Zahl und Entwicklung der Spitalsbetten

hospbeds.r

library(tidyverse)
library(eurostat)
library(msthemes)
library(patchwork)

beds <- get_eurostat("hlth_rs_bds", filters = list(unit = "P_HTHAB", facility = "HBEDT", time = 2000:2017), time_format = "num")

abs <- beds %>% filter(geo %in% c("AT","DE","FR","ES","IT","SE","UK"), time == 2017) %>% 
  ggplot(aes(x = reorder(geo, values), y = values)) +
  geom_bar(stat = "identity", aes(fill=geo)) +
  scale_fill_viridis_d() +
  coord_flip() +
  theme_ms() +
  theme(panel.grid.major.y = element_blank(),
        legend.position = "none",
        axis.title = element_text(size = 7)) +
  labs(x = "", y="Betten pro 100.000 EW.")


devb <- beds %>% filter(geo %in% c("AT","DE","FR","ES","IT","SE","UK")) %>% 
  group_by(geo) %>%
  mutate(startval = case_when(time == 2000 ~ values, TRUE ~ NA_real_)) %>%
  fill(startval) %>% mutate_at(vars(values), ~./startval*100) %>%
  ggplot(aes(x=time,y=values)) +
  geom_line(aes(color=geo), size = 1.2) +
  scale_color_viridis_d(name="") +
  theme_ms() +
  theme(axis.title = element_text(size = 7)) +
  labs(x="", y="Entwicklung (2000 = 100)")

finplot <- (abs | devb) +
  plot_annotation(title = "Sparkurs im Gesundheitswesen",
                  subtitle = "Spitalsbetten in ausgewählten EU-Ländern, 2017",
                  caption = "Daten: Eurostat. Grafik: @matschnetzer",
                  theme = theme_ms(alttf = T)) +
  ggsave("hspbeds.png", dpi = 300, width = 8, height = 4)