Validate and filter diagnostic data by selected ICD-10 or ICPC-2 codes

Usage

filter_diag_data(
  data,
  codes = NULL,
  pattern_codes = NULL,
  classification = "icd",
  id_col = "id",
  code_col = "code",
  date_col = NULL,
  diag_dates = NULL,
  rm_na = TRUE,
  add_description = FALSE,
  log_path = NULL
)

Arguments

data

A data frame containing pre-processed diagnostic data.

codes

A character vector. ICD-10 or ICPC-2 codes to validate and filter in data

pattern_codes

A character vector. Pattern of ICD-10 or ICPC-2 codes to validate and filter in data. For example, F84 will use all codes starting with F84 (F840, F841, F842, F844, etc).

classification

A character string. Classification used in diagnostic codes: ICD-10 or ICPC-2. Options are "icd" or "icpc". Default is "icd".

id_col

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

code_col

A character string. Name of the column containing the ICD-10 or ICPC-2 codes in data, default is "code"

date_col

A character string. Name of the column containing the date of the diagnostic event. Only needed i if you want to filter by diagnosis date. Default is NULL.

diag_dates

A character vector. Dates (years, months, etc) that you want to filter the diagnostic data by.

rm_na

Logical. Should rows with NA in the non-filtered columns be removed? Default is FALSE

add_description

Logical. If TRUE new column will be added with description of ICD-10 or ICPC-2 code. Note: not all code descriptions are available.

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

Filtered and validated diagnostic data frame containing only relevant observations based on diagnostic codes of interest.

Examples

# Validate that F45 and F84 are real codes/family of codes in ICD-10.
# Keep only rows with codes containing F45 and F84.

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

filtered_diag_df <-  filter_diag_data(data = diag_df,
                                 pattern_codes = c("F45", "F84"),
                                 id_col = "id",
                                 code_col = "code",
                                 log_path = log_file,
                                 rm_na = FALSE
                                 )
#> Checking that code exists in ICD-10 or ICPC-2 code list...
#> ✔ Selected codes/pattern are valid: F450, F451, F452, F453, F4530, F4531, F4532, F4533, F4534, F4538, F454, F458, F459, F840, F841, F842, F843, F844, F845, F848, F849
#> 
#> Filtering data by selected codes...
#> 
#> ────────────────────────────────────────────────────────────────────────────────
#> Diagnostic dataset successfully filtered
#> 
#> ℹ Filtered 117717 rows (97.9% removed)
#> 
#> ── Data Summary ────────────────────────────────────────────────────────────────
#> 
#> ── After filtering: 
#> ℹ Remaining number of rows: 2539
#> ℹ Remaining number of columns: 3
#> ℹ Unique IDs in dataset: 2464
#> ℹ Unique codes in dataset: 28
#> ℹ Codes in dataset: "F4520", "F454", "F840", "F845", "F4529", "F456", "F4541", "F841", "F4522", "F844", "F842", "F849", "F457", "F846", "F455", "F452", "F45", "F847", …, "F459", and "F843"
#> 
#> Rows: 2,539
#> Columns: 3
#> $ id        <chr> "P000000704", "P000000704", "P000000886", "P000001615", "P00…
#> $ code      <chr> "F4522", "F840", "F450", "F845", "F4520", "F455", "F457", "F…
#> $ diag_year <int> 2016, 2017, 2017, 2020, 2019, 2016, 2019, 2020, 2013, 2019, …