Patterns in the U.S. Health Insurance rate from 2010 to 2019

Data Visualization

My Roles

Research, Concept Development, UX Wireframing, Narrative Structure Development, Interaction Design, UI Design

Tools

Figma

Timeline

4 weeks (2021)

Team

Elaine Lu, Greg Chen

Overview

We were tasked to analyze data sets, find out meaningful relationships, and create data visualization to communicate our findings. Our data sets were about health insurance status by educational attainment and race from. 2010 to 2019.

We’ve all seen data visualizations—some of them effective; many of them simply interesting graphics. Despite common communication problems that arise in their delivery of information, data visualizations have become a prevalent form of conveying “facts.” In this project, we’re asked to illuminate connections among data in ways that help viewers recognize, engage in, and think critically about important inherent relationships, that may not be apparent or may be overlooked.

                    Therefore, in this project we learned and applied communication strategies that help us make sense of dense information and aid the communication of our discoveries to others. 

Outcome

What can changes in the percentage of insured people overtime at the country, state, and city levels tell us about the adoption of ACA and Medicaid in the U.S.?

Guiding Questions

The beginning is guided by subsequent questions that lead viewers to meaningful findings.

The U.S Level

Viewers see the insurance rate changes in the U.S. Also this part gives an overview of how interaction works.

The State Level

Choosing a circle or a year moves to the state level

Insurance Rate Trend of the States

Viewers can see trends of particular states, up to 3 at once.

Data Overlay

The filter turns on additional data worth comparison over existing data.

'Walkthrough' Prototype

We presented a demo of our prototype that highlights our important discoveries. Our data visualization has a form of a website, that guides viewers according to the narrative structure that consisted of a series of questions, providing information interactively. 

Narrative Structure

Indexical Structure

Expansion of Medicaid

By moving the timeline, viewers can see when each state adopted the expansion of Medicaid.

Insurance Rate Trend of the Cities

Same as the state-level.

The City Level

By double-clicking a state, viewers go into the city level.

Process 1/2

Developing Research Question

Finding connections

To forster research question, we started by jotting down data we wanted to use for our research on health insurance status from the US to Pittsburgh. Then, we wrote questions that we have derived from data sets. While writing down rough ideas, we discussed which data is accessible and which data sets can be related to each other.

While investigating data, we began to wonder which factor would effect for people to get insured, and who can help people get health insurance. 

We came up with the Obamacare. We thought it would be great if we could compare the uninsured rate before and after the act, showing the trend of the uninsured rate. 

Policies, and Policy makers

Guiding Questions and Cleaning Data Sets

What changes did the enactment of ACA in 2010 bring to the percentage of insured people?

% of insured people in the USA from 2010 to 2019 YoY

What changes did the Medicaid expansion in 2014 bring to the percentage of insured people?

Year that Medicaid expansion was adopted by states

% of insured people in 50 states and cities from 2010 to 2019 YoY

The gap between everyone (people of all income levels) and people below 138% of the federal poverty line decreased in the US, states, and cities after the adoption of Medicaid expansion

Relationships & interesting discoveries

Wrap up

Are the ACA and Medicaid expansion the primary reasons for the significant increase of insurance rates?

 

What other factors affect whether people get insurance, e.g. employment rate, price of insurance, etc.?

 

Besides insurance rates, what other changes did ACA and Medicaid expansion bring to the U.S.?

Reflections

Questions we now raise

Visualizing Data

Process 2/2

Narrative and Indexical Structure

To show our findings in a narrative structure, but still let viewers navigate data on their own, we combined indexical structure to our narratives.

Structure Map and Narrative/ Indexical structures in UI design

Pathway

Scales, Range, Buckets

Based on the guiding questions and data that we collected, we made decisions on how to organize and visualize data.

Visual Keys

Coordinate System

Shapes/ Styles

UI design

For consistency and efficiency of the working process, we built systems.

As we represented the insurance rate with circle size, visibility of the change of the sizes was crucial. To make sure that each circle fit into grid showing notable changes, we converted actual numbers into pixel numbers of circle sizes.