I do not think that you need regular expressions for your problem.
Please see the below:
> d0 <- dat_unmatched
> tmp <- apply(d0, 1, function(x){
+ first <- substr(x,1,1)
+ idx <- which(c("T", "Y") == first)
+ comb <- paste(x[idx[1]-1], x[idx], collapse=" ")
+ unlist(strsplit(comb, " "))
+ })
>
Not sure how much help it will be but there is a package on CRAN called
icd9. Although clearly the codes are different in ICD 10 it may give you
some hints. I suppose you could even email the maintainer to see whether
there is an icd10 in the pipeline.
On 17/12/2014 20:14, Robert Strother wrot
"out of your depth" does not serve as a legitimate excuse -- for me
anyway. There are many good tutorials on regular expressions out
there. Go through one. Ditto with R data handling. "An Introduction to
R" (ships with R) is one that's right at hand.
Although others may be more inclined than I am
I have a large dataset (~50,000 rows, 96 columns), of hospital
administrative data.
many of the columns are clinical coding of inpatient event (using ICD-10).
A simplified example of the data is below
> dput(dat_unmatched)
structure(list(ID = structure(c(4L, 3L, 2L, 1L), .Label = c("BCM3455",
"BZD
4 matches
Mail list logo
