Map ICD-10 Codes to CCSR Categories — ccsr

Maps ICD-10-CM diagnosis codes or ICD-10-PCS procedure codes to their corresponding CCSR categories using a downloaded CCSR mapping file.

Usage

ccsr_map(
  data,
  code_col,
  map_df,
  type = NULL,
  default_only = FALSE,
  output_format = "long",
  keep_all = TRUE
)

Arguments

data: A data frame or tibble containing ICD-10 codes to be mapped.
code_col: Character string specifying the name of the column in data that contains the ICD-10 codes.
map_df: A tibble containing the CCSR mapping data, typically obtained from download_ccsr().
type: Character string specifying the type of mapping. Must be one of: "diagnosis" (or "dx") for ICD-10-CM codes, or "procedure" (or "pr") for ICD-10-PCS codes. If NULL (default), the function will attempt to infer the type from the mapping data frame.
default_only: Logical. For diagnosis codes only, if TRUE, returns only the default CCSR category (recommended for principal diagnosis analysis). If FALSE (default), returns all assigned CCSR categories including cross-classifications.
output_format: Character string specifying the output format. Must be one of: "long" (default) or "wide". "long" format duplicates records for each assigned CCSR category. "wide" format creates multiple columns (CCSR_1, CCSR_2, etc.) for multiple categories.
keep_all: Logical. If TRUE (default), returns all original columns from data plus the CCSR mapping columns. If FALSE, returns only the ICD-10 code column and CCSR mapping columns.

Value

A tibble with the original data plus CCSR mapping columns. The structure depends on output_format:

For "long" format: Each row represents one ICD-10 code and one CCSR category assignment (rows are duplicated for multiple categories).
For "wide" format: Each row represents one ICD-10 code with multiple CCSR category columns (CCSR_1, CCSR_2, etc.).

Details

CCSR allows for cross-classification, meaning a single ICD-10 code can map to multiple CCSR categories. The "long" format is recommended for analyses where you want to count all assigned CCSR categories, while "wide" format may be more convenient for patient-level analyses.

For diagnosis codes, CCSR also assigns a "default" category that is recommended for principal diagnosis analysis. Use default_only = TRUE to extract only this default category.

Examples

# \donttest{
# Download mapping file
dx_map <- download_ccsr("diagnosis")
#> Downloading from: https://hcup-us.ahrq.gov/toolssoftware/ccsr/DXCCSR-v2026-1.zip
#> Download complete: /tmp/Rtmp6OONtw/HCUPtools_cache/DXCCSR-v2026-1.zip
#> Reading mapping file: DXCCSR_v2026-1.csv

# Create sample data
sample_data <- tibble::tibble(
  patient_id = 1:3,
  icd10_code = c("E11.9", "I10", "M79.3")
)

# Map codes (long format - default)
mapped_long <- ccsr_map(
  data = sample_data,
  code_col = "icd10_code",
  map_df = dx_map
)

# Map codes (wide format)
mapped_wide <- ccsr_map(
  data = sample_data,
  code_col = "icd10_code",
  map_df = dx_map,
  output_format = "wide"
)

# Map codes (default category only)
mapped_default <- ccsr_map(
  data = sample_data,
  code_col = "icd10_code",
  map_df = dx_map,
  default_only = TRUE
)
# }