From 37610d8dbdfd162279c14dc7147f306422297e0e Mon Sep 17 00:00:00 2001
From: Maxime Wack <maximewack@free.Fr>
Date: Mon, 27 Mar 2017 16:52:11 +0200
Subject: [PATCH] Initial commit

---
 CRHAP.Rmd | 399 ++++++++++++++++++++++++++++++++++++
 CRHAP.wid | Bin 0 -> 67915 bytes
 index.Rmd | 589 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 988 insertions(+)
 create mode 100644 CRHAP.Rmd
 create mode 100644 CRHAP.wid
 create mode 100644 index.Rmd

diff --git a/CRHAP.Rmd b/CRHAP.Rmd
new file mode 100644
index 0000000..fe677a8
--- /dev/null
+++ b/CRHAP.Rmd
@@ -0,0 +1,399 @@
+---
+output:
+  html_document:
+    toc: true
+    toc_float: true
+params:
+  CRH: NA
+  CRH_seance: NA
+  CRH_sans_seance: NA
+---
+
+```{r init, warning = F, message = F, echo = F}
+library(tidyverse)
+library(DT)
+library(magrittr)
+library(stringr)
+library(knitr)
+library(lubridate)
+library(plotly)
+
+opts_chunk$set(warning = F,
+               message = F,
+               fig.width = 9,
+               fig.height = 6,
+               echo = F)
+options(DT.options = list(paging = F,
+                          info = F,
+                          searching = F,
+                          dom = "Bfrtip",
+                          buttons = c('copy', 'excel')))
+```
+
+```{r data, echo = F, message = F, warning = F}
+mois_label <- c("Janvier",
+                "Février",
+                "Mars",
+                "Avril",
+                "Mai",
+                "Juin",
+                "Juillet",
+                "Août",
+                "Septembre",
+                "Octobre",
+                "Novembre",
+                "Décembre")
+
+pdf(NULL)
+```
+
+# Tous RUMs confondus
+
+## Par mois
+
+```{r}
+CRH() %>%
+  count(Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH() %>% count(Mois)) %>%
+  select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH() %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP")) %>%
+  formatPercentage(7)
+```
+<br/>  
+```{r}
+CRH() %>%
+
+  ggplot(aes(x = Mois, fill = Notes)) +
+  geom_bar(position = "fill") +
+  ylab("Proportion") +
+  ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
+
+  ggplotly(p)
+```
+
+## Par Pôle
+
+```{r}
+CRH() %>%
+  count(Pole, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH() %>% count(Pole)) %>%
+  select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH() %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Pôle" = "Pole",
+                         "Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP")) %>%
+  formatPercentage(7)
+```
+<br/>  
+```{r}
+CRH() %>%
+
+  ggplot(aes(x = Pole, fill = Notes)) +
+  geom_bar(position = "fill") +
+  ylab("Proportion") +
+  ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
+  theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
+
+  ggplotly(p)
+
+```
+
+## Par Pôle, par service et par mois
+
+```{r}
+CRH() %>%
+  count(Pole, Service, Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH() %>% count(Pole, Service, Mois)) %>%
+  ungroup %>%
+  select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM,
+         Pole = Pole %>% factor,
+         Mois = Mois %>% factor) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Pôle" = "Pole",
+                         "Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP"),
+            filter = "top",
+            options = list(searching = T, paging = T)) %>%
+  formatPercentage(9)
+```
+<br/>  
+```{r}
+CRH() %>%
+  count(Pole, Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
+         CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
+
+  ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
+  geom_line(stat = "identity") +
+  geom_point() +
+  ylab("Proportion de #CRHA") +
+  ggtitle("Évolution des proportions de #CRHA par pôle") -> p
+
+  ggplotly(p, tooltip = c("x", "y", "colour"))
+```
+
+----
+
+# RUMs non séance
+
+## Par mois
+
+```{r}
+CRH_sans_seance() %>%
+  count(Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH_sans_seance() %>% count(Mois)) %>%
+  select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH_sans_seance() %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP")) %>%
+  formatPercentage(7)
+```
+<br/>  
+```{r}
+CRH_sans_seance() %>%
+
+  ggplot(aes(x = Mois, fill = Notes)) +
+  geom_bar(position = "fill") +
+  ylab("Proportion") +
+  ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
+
+  ggplotly(p)
+```
+
+## Par Pôle
+
+```{r}
+CRH_sans_seance() %>%
+  count(Pole, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH_sans_seance() %>% count(Pole)) %>%
+  select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH_sans_seance() %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Pôle" = "Pole",
+                         "Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP")) %>%
+  formatPercentage(7)
+```
+<br/>  
+```{r}
+CRH_sans_seance() %>%
+
+  ggplot(aes(x = Pole, fill = Notes)) +
+  geom_bar(position = "fill") +
+  ylab("Proportion") +
+  ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
+  theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
+
+  ggplotly(p)
+
+```
+
+## Par Pôle, par service et par mois
+
+```{r}
+CRH_sans_seance() %>%
+  count(Pole, Service, Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH_sans_seance() %>% count(Pole, Service, Mois)) %>%
+  ungroup %>%
+  select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH_sans_seance() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM,
+         Pole = Pole %>% factor,
+         Mois = Mois %>% factor) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Pôle" = "Pole",
+                         "Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP"),
+            filter = "top",
+            options = list(searching = T, paging = T)) %>%
+  formatPercentage(9)
+```
+<br/>  
+```{r}
+CRH_sans_seance() %>%
+  count(Pole, Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
+         CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
+
+  ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
+  geom_line(stat = "identity") +
+  geom_point() +
+  ylab("Proportion de #CRHA") +
+  ggtitle("Évolution des proportions de #CRHA par pôle") -> p
+
+  ggplotly(p, tooltip = c("x", "y", "colour"))
+```
+
+----
+
+# RUMs séance
+
+## Par mois
+
+```{r}
+CRH_seance() %>%
+  count(Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH_seance() %>% count(Mois)) %>%
+  select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH_seance()  %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP")) %>%
+  formatPercentage(7)
+```
+<br/>  
+```{r}
+CRH_seance() %>%
+
+  ggplot(aes(x = Mois, fill = Notes)) +
+  geom_bar(position = "fill") +
+  ylab("Proportion") +
+  ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
+
+  ggplotly(p)
+```
+
+## Par Pôle
+
+```{r}
+CRH_seance() %>%
+  count(Pole, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH_seance() %>% count(Pole)) %>%
+  select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH_seance()  %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Pôle" = "Pole",
+                         "Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP")) %>%
+  formatPercentage(7)
+
+```
+<br/>  
+```{r}
+CRH_seance() %>%
+
+  ggplot(aes(x = Pole, fill = Notes)) +
+  geom_bar(position = "fill") +
+  ylab("Proportion") +
+  ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
+  theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
+
+  ggplotly(p)
+
+```
+
+## Par Pôle, par service et par mois
+
+```{r}
+CRH_seance() %>%
+  count(Pole, Service, Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  full_join(CRH_seance() %>% count(Pole, Service, Mois)) %>%
+  ungroup %>%
+  select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+  full_join(CRH_seance()  %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+  mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         `% absents` = CRHA / RUM,
+         Pole = Pole %>% factor,
+         Mois = Mois %>% factor) %>%
+  datatable(rownames = F,
+            extensions = 'Buttons',
+            colnames = c("Pôle" = "Pole",
+                         "Non renseigné" = "Manquant",
+                         "#CRHA" = "CRHA",
+                         "#CRHP" = "CRHP"),
+            filter = "top",
+            options = list(searching = T, paging = T)) %>%
+  formatPercentage(9)
+
+```
+<br/>  
+```{r}
+CRH_seance() %>%
+  count(Pole, Mois, Notes) %>%
+  mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+  spread(Notes, n) %>%
+  mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
+         CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+         CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+         pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
+
+  ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
+  geom_line(stat = "identity") +
+  geom_point() +
+  ylab("Proportion de #CRHA") +
+  ggtitle("Évolution des proportions de #CRHA par pôle") -> p
+
+  ggplotly(p, tooltip = c("x", "y", "colour"))
+```
diff --git a/CRHAP.wid b/CRHAP.wid
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diff --git a/index.Rmd b/index.Rmd
new file mode 100644
index 0000000..6e7a69a
--- /dev/null
+++ b/index.Rmd
@@ -0,0 +1,589 @@
+---
+title: CRHAP
+runtime: shiny
+output:
+  html_document:
+    toc: true
+    toc_float: true
+---
+
+```{r init, warning = F, message = F, echo = F}
+library(tidyverse)
+library(DT)
+library(magrittr)
+library(stringr)
+library(knitr)
+library(lubridate)
+library(plotly)
+
+opts_chunk$set(warning = F,
+               message = F,
+               fig.width = 9,
+               fig.height = 6,
+               echo = F)
+options(DT.options = list(paging = F,
+                          info = F,
+                          searching = F,
+                          dom = "Bfrtip",
+                          buttons = c('copy', 'excel')),
+        shiny.maxRequestSize = 500*1024^2)
+
+pdf(NULL)
+```
+
+# {.tabset}
+
+## Méthode
+
+### Chargement des données
+
+Le fichier doit être fournis au format CSV avec les paramètres suivants :
+
+* séparateur de champs = ,
+* guillemets = "
+* encodage = UTF-8
+* séparateur de décimales = ,
+
+Il doit être issu de la [requête suivante](CRHAP.wid).
+
+```{r data}
+inputPanel(
+  numericInput("mois", "Mois", (Sys.Date() %>% month) - 1),
+  numericInput("annee", "Année", Sys.Date() %>% year),
+  fileInput("crhap", "CRHAP", accept = "text/csv"),
+  downloadButton("report", "Générer le rapport")
+)
+
+CRH <- reactive(
+  {
+    req(input$crhap, input$annee, input$mois)
+
+    read_csv(input$crhap$datapath, col_types = cols(`Numéro d'hospitalisation` = col_character()), progress = F) %>%
+      setNames(c("RUM", "NDA", "DP", "GHM", "Notes", "Pole", "Service", "Date_DP", "Date_sortie")) %>%
+      mutate(Notes = Notes %>%
+               str_to_upper %>%
+               str_replace_all(" ", "") %>%
+               str_replace("CHR", "CRH") %>%
+               str_extract("CRH."),
+             Notes = ifelse(Notes %in% c("CRHP", "CRHA"), Notes, NA),
+             Date_DP = as.Date(Date_DP),
+             Date_sortie = as.Date(Date_sortie),
+             Delai = as.numeric(Date_DP - Date_sortie),
+             Pole = ifelse(Pole == "GSP : GÉRONTOLOGIE ET SOINS PALLIATIFS", "GSP", Pole),
+             Pole = ifelse(Pole == "POLE LORRAIN DE CHIRURGIE DE L'APPAREIL LOCOMOTEUR", "CCEG", Pole)) %>%
+      filter(!(Service %in% c("MEDECINE INFANTILE", "NEPHROLOGIE") & DP == "Z49.1"),
+             !(Service %in% c("AMP CLINIQUE", "ORTHOGENIE"))) %>%
+      filter(Date_sortie < ceiling_date(as.Date(str_c(input$annee, "-", input$mois, "-01")), unit = "month"),
+             Date_sortie > floor_date(as.Date(str_c(input$annee - 1, "-", input$mois, "-01")), unit = "month")) %>%
+      mutate(Notes = ifelse(Service == "STRUCTURE D'URGENCES" & Delai <= 15 & is.na(Notes), "CRHP", Notes),
+             Mois = str_c(year(Date_sortie), "-", str_pad(month(Date_sortie), 2, "left", "0")))
+  }
+)
+
+
+CRH_sans_seance <- reactive(
+  {
+    req(CRH())
+
+    CRH() %>%
+      filter(!(GHM %>% str_detect("^28")))
+  }
+)
+
+CRH_seance <- reactive(
+  {
+    req(CRH())
+
+    CRH() %>%
+      filter(GHM %>% str_detect("^28")) 
+  }
+)
+
+mois_label <- c("Janvier",
+                "Février",
+                "Mars",
+                "Avril",
+                "Mai",
+                "Juin",
+                "Juillet",
+                "Août",
+                "Septembre",
+                "Octobre",
+                "Novembre",
+                "Décembre")
+```
+
+```{r report}
+output$report <- downloadHandler(filename = "CRHAP.html",
+                                content = function(file)
+                                {
+                                  tempReport <- file.path(tempdir(), "CRHAP.Rmd")
+                                  file.copy("CRHAP.Rmd", tempReport, overwrite = T)
+                                  rmarkdown::render(tempReport, output_file = file, params = list(CRH = CRH(), CRH_seance = CRH_seance(), CRH_sans_seance = CRH_sans_seance()))
+                                })
+```
+
+### Présence du CRH pour le codage des séjours
+
+Ces tableaux concernent les RUMs sur une année glissante.  
+Les RUMs **sans DP** et **codés en erreur** (CMD 90) sont **exclus** de l'analyse.  
+Le pourcentage d'absents est calculé sur la **totalité** des RUMs, *Non renseignés* compris.  
+Le délai médian est le délai médian entre la date de fin du RSS et la date de codage du DP pour le RUM.  
+Les données sont disponibles avec les **séances incluses**, et les **séances excluses**.
+
+Les séances automatiquement codées (dialyse en néphrologie et médecine infantile) sont *exclues*.  
+Les séjours en AMP clinique et orthogénie sont également *exclus*.  
+Les séjours automatiquement codés d'UHCD (séjour en UHCD avec délai de codage <= 15j et sans marque de codage) sont considérés comme *#CRHP*.
+
+Il est possible pour chaque tableau de **trier** chaque colonne en cliquant sur son intitulé.  
+Pour les tableaux par service, il est également possible de **filtrer** par pôle ou selon les valeurs (par exemple, ne faire apparaître que les services avec plus de 50% de CRH absents).
+
+Les tableaux sont **exportables** sous Excel à l'aide du bouton en haut à gauche de chaque tableau.  
+**Attention : les *tris* et *filtres* sont pris en compte pour l'export !**
+
+----
+
+### Saisie
+
+Les marques **#CRHA** (CRH absent) et **#CRHP** (CRH présent) sont saisies dans les **Notes** lors du codage des séjours dans WebPIMS.
+
+#### Format
+
+Les marques sont saisies selon le format suivant :
+
+* marque en début de Notes
+* précédée du #
+* tout attaché
+* attention aux fautes de frappe ! (#C*HR*P, #CR*PH*)
+* **seules ces marques seront analysées !**
+
+#### Conditions
+
+Les marques sont saisies selon les conditions suivantes :
+
+* **\#CRHP** dès lors qu'un compte-rendu permettant le codage du séjour est présent :
+    * au moins un CRH lors de l'hospitalisation
+    * CRH papier accepté
+    * CRH au «mauvais» format accepté
+    * CRH pour venues multiples (séances) accepté
+* **\#CRHA** dès lors qu'il n'existe aucun compte-rendu d'aucune forme permettant le codage du séjour, et **en respectant un délai d'au moins une semaine après la fin de l'hospitalisation**.
+
+Il est recommandé de coder les séjours par ordre **chronologique**.
+
+----
+
+### Analyse
+
+#### Extraction
+
+Les marques sont extraites par le médecin DIM responsable de la clôture, à l'aide d'une requête BO dans l'univers **WebPIMS MCO Prod**. Cette requête est exécutée tous les mois, *une semaine après la clôture mensuelle*. Les marques sont tirées des RUMs remplissant les conditions suivantes :
+
+* RUM de RSS sorti durant la période allant du début de ce recueil (avril 2016) à la fin du mois de la dernière clôture
+* les RUMs sans DP (non codés) sont *exclus*
+* les RUMs de RSS groupés en erreur sont *exclus*
+
+#### Traitement
+
+Les données extraites sont séparées en trois groupes pour l'analyse :
+
+* tous RUMs confondus
+* RUMs séances uniquement
+* RUMs à l'exclusion des séances
+
+Pour chaque jeu de données, les tableaux suivants sont générés :
+
+* par mois de sortie du **RSS**
+* par pôle
+* par service
+
+Chaque tableau présente les indicateurs suivants :
+
+* le nombre de RUMs dans le mois/pôle/service concerné
+* le nombre de RUMs avec marque #CRHP
+* le nombre de RUMs avec marque #CRHA
+* le nombre de RUMs non marqués
+* le **pourcentage de #CRHA**, calculé par rapport au nombre total de RUMs (y compris RUMs non marqués)
+
+## Rapport
+
+### Tous RUMs confondus
+
+#### Par mois
+
+```{r}
+renderDataTable({
+  CRH() %>%
+    count(Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH() %>% count(Mois)) %>%
+    select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH() %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP")) %>%
+    formatPercentage(7)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH() %>%
+
+    ggplot(aes(x = Mois, fill = Notes)) +
+    geom_bar(position = "fill") +
+    ylab("Proportion") +
+    ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
+
+  ggplotly(p)
+})
+```
+
+#### Par Pôle
+
+```{r}
+renderDataTable({
+  CRH() %>%
+    count(Pole, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH() %>% count(Pole)) %>%
+    select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH() %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Pôle" = "Pole",
+                           "Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP")) %>%
+    formatPercentage(7)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH() %>%
+
+    ggplot(aes(x = Pole, fill = Notes)) +
+    geom_bar(position = "fill") +
+    ylab("Proportion") +
+    ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
+    theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
+
+  ggplotly(p)
+})
+```
+
+#### Par Pôle, par service et par mois
+
+```{r}
+renderDataTable({
+  CRH() %>%
+    count(Pole, Service, Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH() %>% count(Pole, Service, Mois)) %>%
+    ungroup %>%
+    select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM,
+           Pole = Pole %>% factor,
+           Mois = Mois %>% factor) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Pôle" = "Pole",
+                           "Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP"),
+              filter = "top",
+              options = list(searching = T, paging = T)) %>%
+    formatPercentage(9)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH() %>%
+    count(Pole, Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
+           CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
+
+    ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
+    geom_line(stat = "identity") +
+    geom_point() +
+    ylab("Proportion de #CRHA") +
+    ggtitle("Évolution des proportions de #CRHA par pôle") -> p
+
+  ggplotly(p, tooltip = c("x", "y", "colour"))
+})
+```
+
+----
+
+### RUMs non séance
+
+#### Par mois
+
+```{r}
+renderDataTable({
+  CRH_sans_seance() %>%
+    count(Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH_sans_seance() %>% count(Mois)) %>%
+    select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH_sans_seance() %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP")) %>%
+    formatPercentage(7)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH_sans_seance() %>%
+
+    ggplot(aes(x = Mois, fill = Notes)) +
+    geom_bar(position = "fill") +
+    ylab("Proportion") +
+    ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
+
+  ggplotly(p)
+})
+```
+
+#### Par Pôle
+
+```{r}
+renderDataTable({
+  CRH_sans_seance() %>%
+    count(Pole, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH_sans_seance() %>% count(Pole)) %>%
+    select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH_sans_seance() %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Pôle" = "Pole",
+                           "Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP")) %>%
+    formatPercentage(7)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH_sans_seance() %>%
+
+    ggplot(aes(x = Pole, fill = Notes)) +
+    geom_bar(position = "fill") +
+    ylab("Proportion") +
+    ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
+    theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
+
+  ggplotly(p)
+})
+```
+
+#### Par Pôle, par service et par mois
+
+```{r}
+renderDataTable({
+  CRH_sans_seance() %>%
+    count(Pole, Service, Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH_sans_seance() %>% count(Pole, Service, Mois)) %>%
+    ungroup %>%
+    select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH_sans_seance() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM,
+           Pole = Pole %>% factor,
+           Mois = Mois %>% factor) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Pôle" = "Pole",
+                           "Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP"),
+              filter = "top",
+              options = list(searching = T, paging = T)) %>%
+    formatPercentage(9)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH_sans_seance() %>%
+    count(Pole, Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
+           CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
+
+    ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
+    geom_line(stat = "identity") +
+    geom_point() +
+    ylab("Proportion de #CRHA") +
+    ggtitle("Évolution des proportions de #CRHA par pôle") -> p
+
+  ggplotly(p, tooltip = c("x", "y", "colour"))
+})
+```
+
+----
+
+### RUMs séance
+
+#### Par mois
+
+```{r}
+renderDataTable({
+  CRH_seance() %>%
+    count(Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH_seance() %>% count(Mois)) %>%
+    select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH_seance()  %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP")) %>%
+    formatPercentage(7)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH_seance() %>%
+
+    ggplot(aes(x = Mois, fill = Notes)) +
+    geom_bar(position = "fill") +
+    ylab("Proportion") +
+    ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
+
+  ggplotly(p)
+})
+```
+
+#### Par Pôle
+
+```{r}
+renderDataTable({
+  CRH_seance() %>%
+    count(Pole, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH_seance() %>% count(Pole)) %>%
+    select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH_seance()  %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Pôle" = "Pole",
+                           "Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP")) %>%
+    formatPercentage(7)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH_seance() %>%
+
+    ggplot(aes(x = Pole, fill = Notes)) +
+    geom_bar(position = "fill") +
+    ylab("Proportion") +
+    ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
+    theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
+
+  ggplotly(p)
+})
+```
+
+#### Par Pôle, par service et par mois
+
+```{r}
+renderDataTable({
+  CRH_seance() %>%
+    count(Pole, Service, Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    full_join(CRH_seance() %>% count(Pole, Service, Mois)) %>%
+    ungroup %>%
+    select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
+    full_join(CRH_seance() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
+    mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           `% absents` = CRHA / RUM,
+           Pole = Pole %>% factor,
+           Mois = Mois %>% factor) %>%
+    datatable(rownames = F,
+              extensions = 'Buttons',
+              colnames = c("Pôle" = "Pole",
+                           "Non renseigné" = "Manquant",
+                           "#CRHA" = "CRHA",
+                           "#CRHP" = "CRHP"),
+              filter = "top",
+              options = list(searching = T, paging = T)) %>%
+    formatPercentage(9)
+})
+```
+<br/>  
+```{r}
+renderPlotly({
+  CRH_seance() %>%
+    count(Pole, Mois, Notes) %>%
+    mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
+    spread(Notes, n) %>%
+    mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
+           CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
+           CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
+           pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
+
+    ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
+    geom_line(stat = "identity") +
+    geom_point() +
+    ylab("Proportion de #CRHA") +
+    ggtitle("Évolution des proportions de #CRHA par pôle") -> p
+
+  ggplotly(p, tooltip = c("x", "y", "colour"))
+})
+```