R/checkVerbatimEndDate.R

In DrugExposureDiagnostics: Diagnostics for OMOP Common Data Model Drug Records

# Copyright 2024 DARWIN EU®
#
# This file is part of DrugExposureDiagnostics
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#' Check the verbatim_end_date field
#'
#' @param cdm CDMConnector reference object
#' @param drugRecordsTable a modified version of the drug exposure table, default "ingredient_drug_records"
#' @param byConcept whether to get result by drug concept
#' @param sampleSize the sample size given in execute checks
#'
#' @return a table with the stats about the verbatim_end_date
checkVerbatimEndDate <- function(cdm,
                                 drugRecordsTable = "ingredient_drug_records",
                                 byConcept = TRUE,
                                 sampleSize = 10000) {
  errorMessage <- checkmate::makeAssertCollection()
  checkDbType(cdm = cdm, messageStore = errorMessage)
  checkTableExists(
    cdm = cdm, tableName = drugRecordsTable,
    messageStore = errorMessage
  )
  checkLogical(byConcept, messageStore = errorMessage)
  checkmate::reportAssertions(collection = errorMessage)

  if (isTRUE(byConcept)) {
    grouping <- c(
      "drug_concept_id",
      "drug",
      "ingredient_concept_id",
      "ingredient"
    )
  } else {
    grouping <- c("ingredient_concept_id", "ingredient")
  }

  total <- cdm[[drugRecordsTable]] %>%
    dplyr::summarise(total = dplyr::n()) %>%
    dplyr::pull()

  records <- cdm[[drugRecordsTable]] %>%
    dplyr::group_by(dplyr::across(dplyr::all_of(grouping))) %>%
    dplyr::summarise(
      minimum_verbatim_end_date = min(.data$verbatim_end_date, na.rm = T),
      maximum_verbatim_end_date = max(.data$verbatim_end_date, na.rm = T),
      n_records = as.integer(dplyr::n()),
      n_sample = .env$sampleSize,
      n_person = dplyr::n_distinct(.data$person_id),
      n_missing_verbatim_end_date = sum(dplyr::case_when(
        is.na(.data$verbatim_end_date) ~ 1,
        !is.na(.data$verbatim_end_date) ~ 0
      ), na.rm = T),
      n_not_missing_verbatim_end_date = sum(dplyr::case_when(
        !is.na(.data$verbatim_end_date) ~ 1,
        is.na(.data$verbatim_end_date) ~ 0
      ), na.rm = T),
      n_verbatim_end_date_equal_to_drug_exposure_end_date = sum(dplyr::case_when(
        .data$drug_exposure_end_date == .data$verbatim_end_date ~ 1,
        .data$drug_exposure_end_date != .data$verbatim_end_date ~ 0,
        is.na(.data$drug_exposure_end_date) | is.na(.data$verbatim_end_date) ~ 0
      ), na.rm = T),
      n_verbatim_end_date_and_drug_exposure_end_date_differ = sum(dplyr::case_when(
        .data$drug_exposure_end_date != .data$verbatim_end_date ~ 1,
        .data$drug_exposure_end_date == .data$verbatim_end_date ~ 0,
        is.na(.data$drug_exposure_end_date) | is.na(.data$verbatim_end_date) ~ 0
      ), na.rm = T)
    )

  records <- records %>%
    dplyr::mutate(
      proportion_missing_verbatim_end_date = .data$n_missing_verbatim_end_date / .env$total,
      proportion_not_missing_verbatim_end_date = .data$n_not_missing_verbatim_end_date / .env$total,
      proportion_verbatim_end_date_equal_to_drug_exposure_end_date = .data$n_verbatim_end_date_equal_to_drug_exposure_end_date / .env$total,
      proportion_verbatim_end_date_and_drug_exposure_end_date_differ = .data$n_verbatim_end_date_and_drug_exposure_end_date_differ / .env$total
    )
}