KHN’s Liz Lucas shares how data can power your reporting on health disparities

Published on
December 4, 2020

Journalists play a critical role in highlighting health disparities, a task that’s become even more vital  amid the pandemic’s uneven toll.

Data can provide reporters with powerful tools for investigating health inequities, Kaiser Health News data editor Elizabeth Lucas told journalists via Zoom at the Center for Health Journalism 2020 Data Fellowship this week.

“It adds an additional lens: Are there groups of people disproportionately affected by these problems?” she said.

Lucas gave examples of how journalists are using data in disparity coverage and highlighted useful health data sets. She also cautioned participants about data’s limitations and shared three steps journalists should follow as they crunch the numbers.   

Spotlighting disparities  

The pandemic has provided “a brutal example” of health care disparities as COVID-19 has disproportionately impacted certain racial and ethnic groups, Lucas said. Lucas and Kaiser Health News colleagues have investigated some of these health inequities, drawing on data to strengthen the stories’ narrative.  

Lucas worked with Laura Ungar on an article looking at Americans living without adequate running water or in overcrowded homes — factors that increase their risk of contracting COVID-19. The article used data from the Census Bureau and the Housing Assistance Council in Washington, D.C.

Similarly, journalists Anna Maria Barry-Jester and Angela Hart investigated the pandemic’s impact on California’s homeless population, a group with high levels of underlying health conditions who live in conditions that place them at high-risk for COVID-19 infection.  

She also pointed to ProPublica’s work looking at how black workers are more likely to be unemployed but less likely to receive the expanded unemployment benefits offered during the pandemic. 

Where to find data

Data plays an important role in telling these stories of disparities, providing answers to questions such as: How many, where, how long, and who’s the worst?

During the pandemic, journalists have created some of the best data tracking resources available, she said. Lucas pointed to The COVID Tracking Project, Big Local News, The New York Times’s case tracker, as well as the Centers for Disease Control’s provisional death data.

Other useful sources: The United States Interagency Council on Homelessness, the government’s nursing home data, and resources compiled by data journalist Jacob Fenton.   

To examine disparities themselves, check out County Health Rankings, a site from the Robert Wood Johnson Foundation that gauges the health of communities. There’s also the CDC’s Social Vulnerability Index, which measures how likely a community can handle a disaster. And, Census Reporter can be useful to add local data to your story.

Data’s limitations

Every dataset Lucas has ever encountered has had an issue she’s had to ferret out, she said.  

Take a close look at your data’s possible shortfalls and limitations. For example, coronavirus testing data might include false positives, or one person could have taken multiple tests. It also doesn’t tell us how severe a case was. While death data is more accurate, the cause of death can be delayed for months.

Make sure to read the documentation about the dataset, such as the CDC’s Understanding the Numbers about provisional death counts. Footnotes are also very important in pointing out missing pieces.

Consider what you want to compare with your data, whether it’s one county to another or one racial group to another, Lucas said.

Another tip: Check to see if the numbers were adjusted, a way of shifting data to make fairer comparisons. For example, hospitalization figures could be adjusted to account for differences such as an older population that is more likely to be hospitalized.

In your article, be transparent about your data sources and methodology.

Three steps to follow 

There are three steps data journalists should always follow, Lucas said.

  • Know your data: Read all the documentation and footnotes, and check all the columns. “It’s quite tedious, but it’s really important so you really know what’s in your data.”
  • Keep a detailed log: Save a copy of your original data. Take notes on your analysis and process. Mark what you have discovered, what queries you’ve run, and how you’ve arrived at your calculations. This can be a helpful reminder if you have to take a break from a project. It’s also useful to have this log when editors have questions.
  • Have someone check your work: Talk through your methodology with a data journalist, trusted reporter or editor. Also, run your findings by at least one expert.

Ultimately, the combination of data and personal narratives can be a powerful tool in shining a light on health disparities. While many root causes of inequities are entrenched, highlighting small sections of data can have an impact, Lucas said. For example, examine what affordable housing policy looks like in your community. Is there anything in the zoning code that helps or hurts that?  

 “It’s like taking a tiny little bite out of this giant monster,” she said. “But, particularly for local reporters, that’s really where there can be some really significant work done.”