<commit_before>---
layout: post
title: What is the appropriate population scaling of the Affordable Care Act Funding?
subtitle: Analysis of the effects of the Graham-Cassidy Bill on the ACA population
tags: [healthcare, ggplot2, geofacet]
---

I have been trying to decipher for myself, what is in the current (well, yesterday's) Graham-Cassidy health care bill. I saw this image on many news outlets a few days ago and my inner hate for pie charts bubbled up.

![](https://raw.githubusercontent.com/yonicd/yonicd.github.io/master/img/aca/ACA_pie_full.jpg)

This is a zoom in on the pie chart ... From what I can gather, these figures are attempting to say that there are specific states that are getting relatively more of the federal health care funds under the Afordable Care Act (ACA) than their relative state population. Among the many things that are really hard to do with pie charts , comparing distributions ranks pretty high up there.

![](https://raw.githubusercontent.com/yonicd/yonicd.github.io/master/img/aca/ACA_pie.png)

It is common practice when comparing different geographical areas that have different populations levels to scale it using the rate per person (per capita) or per number of people, e.g. rate per 1,000 people. In this case it would be population adjusted state federal funding. The question that needs answering, what is the relevant population. 

Many charts in the last week have scaled the funding adjusted to state population (as is alluded to in the figure above), but the funds are not actually being used by everyone in each state, most people have health care from their employer. So, what is the actual population that is being serviced by the federal funding for the ACA? How much of a different picture does that paint from the original figure? 

Hopefully this post will help motivate readers to start looking around for more data on what is the effect of the proposed bill on the approprations of federal funds on the state level. 

My sources of information is the Kaiser Family Foundation site that have a great database for data on the ACA and the proposed bill, and Wikipedia for auxilary population data. We will end up with the following figure, but along the way I learned a number of things that I didn't know from reading online and seeing the news on TV. 

![](https://raw.githubusercontent.com/yonicd/yonicd.github.io/master/img/aca/unnamed-chunk-17-1.png)<!-- -->

A quick note before you proceed - This is not meant to be an all encompassing analysis of the predicted effects of the Graham-Cassidy bill, as it has been said before: "Healthcare is hard...", and if I made any bad assumptions I apologize in advanced and welcome any comments and suggestions to better understand the subject matter. 

Saying that, let's continue: <commit_msg>add rstats tag to aca<commit_after>---
layout: post
title: What is the appropriate population scaling of the Affordable Care Act Funding?
subtitle: Analysis of the effects of the Graham-Cassidy Bill on the ACA population
tags: [rstats, healthcare, ggplot2, geofacet]
---

I have been trying to decipher for myself, what is in the current (well, yesterday's) Graham-Cassidy health care bill. I saw this image on many news outlets a few days ago and my inner hate for pie charts bubbled up.

![](https://raw.githubusercontent.com/yonicd/yonicd.github.io/master/img/aca/ACA_pie_full.jpg)

This is a zoom in on the pie chart ... From what I can gather, these figures are attempting to say that there are specific states that are getting relatively more of the federal health care funds under the Afordable Care Act (ACA) than their relative state population. Among the many things that are really hard to do with pie charts , comparing distributions ranks pretty high up there.

![](https://raw.githubusercontent.com/yonicd/yonicd.github.io/master/img/aca/ACA_pie.png)

It is common practice when comparing different geographical areas that have different populations levels to scale it using the rate per person (per capita) or per number of people, e.g. rate per 1,000 people. In this case it would be population adjusted state federal funding. The question that needs answering, what is the relevant population. 

Many charts in the last week have scaled the funding adjusted to state population (as is alluded to in the figure above), but the funds are not actually being used by everyone in each state, most people have health care from their employer. So, what is the actual population that is being serviced by the federal funding for the ACA? How much of a different picture does that paint from the original figure? 

Hopefully this post will help motivate readers to start looking around for more data on what is the effect of the proposed bill on the approprations of federal funds on the state level. 

My sources of information is the Kaiser Family Foundation site that have a great database for data on the ACA and the proposed bill, and Wikipedia for auxilary population data. We will end up with the following figure, but along the way I learned a number of things that I didn't know from reading online and seeing the news on TV. 

![](https://raw.githubusercontent.com/yonicd/yonicd.github.io/master/img/aca/unnamed-chunk-17-1.png)<!-- -->

A quick note before you proceed - This is not meant to be an all encompassing analysis of the predicted effects of the Graham-Cassidy bill, as it has been said before: "Healthcare is hard...", and if I made any bad assumptions I apologize in advanced and welcome any comments and suggestions to better understand the subject matter. 

Saying that, let's continue: 
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