distribution of facility-level staffing ratios, by Census Region, June 2023

nursing_homes.R

library(tidyverse)
library(ggridges)

# state codes
states_regions <- read_csv("https://raw.githubusercontent.com/cphalpert/census-regions/master/us%20census%20bureau%20regions%20and%20divisions.csv") %>% 
  select(state_abb = `State Code`, region = Region) 

# CMS provider info
# https://data.cms.gov/provider-data/dataset/4pq5-n9py
raw <- read_csv("NH_ProviderInfo_Jun2023.csv") %>% 
  rename(
    staff_ratio = `Adjusted Total Nurse Staffing Hours per Resident per Day`,
    state_abb = State
  ) %>% 
  full_join(states_regions, by = "state_abb")

# draw a picture
my_palette <- viridisLite::viridis(7)

raw %>%
  filter(!is.na(region)) %>% 
  ggplot() + 
  geom_density_ridges(
    aes(x = staff_ratio, y = region, fill = region), 
    color = "white"
  ) + 
  scale_fill_manual(values = alpha(c(my_palette[1:4]), 0.7)) + 
  guides(fill = "none") + 
  hrbrthemes::theme_ipsum() +
  labs(
    x = "Total nurse hours per resident per day", 
    y = NULL, 
    title = "Distribution of facility-level staffing ratios, by Census region, June 2023"
  )