icdcomorbid (version 1.0.0)

icd9_to_comorbid: Find Comorbidities from ICD_9 Codes

Description

This function maps ICD_9 codes to comorbidities based on a provided mapping in order to indicate whether each comorbidity is present for each ID.

Usage

icd9_to_comorbid(df, idx, icd_cols, mapping, batch_size = 1000)

Value

A dataframe with comorbidities as columns and IDs as rows, with True or False values indicating whether each comorbidity is present for each ID.

Arguments

df

The dataframe containing the data.

idx

The name of the column representing the patient identifiers.

icd_cols

A character vector of the columns containing ICD codes.

mapping

The mapping of comorbidities to ICD codes (e.g., quan_elixhauser9, charlson9, custom list).

batch_size

An optional integer specifying the number of rows to process per batch. Default is 1000.

Details

This function assumes that the input dataframe is in wide format, where each row represents a unique identifier (ID), and each column contains a variable associated with that ID. The function maps the ICD_9 codes in the specified columns to comorbidities based on the provided mapping.

The mapping can be one of the following:

- Pre-defined mappings such as "quan_elixhauser9" or "charlson9", which are based on established comorbidity indices.

- Custom mappings (list), where each key represents a comorbidity and its value is a vector of ICD-9 codes associated with that comorbidity. The custom mapping codes may include up to 2 decimal places.

References

1. Quan, H., Sundararajan, V., Halfon, P., Fong, A., Burnand, B., Luthi, J. C., ... & Ghali, W. A. (2005). Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical care, 43(11), 1130-1139. 2. ICD: Python library for working with International Classification of Diseases (ICD) codes. Available online: https://github.com/mark-hoffmann/icd

Examples

df <- data.frame(ID = c(1, 2, 3),
                 icd_1 = c("410.x", "428.0", "496"),
                 icd_2 = c("428.33", "401.9", "493.90"))
# Using pre-existing mapping (e.g., charlson9 or quan_elixhauser9)
mapping <- "charlson9"
icd9_to_comorbid(df, "ID", c("icd_1", "icd_2"), mapping)

# Using custom mapping
custom_mapping <- list("Myocardial Infarction" = c("410.x", "412.x"),
                       "Congestive Heart Failure" = c("398.91", "402.01",
                       "402.11", "402.91", "404.01", "404.03",
                       "404.11", "404.13", "404.91", "404.93", "425.4",
                       "425.5", "425.6", "425.7", "425.8", "425.9", "428.x"))
icd9_to_comorbid(df, "ID", c("icd_1", "icd_2"), custom_mapping, batch_size = 2)