Create Romano map of ICD-9-CM to Charlson comorbidities

Description

Function that creates a dataframe which links ICD-9-CM codes to the Charlson comorbidity categories using the Romano mapping.

Usage

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Arguments

icd9

a unique character vector of ICD-9-CM codes

Details

NOTE: The input vector of ICD-9-CM codes must be unique, because the output dataframe uses the ICD-9-CM code as row.name.

Uses regular expressions created from the paper by Romano in 1993.

ICD-9-CM codes must have periods removed. Diagnostic codes are prefixed with 'D' while procedure codes are prefixed with 'P'. So, diagnostic code 404.03 should be "D40403".

Value

A data frame, with ICD9 codes as row names and one logical column for each comorbidity in charlson_list

References

1. Romano PS, Roos LL, Jollis JG: Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. Journal of clinical epidemiology 1993; 46:1075-9; discussion 1081-90 http://www.ncbi.nlm.nih.gov/pubmed/8410092

See Also

icd9cm_charlson_quan, icd9cm_charlson_deyo, icd9cm_elixhauser_quan, icd9cm_elixhauser_ahrq37, charlson_weights,

Examples

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# Identify Charlson categories in ICD-9-CM listing
cases <- data.frame(id=c(1,1,1,2,2,2),
  icd9cm=c("D20206","D24220","D4439","D5064","DE8788","D40403"))
cases_with_cm <- merge(cases, icd9cm_charlson_romano(levels(cases$icd9cm)), 
  by.x="icd9cm", by.y="row.names", all.x=TRUE)

# generate crude comorbidity summary for each patient
library(plyr)
ddply(cases_with_cm, .(id), 
  function(x) { data.frame(lapply(x[,3:ncol(x)], any)) })

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