R/plot_ed_los_distribution_admission.R

In HorridTom/hospitalflow: Analysis of Patient Flow in Hospitals

#' Length of stay in the emergency department for attendances and admissions
#'
#' @description
#' \code{plot_ed_los_distribution_admission} shows the distribution of length of
#' stay for people in the emergency department, stratified by whether they were
#' admitted to the hospital or discharged.
#'
#' @param data Hospital episode data.
#' @inheritParams plot_admissions_discharges_day_of_week
#'
#' @return A plot (default) or a dataframe showing the distribution of length of
#' stay for patients in the emergency department.
#'
#' @examples
#' \dontrun{
#' TBD
#' }
#' @export
plot_ed_los_distribution_admission <- function(data,
                           startDate,
                           endDate,
                           returnPlot,
                           hospitalName) {

  # get time zone of data
  time_zone <- attr(data$spell_start, "tzone")

  # set input dates to have the same time zone as the data
  start_date <- as.Date(startDate, tz = time_zone)
  end_date <- as.Date(endDate, tz = time_zone)

  df <- data %>%
    dplyr::select(spell_number, spell_start, spell_end, spell_class_col, initial_ed_end_datetime) %>%
    dplyr::filter(spell_start < end_date | spell_end > start_date) %>%
    dplyr::filter(spell_class_col == "ed_non_admission" | spell_class_col == "ed_comp_non_admission" | spell_class_col == "ed_admission") %>%
    tidyr::drop_na()

  df_recode <- df %>%
    dplyr::mutate(Time_spent = as.numeric(difftime(initial_ed_end_datetime, spell_start), unit = c("mins"))) %>%
    dplyr::mutate(Time_binned = dplyr::case_when(
      Time_spent <= 14 ~ "00:00",
      Time_spent == 15 | Time_spent <= 29 ~ "00:15",
      Time_spent == 30 | Time_spent <= 44 ~ "00:30",
      Time_spent == 45 | Time_spent <= 59 ~ "00:45",
      Time_spent == 60 | Time_spent <= 74 ~ "1:00",
      Time_spent == 75 | Time_spent <= 89 ~ "1:15",
      Time_spent == 90 | Time_spent <= 104 ~ "1:30",
      Time_spent == 105 | Time_spent <= 119 ~ "1:45",
      Time_spent == 120 | Time_spent <= 134 ~ "2:00",
      Time_spent == 135 | Time_spent <= 149 ~ "2:15",
      Time_spent == 150 | Time_spent <= 164 ~ "2:30",
      Time_spent == 165 | Time_spent <= 179 ~ "2:45",
      Time_spent == 180 | Time_spent <= 194 ~ "3:00",
      Time_spent == 195 | Time_spent <= 209 ~ "3:15",
      Time_spent == 210 | Time_spent <= 224 ~ "3:30",
      Time_spent == 225 | Time_spent <= 239 ~ "3:45",
      Time_spent == 240 | Time_spent <= 254 ~ "4:00",
      Time_spent == 255 | Time_spent <= 269 ~ "4:15",
      Time_spent == 270 | Time_spent <= 284 ~ "4:30",
      Time_spent == 285 | Time_spent <= 299 ~ "4:45",
      Time_spent == 300 | Time_spent <= 314 ~ "5:00",
      Time_spent == 315 | Time_spent <= 329 ~ "5:15",
      Time_spent == 330 | Time_spent <= 344 ~ "5:30",
      Time_spent == 345 | Time_spent <= 359 ~ "5:45",
      Time_spent == 360 | Time_spent <= 374 ~ "6:00",
      Time_spent == 375 | Time_spent <= 389 ~ "6:15",
      Time_spent == 390 | Time_spent <= 404 ~ "6:30",
      Time_spent == 405 | Time_spent <= 414 ~ "6:45",
      Time_spent == 415 | Time_spent <= 429 ~ "7:00",
      Time_spent == 430 | Time_spent <= 444 ~ "7:15",
      Time_spent == 445 | Time_spent <= 459 ~ "7:30",
      Time_spent == 460 | Time_spent <= 474 ~ "7:45",
      Time_spent == 475 | Time_spent <= 720 ~ "8-12 hrs",
      Time_spent >= 721 ~ "> 12 hrs"
    ))


  # Calculate Attendances
  dt_attendances <- df_recode %>%
    dplyr::filter(spell_class_col == "ed_non_admission" | spell_class_col == "ed_comp_non_admission") %>%
    dplyr::group_by(Time_binned) %>%
    dplyr::mutate(Direct_discharge = dplyr::n())


  dt_admissions <- df_recode %>%
    dplyr::filter(spell_class_col == "ed_admission" | spell_class_col == "ed_comp_admissions") %>%
    dplyr::group_by(Time_binned) %>%
    dplyr::mutate(Hospital_admissions = dplyr::n())


  dt_attend_admiss <- dplyr::bind_rows(dt_attendances, dt_admissions) %>%
    tidyr::gather(key = "Variable", value = "Value", "Direct_discharge", "Hospital_admissions") %>%
    tidyr::drop_na() %>%
    dplyr::select(spell_number, Time_binned, Variable, Value) %>%
    dplyr::group_by(Time_binned, Variable) %>%
    dplyr::summarize("Value" = dplyr::n()) %>%
    dplyr::ungroup()

  # Set the title
  title_stub <- " LoS distribution for admitted patients, "
  # hospitalName <- "Chelsea & Westminster"
  start_date_title <- format(as.Date(start_date), format = "%d %B %Y")
  end_date_title <- format(as.Date(end_date), format = "%d %B %Y")
  chart_title <- paste0(hospitalName, title_stub, start_date_title, " to ", end_date_title)

  att_plot_t_binned <- ggplot2::ggplot(dt_attend_admiss, ggplot2::aes(Time_binned, Value, group = Variable, fill = Variable)) + # shape = Event,  colour = Event
    ggplot2::geom_bar(stat = "identity", position = "identity", width = 0.5, lwd = 0.3, colour = "white") +
    # geom_line(aes(linetype = variable, color = variable), size = 1.0) +
    # geom_point(aes(shape = variable), size = 1.0) +
    # ggplot2::scale_shape_manual(values = c(7, 6)) +
    # ggplot2::scale_linetype_manual(values = c("twodash", "solid")) +
    # ggplot2::scale_color_manual(values=c("black", "red")) +
    ggplot2::theme_bw() +
    ggplot2::xlim(
      "00:00", "00:15", "00:30", "00:45",
      "1:00", "1:15", "1:30", "1:45",
      "2:00", "2:15", "2:30", "2:45",
      "3:00", "3:15", "3:30", "3:45",
      "4:00", "4:15", "4:30", "4:45",
      "5:00", "5:15", "5:30", "5:45",
      "6:00", "6:15", "6:30", "6:45",
      "7:00", "7:15", "7:30", "7:45",
      "8-12 hrs", "> 12 hrs"
    ) +
    ggplot2::labs(
      title = chart_title,
      subtitle = "Unscheduled A&E attendances, n; ED LoS 15min bins to 8 hr, 8-12 hr, >12,
Note: (i) results are intended for management information only",
      y = "Count (n), Direct Discharged and Hospital Admissions", x = "Days of the week", caption = "Source: CLAHRC NWL"
    ) +
    ggplot2::theme(
      axis.title.y = ggplot2::element_text(margin = ggplot2::margin(t = 0, r = 21, b = 0, l = 0)),
      axis.text.x = ggplot2::element_text(angle = 45, hjust = 1),
      plot.title = ggplot2::element_text(size = 10, face = "bold"),
      plot.subtitle = ggplot2::element_text(size = 8),
      legend.position = "bottom", legend.box = "horizontal"
    )

  att_plot_t_binned

  if (returnPlot == TRUE) {
    att_plot_t_binned
  } else {
    att_plot_t_binned$data %>%
      tibble::as_tibble() %>%
      dplyr::select(Time_binned, Variable, Value)
  }
}