Public Health in the USA: How Dataviz Moves Government Toward Equity
Series: Communicating Data for Health Impact
In the USA, government public health agencies are responsible for vast quantities of data: collecting it, analyzing it, and reporting it. Traditional data visualization in public health reporting is similar to other scientific fields: often filled with the type of Excel-charts style defaults common in environments that lack specialists in data communication or design.
However, as open data and civic service design movements gain steam, data visualization offers a path toward information equity: making more information available and understandable to more people. More public health agencies are making data available via interactive data explorer websites. Let’s take a look at what good data visualization can offer.
But first, some background
Public health is a field that runs on data. Throughout the USA, epidemiologists at public health agencies run by the federal government, the 50 states, and cities and counties across the country collect and analyze data to understand the causes of diseases or the patterns in how they appear throughout the population.
Let’s take a look at an example: you become short of breath. Your chest gets tight, and you start to wheeze. A hit on your inhaler usually settles things down, but not this time. It’s bad, so you head to the emergency room. There, they give you more powerful medication and monitor you as symptoms subside.
The hospital reports your admission to public health agencies. An epidemiologist will analyze anonymized admissions data, turn counts of all asthma emergency department visits into rates, compare asthma rates in different areas, and review other data — on, perhaps, air quality, housing quality, traffic volume, or industrial emissions — to understand what could be causing variations. The goal is to answer questions that can inform policies and activities: who’s getting sick, and why? What’s affecting asthma rates in the area? What should people do to stay healthy?
So where does the data go and what does it look like?
A lot of these data are analyzed for research and reporting purposes: trying to figure out what issues health organizations and public policy should focus on.
The data — and the visualizations that communicate them — often wind up in reports that stay inside the government. There’s a large population of .pdfs live deep within .govs.
The data visualization in reports like these often reflect a certain traditional approach common in the sciences. We often see basic values-reporting data visualization that doesn’t show data communication or data design practices that are common in the wider data visualization field:
Thinking bigger
Government public health organizations often want to communicate their findings to “the general public” as part of work to increase people’s understandings of what affects health on a large scale, and to encourage people to take up evidence-based health behaviors. And clearly, pdf reports intended for policy, professional, and health-focused audiences won’t cut it.
In recent years, government public agencies have been building data portals — websites that allow users to explore and visualize public health data. This is great work: communicating data clearly and openly has the potential to increase transparency, increase trust in government work, and communicate important information that can foster greater understanding and civic engagement and health behaviors.
But just putting information on a website doesn’t make it useful — some systems, especially ones with a huge volume of data, reflect the struggle to dynamically generate data visualizations while still providing communicative power and usable, engaging design.
Visualizing data is important for modernization
As open data movements encourage government agencies to publish data, more government agencies are exploring civic service design, employing user-centered design to create more open, transparent, and usable digital information. They’re building systems with better design, usability, and communicative power.
For example, take a look at the Healthy LA Health Profiles:
Here, we see a system that offers a lot of data in an easy-to-use display. It provides values and their context, compares values to benchmarks, and is designed to clearly and simply highlight the data.
With this example, we see that data vis in public health work doesn’t need to be innovative to be effective. To explain complicated information, communicate government messages in an understandable, trustworthy manner, and provide reasons for people to adopt health behaviors, government agencies can take great steps by bringing their data visualization in line with contemporary digital design standards.
While government public health agencies are still building their capacity, private organizations are sometimes leading the way: for example, Data2Go visualizes public-sector data in a system that’s easier to access, understand, and use than most public agencies accomplish. It combines contemporary design, web usability, and data visualization techniques for greater communicative power.
Visualizing data is crucial to communicating it
What should data vis in public health look like? Tools that most people can understand and use.
In fact, moving from jargon- and science-heavy .pdfs buried deep within government websites and moving towards systems that are simpler and more usable represents a shift toward information equity: designing information so that it can be more accessible to more people.
Communicating data is crucial towards acting on it
Public health is a data-driven field. It’s also a field that attempts to be inherently interdisciplinary: the Health in All Policies movement works to ensure that public health considerations are baked into public policies across a wide range of disciplines so that we can build a healthy and equitable society.
This means making more data and more information available to more people. And that means better data vis — and more of it.
There’s plenty of skepticism toward government. Public health professionals fight uphill battles against forces of vaccine skepticism, science denial, and widespread modes of social thought that reframe structural issues as individual shortcomings. Mistrust of elected officials blends into a mistrust of all government work — even of civil servants working to improve the health of the communities in which they live.
Improving digital communications using data visualization, though, has the potential to shorten the distance between people and their government. Transparent, easy-to-understand information from government can help build trust. And in public health, we can and must report our data and analyses in open, honest, communicative ways that are available and accessible to all citizens, residents, and constituents of our work. We can’t do that without good data visualization.
