Health care expenditure by financing scheme - hlth_sha11_hf

Data - Eurostat

Info

Last observation: Annual: 2025 (N = 957)

First observation: Annual: 1992 (N = 132)

Last data update: 23 jul 2026, 22:39. Last compile: 24 jul 2026, 01:52

Structure

freq

unit

icha11_hf

geo

Ex: Government schemes and compulsory contributory health care financing schemes (% of GDP)

hlth_sha11_hf %>%
  filter(geo %in% c("FR", "DE", "IT"),
         # HF1: Government schemes and compulsory contributory health care financing schemes
         icha11_hf == "HF1",
         # PC_GDP: Percentage of gross domestic product (GDP)
         unit == "PC_GDP") %>%
  
  year_to_enddate %>%
  ggplot + geom_line(aes(x = date, y = values/100, color = Geo)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal()  +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = 0.01*seq(0, 60, 0.5),
                     labels = scales::percent_format(accuracy = 0.1))

Financing Schemes: France

Government, Voluntary Insurance, Out-of-Pocket (% of GDP)

hlth_sha11_hf %>%
  filter(geo == "FR",
         icha11_hf %in% c("HF1", "HF2", "HF3"),
         unit == "PC_GDP") %>%

  year_to_enddate %>%
  ggplot + geom_line(aes(x = date, y = values/100, color = Icha11_hf)) +
  theme_minimal()  +
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = 0.01*seq(0, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

Latest Year: Health Expenditure per Inhabitant (All Financing Schemes)

latest_year <- hlth_sha11_hf %>%
  filter(icha11_hf == "TOT_HF", unit == "EUR_HAB", !is.na(values)) %>%
  summarise(m = max(time)) %>%
  pull(m)

hlth_sha11_hf %>%
  filter(time == latest_year,
         geo %in% c("FR", "DE", "IT", "ES", "NL"),
         icha11_hf == "TOT_HF",
         unit == "EUR_HAB") %>%
  select(geo, Geo, values) %>%
  arrange(-values) %>%
  print_table_conditional()

geo	Geo	values
DE	Germany	6323.38
NL	Netherlands	6295.67
FR	France	4899.88
IT	Italy	3158.69