icd (version 3.0.0)

van_walraven: Calculate van Walraven Elixhauser Score

Description

van Walraven Elixhauser score is calculated from the Quan revision of Elixhauser's ICD-9 mapping. This function allows for the hierarchical exclusion of less severe versions of comorbidities when their more severe version is also present via the hierarchy argument. For the Elixhauser comorbidities, this is diabetes v. complex diabetes and solid tumor v. metastatic tumor

Usage

van_walraven(x, visit_name = NULL, return_df = FALSE,
  stringsAsFactors = getOption("stringsAsFactors"), ...)
# S3 method for data.frame
van_walraven(x, visit_name = NULL, return_df = FALSE,
  stringsAsFactors = getOption("stringsAsFactors"), ...)
van_walraven_from_comorbid(x, visit_name = NULL, hierarchy = FALSE)
icd_van_walraven.data.frame(...)
icd_van_walraven(...)
icd_van_walraven_from_comorbid(...)

Arguments

x

data frame containing a column of visit or patient identifiers, and a column of ICD-9 codes. It may have other columns which will be ignored. By default, the first column is the patient identifier and is not counted. If visit_name is not specified, the first column is used.

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.

return_df

single logical value, if true, a two column data frame will be returned, with the first column named as in input data frame (i.e. visit_name), containing all the visits, and the second column containing the Charlson Comorbidity Index.

stringsAsFactors

Single logical value, describing whether the resulting data frame should have strings, e.g. visit_id converted to factor. Default is to follow the current session option. This is identical to the argument used in, among other base functions as.data.frame.

...

arguments passed on to other functions

hierarchy

single logical value that defaults to TRUE, in which case the hierarchy defined for the mapping is applied. E.g. in Elixhauser, you can't have uncomplicated and complicated diabetes both flagged.

Methods (by class)

• data.frame: van Walraven scores from data frame of visits and ICD-9 codes

Deprecated function names

Future versions of icd will drop the icd_ prefix. For example, charlson should be used in favor of icd_charlson. To distinguish icd function calls, consider using the namespace prefix icd:: instead, e.g., icd::charlson. Functions which specifically operate on either ICD-9 or ICD-10 codes or their subtypes will retain the prefix. E.g. icd9_comorbid_ahrq. icd specific classes also retain the prefix, e.g., icd_wide_data.

Future versions of icd will drop the icd_ prefix. For example, charlson should be used in favor of icd_charlson. To distinguish icd function calls, consider using the namespace prefix icd:: instead, e.g., icd::charlson. Functions which specifically operate on either ICD-9 or ICD-10 codes or their subtypes will retain the prefix. E.g. icd9_comorbid_ahrq. icd specific classes also retain the prefix, e.g., icd_wide_data.

Future versions of icd will drop the icd_ prefix. For example, charlson should be used in favor of icd_charlson. To distinguish icd function calls, consider using the namespace prefix icd:: instead, e.g., icd::charlson. Functions which specifically operate on either ICD-9 or ICD-10 codes or their subtypes will retain the prefix. E.g. icd9_comorbid_ahrq. icd specific classes also retain the prefix, e.g., icd_wide_data.

References

van Walraven C, Austin PC, Jennings A, Quan H, Forster AJ. A Modification to the Elixhauser Comorbidity Measures Into a Point System for Hospital Death Using Administrative Data. Med Care. 2009; 47(6):626-633. http://www.ncbi.nlm.nih.gov/pubmed/19433995

Examples

# NOT RUN {
mydf <- data.frame(visit_name = c("a", "b", "c"),
                   icd9 = c("412.93", "441", "042"))
van_walraven(mydf)
# or calculate comorbodities first:
cmb <- icd9_comorbid_quan_elix(mydf, short_code = FALSE, hierarchy = TRUE)
vwr <- van_walraven_from_comorbid(cmb)
stopifnot(identical(van_walraven(mydf), vwr))

# alternatively return as data frame in 'tidy' format
van_walraven(mydf, return_df = TRUE)
# }