icd (version 3.2.0)

factor_split_rcpp: Split data based on codes

Description

Using C++ because I also want to quickly return the visits corresponding to the NA or non-NA factor elements. This is half-way to implementing the core comorbidity calculation all in C++.

Usage

factor_split_rcpp(df, relevant, id_name, code_name)

Arguments

df

A data.frame, with a visit column (name given by visit_name), and a code column (name given by code_name -- not icd_name in this function). The code column must be a factor.

relevant

A character vector containing the factor levels of interest.

code_name

String with name of column containing the codes.

visit_name

The name of the column in the data frame which contains the patient or visit identifier. Typically this is the visit identifier, since patients come leave and enter hospital with different ICD-9 codes. It is a character vector of length one. If left empty, or NULL, then an attempt is made to guess which field has the ID for the patient encounter (not a patient ID, although this can of course be specified directly). The guesses proceed until a single match is made. Data frames may be wide with many matching fields, so to avoid false positives, anything but a single match is rejected. If there are no successful guesses, and visit_id was not specified, then the first column of the data frame is used.

Value

Returns a list with two components:

1. A reduced data frame, with only those rows where are least one visit had a relevant code

2. A character vector with all the visits where there were no matching codes.

Examples

# NOT RUN {
  df <- data.frame(visit_id = factor(c("visit1", "visit2", "visit1")),
                   icd_code = factor(c("410", "0010", "E999")))
  icd:::factor_split_rcpp(df, "410", "visit_id", "icd_code")
# }
# NOT RUN {
R -e "devtools::load_all();devtools::test(filter='github')"
R -e "devtools::load_all();icd9_comorbid_ahrq(data.frame(a='vis', b='0010'))"
# }