length of stay with stacked bars

gistfile1.txt

los_distrib_1_month_with_breaks_provided <- function(data, plot_chart){

  # renaming the variables I am interested in 
  # renaming the variables I am interested in 
  df_rename <- data %>%
    select(PAT_CODE, START_DATETIME, END_DATETIME, episode.order, Admission.Type, disch.ward.type, WARD_CODE) %>%
    dplyr::rename(IDcol = PAT_CODE, Admissions = START_DATETIME, 
                  Discharges = END_DATETIME, Episode_number = episode.order, Ward_code = WARD_CODE, 
                  Admission_type = Admission.Type, Discharge_ward_type = disch.ward.type)
  
  colname_ct <- function(data, colname){
    data[,colname] = as.POSIXct(data[,colname])
    data
  }
  
  #subseting data set#
  
  dt_march <-  df_rename %>%
    colname_ct("Admissions") %>%
    colname_ct("Discharges") %>%
    dplyr::filter(Admissions >= "2015-02-05 00:00:00" & Admissions <= "2015-05-03 23:59:00" | 
                    Discharges >= "2015-02-05 00:00:00" & Discharges <= "2015-05-03 23:59:00") %>%
    dplyr::filter(Episode_number == 1) %>%
    mutate(
      Admitted_date = as.Date(Admissions),
      Discharge_date = as.Date(Discharges), 
      Same_day_discharge = ifelse(Admitted_date == Discharge_date, "True", "False"), 
      Maternity = ifelse(Admission_type == "Maternity" & Discharge_ward_type == "Unknown", "Maternity", "Unknown")
    ) %>%
    select(IDcol, Admissions, Discharges, Admission_type, Discharge_ward_type, Ward_code, Episode_number, Admitted_date, Discharge_date, Same_day_discharge, Maternity)
  
  
  dt_recode <- dt_march %>%
    mutate(Ward_type = case_when(Admission_type != "Emergency" & Discharge_ward_type == "Other" ~ "Other wards (non_emergency)" , 
                                 Admission_type == "Emergency" & Discharge_ward_type == "Other" ~ "Other wards (emergency)" , 
                                 Admission_type != "Emergency" & Discharge_ward_type == "AAU" ~ "AAU" , 
                                 Admission_type == "Emergency" & Discharge_ward_type == "AAU" ~ "AAU" , 
                                 Admission_type != "Emergency" & Discharge_ward_type == "Obs Ward" ~ "Obs Ward" , 
                                 Admission_type == "Emergency" & Discharge_ward_type == "Obs Ward" ~ "Obs Ward" , 
                                 Admission_type == "Maternity" & Discharge_ward_type == "Unknown" ~ "Maternity"))
  
  
  ############################
  # calculating total time by using difftime - length of stay
  # getting rid of the same day non-emergency
  ################################
  dt_los <- dt_recode %>%
    filter(Same_day_discharge == "False") %>%
    mutate(LOS = as.numeric(difftime(Discharges, Admissions, units = c("days")))) %>% # or minutes? 
    select(IDcol, Admissions, Discharges, Admission_type, LOS, Ward_code, Same_day_discharge, Ward_type) %>%
    na.omit()
  
  # Selecting bins from the Los 
  ###########################
  los <-  dt_los$LOS
  ##########################
  # Need to transform los into numeric
  ###########################
  as.numeric(los)
  
  ###########################
  # choosing the bins
  ##########################
  breaks <- c(0, 0.8, 0.16, 
              1, 1.8, 1.16, 
              2, 2.8, 2.16, 
              3, 3.8, 3.16, 
              4, 4.8, 4.16, 
              5, 5.8, 5.16, 
              6, 6.8, 6.16, 
              7, 14, 21, 28, max(los, na.rm = TRUE))
  
  ###########################
  
  dt_los$losbinned <- cut(dt_los$LOS, 
                          breaks = breaks,
                          labels = c("0hrs", "8hrs", "16hrs", 
                                     "1 d", "1 d 8hrs", "1 d 16hrs",
                                     "2 d", "2 d 8hrs", "2 d 16hrs", 
                                     "3 d", "3 d 8hrs", "3 d 16hrs", 
                                     "4 d", "4 d 8hrs", "4 d 16hrs", 
                                     "5 d", "5 d 8hrs", "5 d 16hrs", 
                                     "6 d",  "6 d 8hrs","6 d 16hrs", 
                                     "7 - 14 d", "15 - 21 d", "22 - 28 d", "> 28 d"), 
                          right = TRUE)
  
  
  df_wrd_c <-  dt_los %>%
    na.omit()%>%
    group_by(Ward_type, losbinned) %>% 
    dplyr::summarise(Count = n(), 
                     CountT = sum(Count),
                     Per = paste0(round(100*Count/CountT,2), '%'))
  # tried different stuff and did not work 
  
  
  # Plotting the lenght of stay by the ward  - check for dual axis graphs
  
  plot <-ggplot(df_wrd_c, aes(x = losbinned, y = Count, group = Ward_type,  fill = Ward_type)) +   #alpha= ward.type - this gives a ligther version of the colours I choose   # changing the size of the bars for each categ change the parameter width, and in between the stacked categories the white colour is passed on the color command, with the width of the line 0.5
    geom_bar(stat = "identity",width = 0.5, lwd = 0.5, colour = "white") + # 
    scale_fill_brewer(palette= "Reds") +
    scale_y_continuous(expand = c(0, .9)) +
    theme_bw() +
    #scale_y_continuous("Cumulative hospital addmissions, %", sec.axis = ) +
    labs(title ="Hospital LoS distribution for admitted patients, 1st of March to 31st of March, 2015",
         subtitle = "Hospital discharges, excl. same-day non-emergency, 1st of March to 31st of March,2015; cummulative hospital LoS in 8 hr bins to 7 d, 7 d bins to28 d, > 28 d
         Note:(i)LoS calculated in days, incl. trolleyed ED LoS and excl transit areas;(ii) results are intended for management information only",
         y = "Hospital admissions*, n", x = "Hospital LoS, d (8 hr bins to 7d, 7d bins to 28d, >28 d) ", caption = "Source: CLAHRC NWL")+
    theme(axis.title.y = element_text(margin = ggplot2::margin(t = 0, r = 21, b = 0, l = 0)),
          plot.title = element_text(size = 11, face = "bold"), # changing the parameters in this box will give a different size of the title, with bold passed as a parameter
          plot.subtitle = element_text(size = 8)) + # changing the parameters in this box will give a different size of the subtitle
    theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
          legend.position = "bottom", legend.box = "horizontal" ) +
    guides(fill = guide_legend(title = "Discharge from"))
  
  plot
  
  if(plot_chart == TRUE){
    
    plot
    
  }else{
    
    plot$data %>% select(Ward_type, losbinned, Count)
    
  }
  
}