write the GP OoH lookup out using some functions

[github-actions[bot]]

https://github.com/Public-Health-Scotland/source-linkage-files/blob/a26fc056346a37956eab71f9c8b483b6d6ee6123/R/process_extract_gp_ooh.R#L88

#' Process the GP OoH extract
#'
#' @description This will read and process the
#' GP OoH extract, it will return the final data
#' but also write this out as a zsav and rds.
#'
#' @param year The year to process, in FY format.
#' @param data_list A list containing the extracts.
#' @param write_to_disk (optional) Should the data be written to disk default is
#' `TRUE` i.e. write the data to disk.
#'
#' @return the final data as a [tibble][tibble::tibble-package].
#' @export
#' @family process extracts
process_extract_gp_ooh <- function(year, data_list, write_to_disk = TRUE) {
  diagnosis_extract <- process_extract_ooh_diagnosis(data_list[["diagnosis"]], year)
  outcomes_extract <- process_extract_ooh_outcomes(data_list[["outcomes"]], year)
  consultations_extract <- process_extract_ooh_consultations(data_list[["consultations"]], year)

  # Join data ---------------------------------

  matched_data <- consultations_extract %>%
    dplyr::left_join(diagnosis_extract, by = "ooh_case_id") %>%
    dplyr::left_join(outcomes_extract, by = "ooh_case_id")

  # Costs ---------------------------------

  # OOH cost lookup
  ooh_cost_lookup <- readr::read_rds(get_gp_ooh_costs_path()) %>%
    dplyr::rename(
      hbtreatcode = "TreatmentNHSBoardCode"
    )

  ooh_costs <- matched_data %>%
    dplyr::mutate(
      hbtreatcode = dplyr::case_when(
        # Recode Fife and Tayside so they match the cost lookup.
        hbtreatcode == "S08000018" ~ "S08000029",
        hbtreatcode == "S08000027" ~ "S08000030",
        # Recode Greater Glasgow & Clyde and Lanarkshire so they
        # match the costs lookup (2018 -> 2019 HB codes).
        hbtreatcode == "S08000021" ~ "S08000031",
        hbtreatcode == "S08000023" ~ "S08000032",
        TRUE ~ hbtreatcode
      ),
      year = year
    ) %>%
    # Match to cost lookup
    dplyr::left_join(ooh_cost_lookup, by = c("hbtreatcode", "year")) %>%
    dplyr::rename(
      cost_total_net = "cost_per_consultation"
    ) %>%
    create_day_episode_costs(.data$record_keydate1, .data$cost_total_net)

  # Final cleaning  ---------------------------------

  ooh_clean <- ooh_costs %>%
    dplyr::mutate(
      # Replace location unknown with NA
      location = dplyr::na_if(.data$location, "UNKNOWN"),
      recid = "OoH",
      smrtype = add_smr_type(.data$recid, consultation_type = .data$consultation_type),
      kis_accessed = factor(
        dplyr::case_when(
          kis_accessed == "Y" ~ 1L,
          kis_accessed == "N" ~ 0L,
          TRUE ~ 9L
        ),
        levels = c(0L, 1L, 9L),
        labels = c("Y", "N", "Unknown")
      ),
      gpprac = convert_eng_gpprac_to_dummy(.data$gpprac),
      # Split the time from the date
      keytime1 = hms::as_hms(.data$record_keydate1),
      keytime2 = hms::as_hms(.data$record_keydate2),
      record_keydate1 = trunc(.data$record_keydate1, "days"),
      record_keydate2 = trunc(.data$record_keydate2, "days")
    ) %>%
    dplyr::mutate(
      record_keydate1 = as.Date(.data$record_keydate1),
      record_keydate2 = as.Date(.data$record_keydate2)
    )

  # Keep the location descriptions as a lookup.
  # TODO write the GP OoH lookup out using some functions
  location_lookup <- ooh_clean %>%
    dplyr::group_by(.data$location) %>%
    dplyr::summarise(
      location_description = dplyr::first(.data$location_description)
    ) %>%
    dplyr::ungroup()

  ## Save Outfile -------------------------------------

  final_data <- ooh_clean %>%
    dplyr::select(
      "year",
      "recid",
      "smrtype",
      "record_keydate1",
      "record_keydate2",
      "keytime1",
      "keytime2",
      "chi",
      "gender",
      "dob",
      "gpprac",
      "postcode",
      "hbrescode",
      "datazone",
      "hscp",
      "hbtreatcode",
      "location",
      "attendance_status",
      "kis_accessed",
      "refsource",
      tidyselect::starts_with("diag"),
      tidyselect::starts_with("ooh_outcome"),
      "cost_total_net",
      tidyselect::ends_with("_cost"),
      "ooh_case_id"
    )

  if (write_to_disk) {
    final_data %>%
      write_rds(get_source_extract_path(year, "GPOoH", check_mode = "write"))
  }

  return(final_data)
}

[github-actions[bot]]

Closed in 9fd2b116ebc2772d972784411d5d3b98bd4ae035