Impact of AHCA on Number of Uninsured Persons

ahca_visualization.R

# Uninsured persons estimates for ACA
# Centers for Disease Control and Prevention National Health Interview Survey
# https://www.cdc.gov/nchs/data/nhis/earlyrelease/insur201702.pdf 
# (see Table II, page A3)

# ACA data estimates through 2016: absolute uninsured
aca_data <- approx(c(2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2020, 2026),
                   c(48.6,46.3,45.5,44.8,36,28.6,28.2,28.2,28.2,28.2,28.2), n=17)

# Uninsured persons estimates for AHCA from Congressional Budget Office
# https://www.cbo.gov/sites/default/files/115th-congress-2017-2018/costestimate/americanhealthcareact_0.pdf
# (see "Effects on Health Insurance Coverage", page 2)

# AHCA data estimates for 2018, 2021, and 2026: additional uninsured relative to ACA
ahca_data <- approx(c(2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2020, 2026),
                    c(0,0,0,0,0,0,0,0,14,21,24), n=17)

uninsured <- data.frame(Year=ahca_data$x, Uninsured=ahca_data$y, Plan="AHCA")
uninsured <- rbind(uninsured, data.frame(Year=aca_data$x, Uninsured=aca_data$y, Plan="ACA"))

plot <- ggplot(uninsured, aes(x=Year, y=Uninsured, fill=Plan)) + geom_area()

plot <- plot + scale_x_continuous(breaks=pretty(uninsured$Year, n=17))
plot <- plot + scale_fill_manual(values=c("#D55E00", "#0072B2"))

plot <- plot + labs(y="Uninsured Persons (in Million)", 
                    x="Year")
plot <- plot + labs(title="Impact of AHCA on Number of Uninsured Persons", 
                    subtitle = "Based on estimates from the CDC and CBO / Code + Data: https://gist.github.com/ngehlenborg/84775d09cd192bd70ea39562c35453f6", 
                    caption="@nils_gehlenborg" )

ggsave("ahca_uninsured_persons.png", plot)

Sampling of Similar Visualizations from Major News Outlets

New York Times

Wall Street Journal

Washington Post

Bloomberg