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## Main Function
#' Identify CCSR codes corresponding to ICD-10 codes
#'
#' @param workset Dataset with ICD-10 codes
#' @param dxs List of column name(s) of ICD-10 codes within workset
#' @param example indicator if running an example, default is FALSE
#'
#' @return A list of CCSR codes corresponding to the ICD-10 codes
#' @export
#'
#' @examples
#'
#' # Example dataset
#' id<-c(1:2)
#' dx1<-c("A000","B0189")
#' dx2<-c("A157","E133591")
#' workset<-data.frame(id,dx1,dx2)
#'
#' dxs<-c("dx1","dx2")
#'
#' # Convert to CCSR codes
#' CCSRfind(workset=workset,dxs=dxs,example=TRUE)
CCSRfind<-function(workset,dxs, example=FALSE){
XX<-nrow(Legend)
YY<-nrow(LegendExtend)
if(example==TRUE){
XX<-5
YY<-2
}
if(length(dxs==1)){
dxs<-c(dxs,dxs)
}
##For short codes classification
for(i in 1:XX){
codecol<-DXCCSR$ICD10[DXCCSR$CCSRCat==Legend$CCSRCat[i]]
if(length(codecol)<=1000){
hh<-knitr::combine_words(codecol,sep="|",and="")
workset[[Legend$CCSRCat[i]]]<-disc(workset,dxs,hh)
Legend[["Proportion"]][i]<-sum(workset[[Legend$CCSRCat[i]]])/nrow(workset)
#print(i)
#print(Legend[["Proportion"]][i])
}
}
##For long codes classification
for(i in 1:YY){
resvec<-numeric(nrow(workset))
codecol<-DXCCSR$ICD10[DXCCSR$CCSRCat==LegendExtend$CCSRCat[i]]
JJ<-floor(length(codecol)/1000)
for(j in 1:(JJ+1)){
if(j<(JJ+1)){
codecolJ<-codecol[c(1:1000)]
codecol<-codecol[-c(1:1000)]
}
if(j==(JJ+1)){
codecolJ<-codecol
}
hh<-knitr::combine_words(codecolJ,sep="|",and="")
resvec<-cbind(resvec,disc(workset,dxs,hh))
#print(c(j,JJ))
}
workset[[LegendExtend$CCSRCat[i]]]<-apply(resvec,1,max)
LegendExtend[["Proportion"]][i]<-sum(workset[[LegendExtend$CCSRCat[i]]])/nrow(workset)
}
LegendFin<-rbind(Legend[Legend$codecolvec<=1000,],LegendExtend)
LegendFin<-LegendFin[LegendFin$Proportion>0,]
if(example==TRUE){
LegendFin<-NULL
}
return(list(workset,LegendFin))
}
# Suppress R CMD check note about the global variable
utils::globalVariables("DXCCSR")
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