icd (version 3.2.0)

comorbid_pccc_dx: Calculate pediatric complex chronic conditions (PCCC) comorbidities

Description

Calculate pediatric complex chronic conditions (PCCC) comorbidities

Usage

comorbid_pccc_dx(x, visit_name = get_visit_name(x),
  icd_name = get_icd_name(x), short_code = guess_short(x, icd_name =
  icd_name), return_df = FALSE, return_binary = FALSE, ...)
icd9_comorbid_pccc_dx(x, visit_name = NULL, icd_name = NULL,
  short_code = guess_short(x, icd_name = icd_name), return_df = FALSE,
  return_binary = FALSE, ...)
icd10_comorbid_pccc_dx(x, visit_name = NULL, icd_name = NULL,
  short_code = guess_short(x, icd_name = icd_name), return_df = FALSE,
  return_binary = FALSE, ...)
icd9_comorbid_pccc_pcs(x, map, visit_name, icd_name, return_df = FALSE,
  return_binary = FALSE)
icd10_comorbid_pccc_pcs(x, map, visit_name, icd_name, return_df = FALSE,
  return_binary = FALSE)

Arguments

x

data.frame containing a column of patient-visit identifiers and a column of ICD codes. The data.frame should be in ‘long’ format, like the example vermont_dx data. If it is in ‘wide’ format, it must be converted to ‘long’ using wide_to_long before calling any comorbidity functions.

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.

icd_name

The name of the column in the data.frame which contains the ICD codes. This is a character vector of length one. If it is NULL, icd9 will attempt to guess the column name, looking for progressively less likely possibilities until it matches a single column. Failing this, it will take the first column in the data frame. Specifying the column using this argument avoids the guesswork.

short_code

single logical value which determines whether the ICD-9 code provided is in short (TRUE) or decimal (FALSE) form. Where reasonable, this is guessed from the input data.

return_df

single logical value, if TRUE, return the result as a data frame with the first column being the visit_id, and the second being the count. If visit_id was a factor or named differently in the input, this is preserved.

return_binary

Single logical value, if TRUE, the returned matrix or data.frame will be composed of 1 and 0, instead of TRUE and FALSE, respectively. This conversion can also be done by the internal functions icd:::logical_to_binary and icd:::binary_to_logical, or using other tools, e.g. apply(x, 2, as.integer)

...

arguments passed on to other functions

map

list of the comorbidities with each list item containing a vector of decimal ICD-9 codes. This is in the form of a list, with the names of the items corresponding to the comorbidities (e.g. ‘HTN’, or ‘diabetes’) and the contents of each list item being a character vector of short-form (no decimal place, zero left-padded) ICD codes. There is no default: the user should use the family of functions, e.g. comorbid_ahrq, since these also name the fields correctly, apply any hierarchical rules (see hierarchy below)

Functions

• icd9_comorbid_pccc_dx: Calculate PCCC comorbidities from ICD-9 diagnosis codes

• icd10_comorbid_pccc_dx: Calculate PCCC comorbidities from ICD-10 diagnosis codes

• icd9_comorbid_pccc_pcs: Calculate PCCC comorbidities from ICD-9 procedure codes

• icd10_comorbid_pccc_pcs: Calculate PCCC comorbidities from ICD-10 procedure codes

Examples

# NOT RUN {
# not pediatric data, but let's look for this example
head(icd9_comorbid_pccc_dx(wide_to_long(vermont_dx)))
# }