class: center, middle, inverse, title-slide # Module 4: Difference-in-Differences and Effects of Medicaid Expansion ## Part 1: Medicaid Expansion and the ACA ### Ian McCarthy | Emory University ### Econ 470 & HLTH 470 --- <!-- Adjust some CSS code for font size and maintain R code font size --> <style type="text/css"> .remark-slide-content { font-size: 30px; padding: 1em 2em 1em 2em; } .remark-code { font-size: 15px; } .remark-inline-code { font-size: 20px; } </style> <!-- Set R options for how code chunks are displayed and load packages --> # Affordable Care Act <br> .center[  ] --- # Background 1. What percent of people are uninsured? -- .plot-callout[ <img src="04-medicaid-uninsurance1_files/figure-html/unins-plot-1.png" style="display: block; margin: auto;" /> ] --- # What percent of people are uninsured? <img src="04-medicaid-uninsurance1_files/figure-html/unins-plot-big-1.png" style="display: block; margin: auto;" /> --- # Background 1. What percent of people are uninsured? 2. How do people get health insurance? -- .plot-callout[ <img src="04-medicaid-uninsurance1_files/figure-html/type-2012-plot-1.png" style="display: block; margin: auto;" /> ] --- # How do people get health insurance? <img src="04-medicaid-uninsurance1_files/figure-html/type-2012-plot-big-1.png" style="display: block; margin: auto;" /> --- # Employer provided insurance The U.S. still relies heavily on private insurance provided by employers. -- <br> <br> Any thoughts on why? --- # Employer provided insurance 1. Stabalization act of 1942 (wages frozen but not benefits) 2. Tax exclusion for insurance expenditures (1954) --- # How did the ACA change things? <ol> <li>Create health insurance exchanges <ul> <li>Individual mandate (since set to $0)</li> <li>Premium and cost-sharing subsidies (some unpaid by Trump administration)</li> <li>Insurance subsidies (removed before intended)</li> <li>Decision assistance</li> <li>Minimum benefits and community ratings</li> </ul> </li> <br> <li>Stay on parent's plan to 26</li> <ol> --- # How did the ACA change things? <ol start="3"> <li>Medicaid Expansion <ul> <li>Originally tied to federal funding</li> <li>Made voluntary by supreme court ruling</li> <li>Higher initial federal match rate, decreasing over time</li> </ul> </li> <br> <li>Pay-for-performance measures <ul> <li>Hospital value-based purchasing</li> <li>Hospital readmission reduction</li> <li>Medicare Advantage quality improvement program</li> <li>Bundled payments and ACOs (related)</li> </ul> </li> </ol> --- # Change in Insurance Type over Time <div 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Purchase","Employer-provided","Medicaid","Medicare"],"x":[0.0806036276569507,0.579125745813671,0.114603533755159,0.0134016721910019],"frame":"2018","type":"bar","orientation":"h","marker":{"color":"rgba(31,119,180,1)","line":{"color":"rgba(31,119,180,1)"}},"error_y":{"color":"rgba(31,119,180,1)"},"error_x":{"color":"rgba(31,119,180,1)"},"xaxis":"x","yaxis":"y","visible":true}],"traces":[0]}],"shinyEvents":["plotly_hover","plotly_click","plotly_selected","plotly_relayout","plotly_brushed","plotly_brushing","plotly_clickannotation","plotly_doubleclick","plotly_deselect","plotly_afterplot","plotly_sunburstclick"],"base_url":"https://plot.ly"},"evals":[],"jsHooks":[]}</script> --- # Data sources We'll use two main data sources here: 1. Data on which states expanded Medicaid (and when - Available from *Kaiser Family Foundation* 2. Data on insurance status and source of health insurance by state - Available from the *American Community Survey* - These data can be tricky to work with due to their size, but there are some handy tricks in `R` --- # Data sources Code and links available at the [Insurance Access GitHub repository](https://github.com/imccart-test/insurance-access) --- # Medicaid Expansion - Directly downloaded from KFF website - Just a raw .csv file --- # Insurance status and source - Data from the American Community Survey - CPS data also available but questions changed in 2014 - Easiest way to access ACS data is through a Census API and the `acs` package...details on the *GitHub* repo --- # What is an API? - Stands for application programming interface - An official way for one computer to request information from another - Often requires a code for external program/server to validate the request --- # Describing the data First let's take a look at the final dataset ```r head(ins.dat %>% arrange(year, State)) ``` ``` ## # A tibble: 6 × 20 ## State year adult_pop ins_employer ins_direct ins_medicare ins_medicaid ## <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 Alabama 2012 2937335 1528419 180043 56890 190312 ## 2 Alaska 2012 460946 222769 15608 2027 28177 ## 3 Arizona 2012 3866694 1867954 263076 41042 428972 ## 4 Arkansas 2012 1761365 871970 106277 39157 114012 ## 5 California 2012 23798381 12015639 1824564 180861 2275053 ## 6 Colorado 2012 3270163 1801613 303179 27254 213045 ## # … with 13 more variables: uninsured <dbl>, expand_ever <lgl>, ## # date_adopted <date>, expand_year <dbl>, expand <lgl>, perc_private <dbl>, ## # perc_public <dbl>, perc_ins <dbl>, perc_unins <dbl>, perc_employer <dbl>, ## # perc_medicaid <dbl>, perc_medicare <dbl>, perc_direct <dbl> ``` --- # Summary stats And now for some basic summary stats (pooling all years): ```r stargazer(as.data.frame(ins.dat %>% select(perc_unins, perc_direct, perc_medicaid)), type="html") ``` <table style="text-align:center"><tr><td colspan="8" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Statistic</td><td>N</td><td>Mean</td><td>St. Dev.</td><td>Min</td><td>Pctl(25)</td><td>Pctl(75)</td><td>Max</td></tr> <tr><td colspan="8" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">perc_unins</td><td>364</td><td>0.140</td><td>0.058</td><td>0.036</td><td>0.093</td><td>0.181</td><td>0.305</td></tr> <tr><td style="text-align:left">perc_direct</td><td>364</td><td>0.081</td><td>0.020</td><td>0.030</td><td>0.067</td><td>0.093</td><td>0.141</td></tr> <tr><td style="text-align:left">perc_medicaid</td><td>364</td><td>0.104</td><td>0.060</td><td>0.028</td><td>0.062</td><td>0.132</td><td>0.417</td></tr> <tr><td colspan="8" style="border-bottom: 1px solid black"></td></tr></table> --- # Uninsurance over time ```r ins.dat %>% group_by(year) %>% summarize(mean=mean(perc_unins)) %>% ggplot(aes(x=year,y=mean)) + geom_line() + geom_point() + theme_bw() + labs( x="Year", y="Fraction Uninsured", title="Share of Uninsured over Time" ) + geom_vline(xintercept=2013.5, color="red") ``` .plot-callout[ <img src="04-medicaid-uninsurance1_files/figure-html/unins-plot-small-1.png" style="display: block; margin: auto;" /> ] --- # Uninsurance over time <img src="04-medicaid-uninsurance1_files/figure-html/unins-plot-big-1.png" style="display: block; margin: auto;" /> --- # Direct purchase over time ```r ins.dat %>% group_by(year) %>% summarize(mean=mean(perc_direct)) %>% ggplot(aes(x=year,y=mean)) + geom_line() + geom_point() + theme_bw() + labs( x="Year", y="Fraction with Direct Purchase", title="Share of Direct Purchase Insurance over Time" ) + geom_vline(xintercept=2013.5, color="red") ``` .plot-callout[ <img src="04-medicaid-uninsurance1_files/figure-html/direct-plot-small-1.png" style="display: block; margin: auto;" /> ] --- # Direct purchase over time <img src="04-medicaid-uninsurance1_files/figure-html/direct-plot-big-1.png" style="display: block; margin: auto;" /> --- # Medicaid over time ```r ins.dat %>% group_by(year) %>% summarize(mean=mean(perc_medicaid)) %>% ggplot(aes(x=year,y=mean)) + geom_line() + geom_point() + theme_bw() + labs( x="Year", y="Fraction with Medicaid", title="Share of Medicaid Insurance over Time" ) + geom_vline(xintercept=2013.5, color="red") ``` .plot-callout[ <img src="04-medicaid-uninsurance1_files/figure-html/mcaid-plot-small-1.png" style="display: block; margin: auto;" /> ] --- # Medicaid enrollment over time <img src="04-medicaid-uninsurance1_files/figure-html/mcaid-plot-big-1.png" style="display: block; margin: auto;" /> --- # Main takeaways <ol> <li>Large reduction in uninsured population following ACA</li> <li>Biggest gains going to direct purchase (exchanges) and Medicaid (expansion)</li> </ol> -- <br> <br> But what amount of extra insurance is *due to* Medicaid expansion? In other words, who got insurance through Medicaid that wouldn't have gotten it otherwise? --- # What does the literature say The *Kaiser Family Foundation* has some great info on this... <br> - [KFF Medicaid Coverage](https://www.kff.org/medicaid/) - [KFF Report on ACA Expansion](https://www.kff.org/medicaid/issue-brief/the-effects-of-medicaid-expansion-under-the-aca-updated-findings-from-a-literature-review-august-2019/) - [Health Insurance and Mortality](https://www.nber.org/papers/w26533) (not what we're discussing here but still important)