 12 * data$Metastatic_Elix + 4 * data$Solid_Elix + 0 * data$Rheumatoid_Elix + 3 * data$Coagulopathy_Elix - 4 * data$Obesity_Elix + 6 * data$Weight_Elix + 5 * data$Fluid_Elix - 2 * data$Blood_Elix - 2 * data$Deficiency_Elix + 0 * data$Alcohol_Elix - 7 * data$Drug_Elix + 0 * data$Psychoses_Elix - 3 * data$Depression_Elix
# All previous ICD-10 coding algorithms were refered to:
# Quan, H., Sundararajan, V., Halfon, P., Fong, A., Burnand, B., Luthi, J. C., ... & Ghali, W. A. (2005). Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical care, 1130-1139.
return(data)
}
caimiao0714/MiaoCom documentation built on Oct. 8, 2021, 9:17 p.m.
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Defines functions eci
Documented in eci
#' To calculate the Elixhauser Comorbidity Index
#'
#' @author Miao Cai <email: miao.cai@outlook.com>
#' @description This file aims to calculate the Elixhauser Comorbidity Index.
#' @note The Elixhauser Comorbidity Index does not include age as a component of the index.
#' @param data Your data file in which Elixhauser Comorbidity Index is to be calculated
#' @param comorbidity A vector of all comorbidity variables
#' @return data: a new data.frame named "data". This data frame contains a new variable "Elix_Index": The Elixhauser Comorbidity Index, developed by Anne Elixhauser in 1998
#' @references Elixhauser, A., Steiner, C., Harris, D. R., & Coffey, R. M. (1998). Comorbidity measures for use with administrative data. Medical care, 36(1), 8-27.
#' @references van Walraven, C., Austin, P. C., Jennings, A., Quan, H., & Forster, A. J. (2009). A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Medical care, 626-633.
#' @references Quan, H., Sundararajan, V., Halfon, P., Fong, A., Burnand, B., Luthi, J. C., ... & Ghali, W. A. (2005). Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical care, 1130-1139.
#' @importFrom magrittr %>%
#' @importFrom dplyr mutate_if
#' @export eci
#'
eci <- function(data, comorbidity) {
### PART A: SUBSETTING DATA---------------------------
data_comorbidity <- subset(data, select = comorbidity)# subset the whole dataset into "data_comorbidity": subset data that only contains comorbidities
data_comorbidity %>% dplyr::mutate_if(is.factor, as.character) -> data_comorbidity # this converts factor values into characters
data_comorbidity[is.na(data_comorbidity)] <- 'NA' #imputate missing values with zeros
dim_comorbidity <- dim(data_comorbidity)# save the dimensionality of comorbidity subset data
unlisted_data <- unlist(data_comorbidity)# unlist the comorbidity subset data(converts the data into a vector. Vectorization speeds up the functions)
unlisted_data <- toupper(unlisted_data)
### PART B: FILTERING COMORBIDITIES---------------------------
##1:CHF_Elix, Congestive heart failure
bidata_com <- grepl('I09\\.9|I11\\.0|I13\\.0|I13\\.2|I25\\.5|I42\\.0|I42\\.5|I42\\.6|I42\\.7|I42\\.8|I42\\.9|P29\\.0|I43|I50', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Congestive heart failure" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$CHF_Elix <- rowSums(bidata_com)
data$CHF_Elix[data$CHF_Elix >= 1] <- 1
#2: CA_Elix, Cardiac arrhythmias
bidata_com <- grepl('I44\\.1|I44\\.2|I44\\.3|I45\\.6|I45\\.9|R00\\.0|R00\\.1|R00\\.8|T82\\.1|Z45\\.0|Z95\\.0|I47|I48|I49', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Cardiac arrhythmias" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$CA_Elix <- rowSums(bidata_com)
data$CA_Elix[data$CA_Elix >= 1] <- 1
#3:VD_Elix, Valvular disease
bidata_com <- grepl('A52\\.0|I09\\.1|I09\\.8|Q23\\.0|Q23\\.1|Q23\\.2|Q23\\.3|Z95\\.2|Z95\\.3|Z95\\.4|I05|I06|I07|I08|I34|I35|I36|I37|I38|I39', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$VD_Elix <- rowSums(bidata_com)
data$VD_Elix[data$VD_Elix >= 1] <- 1
#4\\.PCD_Elix, Pulmonary circulation disorders
bidata_com <- grepl('I28\\.0|I28\\.8|I28\\.9|I26|I27', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Pulmonary circulation disorders" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$PCD_Elix <- rowSums(bidata_com)
data$PCD_Elix[data$PCD_Elix >= 1] <- 1
#5:PVD_Elix, Peripheral vascular disorders
bidata_com <- grepl('I73\\.1|I73\\.8|I73\\.9|I77\\.1|I79\\.0|I79\\.2|K55\\.1|K55\\.8|K55\\.9|Z95\\.8|Z95\\.9|I70|I71', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$PVD_Elix <- rowSums(bidata_com)
data$PVD_Elix[data$PVD_Elix >= 1] <- 1
#6: Hypertensionun_Elix, Hypertension, uncomplicated
bidata_com <- grepl('I10', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Hypertension, uncomplicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Hypertensionun_Elix <- rowSums(bidata_com)
data$Hypertensionun_Elix[data$Hypertensionun_Elix >= 1] <- 1
#7: Hypertension_Elix, Hypertension, complicated
bidata_com <- grepl('I11|I12|I13|I15', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Hypertension, complicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Hypertension_Elix <- rowSums(bidata_com)
data$Hypertension_Elix[data$Hypertension_Elix >= 1] <- 1
#8: Paralysis_Elix
bidata_com <- grepl('G04\\.1|G11\\.4|G80\\.1|G80\\.2|G83\\.9|G83\\.0|G83\\.1|G83\\.2|G83\\.3|G83\\.4|G81|G82', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Paralysis" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Paralysis_Elix <- rowSums(bidata_com)
data$Paralysis_Elix[data$Paralysis_Elix >= 1] <- 1
#9: OND_Elix, Other neurological disorders
bidata_com <- grepl('G25\\.4|G25\\.5|G31\\.2|G31\\.8|G31\\.9|G93\\.1|G93\\.4|R47\\.0|G10|G20|G35|G41|G11|G21|G36|R56|G12|G22|G37|G13|G32|G40', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Other neurological disorders" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$OND_Elix <- rowSums(bidata_com)
data$OND_Elix[data$OND_Elix >= 1] <- 1
#10: CPD_Elix, Chronic pulmonary disease
bidata_com <- grepl('I27\\.8|I27\\.9|J68\\.4|J70\\.1|J70\\.3|J40|J60|J41|J61|J42|J62|J43|J63|J44|J64|J45|J65|J46|J66|J47|J67', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Chronic pulmonary disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$CPD_Elix <- rowSums(bidata_com)
data$CPD_Elix[data$CPD_Elix >= 1] <- 1
#11:DMun_Elix, Diabetes, uncomplicated
bidata_com <- grepl('E10\\.0|E10\\.1|E10\\.9|E11\\.0|E11\\.1|E11\\.9|E12\\.0|E12\\.1|E12\\.9|E13\\.0|E13\\.1|E13\\.9|E14\\.0|E14\\.1|E14\\.9', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Diabetes, uncomplicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$DMun_Elix <- rowSums(bidata_com)
data$DMun_Elix[data$DMun_Elix >= 1] <- 1
#12: DM_Elix, Diabetes, complicated
bidata_com <- grepl('E10\\.2|E11\\.2|E12\\.2|E13\\.2|E14\\.2|E10\\.3|E11\\.3|E12\\.3|E13\\.3|E14\\.3|E10\\.4|E11\\.4|E12\\.4|E13\\.4|E14\\.4|E10\\.5|E11\\.5|E12\\.5|E13\\.5|E14\\.5|E10\\.6|E11\\.6|E12\\.6|E13\\.6|E14\\.6|E10\\.7|E11\\.7|E12\\.7|E13\\.7|E14\\.7|E10\\.8|E11\\.8|E12\\.8|E13\\.8|E14\\.8', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Diabetes, complicated" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$DM_Elix <- rowSums(bidata_com)
data$DM_Elix[data$DM_Elix >= 1] <- 1
#13: Hypothyroidism_Elix
bidata_com <- grepl('E89\\.0|E00|E01|E02|E03', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Hypothyroidism_Elix" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Hypothyroidism_Elix <- rowSums(bidata_com)
data$Hypothyroidism_Elix[data$Hypothyroidism_Elix >= 1] <- 1
#14: Renal_Elix, Renal failure
bidata_com <- grepl('I12\\.0|I13\\.1|N25\\.0|Z49\\.0|Z49\\.1|Z49\\.2|Z94\\.0|Z99\\.2|N18|N19', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Renal failure" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Renal_Elix <- rowSums(bidata_com)
data$Renal_Elix[data$Renal_Elix >= 1] <- 1
#15: LD_Elix, Liver disease
bidata_com <- grepl('I86\\.4|I98\\.2|K71\\.1|K71\\.3|K71\\.4|K71\\.5|K71\\.7|K76\\.0|Z94\\.4|K76\\.2|K76\\.3|K76\\.4|K76\\.5|K76\\.6|K76\\.7|K76\\.8|K76\\.9|B18|I85|K70|K72|K73|K74', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Liver disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$LD_Elix <- rowSums(bidata_com)
data$LD_Elix[data$LD_Elix >= 1] <- 1
#16: PUD_Elix, Peptic ulcer disease excluding bleeding
bidata_com <- grepl('K25\\.7|K25\\.9|K26\\.7|K26\\.9|K27\\.7|K27\\.9|K28\\.7|K28\\.9', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Peptic ulcer disease excluding bleeding" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$PUD_Elix <- rowSums(bidata_com)
data$PUD_Elix[data$PUD_Elix >= 1] <- 1
#17: AIDS_Elix, AIDS/HIV
bidata_com <- grepl('B20|B21|B22|B24', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "AIDS/HIV" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$AIDS_Elix <- rowSums(bidata_com)
data$AIDS_Elix[data$AIDS_Elix >= 1] <- 1
#18: Lymphoma_Elix
bidata_com <- grepl('C90\\.0|C90\\.2|C81|C82|C83|C84|C85|C88|C96', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Lymphoma" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Lymphoma_Elix <- rowSums(bidata_com)
data$Lymphoma_Elix[data$Lymphoma_Elix >= 1] <- 1
#19: Metastatic_Elix, Metastatic cancer
bidata_com <- grepl('C77|C78|C79|C80', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Metastatic cancer" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Metastatic_Elix <- rowSums(bidata_com)
data$Metastatic_Elix[data$Metastatic_Elix >= 1] <- 1
#20: Solid_Elix, Solid tumor without metastasis，
bidata_com <- grepl('C00|C01|C02|C03|C04|C05|C06|C07|C08|C09|C10|C11|C12|C13|C14|C15|C16|C17|C18|C19|C20|C21|C22|C23|C24|C25|C26|C30|C31|C32|C33|C34|C37|C38|C39|C40|C41|C43|C45|C46|C47|C48|C49|C50|C51|C52|C53|C54|C55|C56|C57|C58|C60|C61|C62|C63|C64|C65|C66|C67|C68|C69|C70|C71|C72|C73|C74|C75|C76|C97', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Solid_Elix" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Solid_Elix <- rowSums(bidata_com)
data$Solid_Elix[data$Solid_Elix >= 1] <- 1
#21: Rheumatoid_Elix, Rheumatoid arthritis/collagen vascular diseases
bidata_com <- grepl('L94\\.0|L94\\.1|L94\\.3|M46\\.1|M46\\.8|M46\\.9|M12\\.0|M12\\.3|M31\\.0|M31\\.1|M31\\.2|M31\\.3|M32|M33|M34|M35|M45|M05|M06|M08|M30', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Rheumatoid arthritis/collagen vascular diseases" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Rheumatoid_Elix <- rowSums(bidata_com)
data$Rheumatoid_Elix[data$Rheumatoid_Elix >= 1] <- 1
#22: Coagulopathy_Elix
bidata_com <- grepl('D69\\.1|D69\\.3|D69\\.4|D69\\.5|D69\\.6|D65|D66|D67|D68', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Coagulopathy" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Coagulopathy_Elix <- rowSums(bidata_com)
data$Coagulopathy_Elix[data$Coagulopathy_Elix >= 1] <- 1
#23: Obesity_Elix
bidata_com <- grepl('E66', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Obesity" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Obesity_Elix <- rowSums(bidata_com)
data$Obesity_Elix[data$Obesity_Elix >= 1] <- 1
#24: Weight_Elix, Weight loss
bidata_com <- grepl('R63\\.4|E40", "E41", "E42", "E43", "E44", "E45", "E46", "R64', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Weight_Elix <- rowSums(bidata_com)
data$Weight_Elix[data$Weight_Elix >= 1] <- 1
#25: Fluid_Elix, Fluid and electrolyte disorders
bidata_com <- grepl('E22\\.2|E86|E87', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Fluid_Elix <- rowSums(bidata_com)
data$Fluid_Elix[data$Fluid_Elix >= 1] <- 1
#26: Blood_Elix, Blood loss anemia
bidata_com <- grepl('D50\\.0', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Blood_Elix <- rowSums(bidata_com)
data$Blood_Elix[data$Blood_Elix >= 1] <- 1
#27: Deficiency_Elix, Deficiency anemia
bidata_com <- grepl('D50\\.8|D50\\.9|D51|D52|D53', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Valvular disease" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Deficiency_Elix <- rowSums(bidata_com)
data$Deficiency_Elix[data$Deficiency_Elix >= 1] <- 1
#28: Alcohol_Elix, Alcohol abuse
bidata_com <- grepl('G62\\.1|I42\\.6|K29\\.2|K70\\.0|K70\\.3|K70\\.9|Z50\\.2|Z71\\.4|Z72\\.1|F10|E52|T51',
unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Alcohol abuse" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Alcohol_Elix <- rowSums(bidata_com)
data$Alcohol_Elix[data$Alcohol_Elix >= 1] <- 1
#29: Drug_Elix, Drug abuse
bidata_com <- grepl('Z71\\.5|Z72\\.2|F11|F12|F13|F14|F15|F16|F18|F19', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Drug abuse" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Drug_Elix <- rowSums(bidata_com)
data$Drug_Elix[data$Drug_Elix >= 1] <- 1
#30: Psychoses_Elix
bidata_com <- grepl('F30\\.2|F31\\.2|F31\\.5|F20|F22|F23|F24|F25|F28|F29', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Psychoses" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Psychoses_Elix <- rowSums(bidata_com)
data$Psychoses_Elix[data$Psychoses_Elix >= 1] <- 1
#31: Depression_Elix
bidata_com <- grepl('F20\\.4|F31\\.3|F31\\.4|F31\\.5|F34\\.1|F41\\.2|F43\\.2|F32|F33', unlisted_data, perl = TRUE, ignore.case = TRUE) # regular expression to find out cases with "Depression" comorbidity ICD-10 codes
dim(bidata_com) <- dim_comorbidity # convert the comorbidity data vector back into data.frame
data$Depression_Elix <- rowSums(bidata_com)
data$Depression_Elix[data$Depression_Elix >= 1] <- 1
# About age: age is not included in calculating the Elixhauser Comorbidity Index.
###PART D---WEIGHTED SUM---------------------------
# Refer to:
# Elixhauser, A., Steiner, C., Harris, D. R., & Coffey, R. M. (1998). Comorbidity measures for use with administrative data. Medical care, 36(1), 8-27.
# The weights refer to:
# van Walraven, C., Austin, P. C., Jennings, A., Quan, H., & Forster, A. J. (2009). A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Medical care, 626-633.
data$Elix_Index <- 7 * data$CHF_Elix + 5 * data$CA_Elix - 1 * data$VD_Elix + 4 * data$PCD_Elix + 2 * data$PVD_Elix + 0 * data$Hypertensionun_Elix + 0 * data$Hypertension_Elix + 7 * data$Paralysis_Elix + 6 * data$OND_Elix + 3 * data$CPD_Elix + 0 * data$DMun_Elix + 0 * data$DM_Elix + 0 * data$Hypothyroidism_Elix + 5 * data$Renal_Elix + 11 * data$LD_Elix + 0 * data$PUD_Elix + 0 * data$AIDS_Elix + 9 * data$Lymphoma_Elix + 12 * data$Metastatic_Elix + 4 * data$Solid_Elix + 0 * data$Rheumatoid_Elix + 3 * data$Coagulopathy_Elix - 4 * data$Obesity_Elix + 6 * data$Weight_Elix + 5 * data$Fluid_Elix - 2 * data$Blood_Elix - 2 * data$Deficiency_Elix + 0 * data$Alcohol_Elix - 7 * data$Drug_Elix + 0 * data$Psychoses_Elix - 3 * data$Depression_Elix
# All previous ICD-10 coding algorithms were refered to:
# Quan, H., Sundararajan, V., Halfon, P., Fong, A., Burnand, B., Luthi, J. C., ... & Ghali, W. A. (2005). Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical care, 1130-1139.
return(data)
}
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