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Curate diagnostic data

Source: R/curate_diag_data.R
curate_diag_data.Rd

Curate diagnostic data

Usage

curate_diag_data(
  data,
  min_diag = 1,
  first_diag = TRUE,
  id_col = "id",
  code_col = "icd_code",
  date_col = "date",
  log_path = NULL
)

Arguments

data

A data frame containing pre-processed and validated diagnostic data.

min_diag

Integer. Number of minimum amount of diagnostic events. Default is 1.

first_diag

Logical. If TRUE, keep only information from the first recorded diagnostic event. Default set to TRUE. Default is TRUE.

id_col

A character string. Name of ID column in data, default is "id"

code_col

A character string. Name of column containing the ICD-10 codes in data, default is "icd_code"

date_col

A character string. Name of column containing the diagnostic date in data, default is "date"

log_path

A character string. Path to the log file to append function logs. Default is NULL.

  • If NULL, a new directory /log and file is created in the current working directory.

Value

Curated diagnostic data: minimum diagnostic events, and/or first ever diagnosis information

Examples

# Keep only curated diagnostic data
# for example minimum diagnostic events or first recorded diagnosis

log_file <- tempfile()
cat("Example log file", file = log_file)

curated_diag_df <- curate_diag_data(data = diag_df,
                               min_diag = 1,
                               first_diag = TRUE,
                               id_col = "id",
                               code_col = "code",
                               date_col = "diag_year",
                               log_path = log_file)
#> ✔ Filtered observations that do not have at least 1 diagnostic event
#> ✔ Summarized first diagnostic event information
#> 
#> ────────────────────────────────────────────────────────────────────────────────
#> Diagnostic dataset successfully curated and summarized
#> 
#> ℹ Filtered 90232 rows (75% removed)
#> 
#> ── Data Summary ────────────────────────────────────────────────────────────────
#> 
#> ── After filtering: 
#> ℹ Remaining number of rows: 30024
#> ℹ Remaining number of columns: 4
#> ℹ Unique IDs in dataset: 30024
#> ℹ ICD-10 codes in dataset: F726, F639, F543, F872, F868, F150, F323, F115, F959, F182, F913, F1620, F060, F337, F1319, F701, F8181, F965, …, F923, and F075
#> 
#> tibble [30,024 × 4] (S3: tbl_df/tbl/data.frame)
#>  $ id               : chr [1:30024] "P000000037" "P000000052" "P000000059" "P000000111" ...
#>  $ code             : chr [1:30024] "F750" "F035" "F198" "F230" ...
#>  $ y_diagnosis_first: int [1:30024] 2018 2012 2013 2012 2013 2012 2013 2013 2013 2013 ...
#>  $ diagnosis_count  : int [1:30024] 2 5 2 2 5 6 3 4 4 5 ...