Hospital beds by NUTS 2 regions - hlth_rs_bdsrg

Data - Eurostat

Author

unit

Code

hlth_rs_bdsrg %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

unit	Unit	Nobs
NR	Number	32501
P_HTHAB	Per hundred thousand inhabitants	30432
HAB_P	Inhabitants per ...	26196

facility

Code

hlth_rs_bdsrg %>%
  left_join(facility, by = "facility") %>%
  group_by(facility, Facility) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

facility	Facility	Nobs
HBEDT	Available beds in hospitals (HP.1)	23402
HBEDT_CUR	Curative care beds in hospitals (HP.1)	16681
HBEDI_PSY	Psychiatric care beds in hospitals (HP.1)	16354
HBEDT_LT	Long-term care beds in hospitals (HP.1)	12295
HBEDT_REH	Rehabilitative care beds in hospitals (HP.1)	10321
HBEDT_OTH	Other beds in hospitals (HP.1)	10076

geo

Code

hlth_rs_bdsrg %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ex 1: Hospital Care Beds

Code

hlth_rs_bdsrg %>%
  filter(time == "2015", 
         nchar(geo) == 4,
         facility == "HBEDT_CUR") %>%
  left_join(geo, by = "geo") %>%
  select(geo, Geo, hospital_care = values) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ex 2: Hospital Care Beds - NUTS2

Code

hlth_rs_bdsrg %>%
  filter(time == "2015", 
         nchar(geo) == 4,
         facility == "HBEDT_CUR",
         unit == "HAB_P") %>%
  left_join(geo, by = "geo") %>%
  select(geo, Geo, values) %>%
  arrange(-values) %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -15, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::dollar_format(accuracy = 1, prefix = ""),) +
  theme_void() + theme(legend.position = c(0.25, 0.85)) + 
  labs(fill = "Inhabitants per curative beds")

Ex 2: Available Beds - NUTS2

Code

hlth_rs_bdsrg %>%
  filter(time == "2015", 
         nchar(geo) == 4,
         facility == "HBEDT",
         unit == "HAB_P") %>%
  left_join(geo, by = "geo") %>%
  select(geo, Geo, values) %>%
  arrange(-values) %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -15, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::dollar_format(accuracy = 1, prefix = ""),) +
  theme_void() + theme(legend.position = c(0.25, 0.85)) + 
  labs(fill = "Inhabitants per available beds")