You Can’t Spell Advocate without Data: Making the Case with Numbers & Visuals

Health centers have a unique advantage when it comes to demonstrating their value—access to publicly available, standardized data from all health centers receiving section 330 funds or look alike status designations. While that doesn’t make most people jump up and down, the Uniform Data System (UDS) is an important tool in demonstrating the services, economic impacts, patient characteristics, health outcomes, and innovations that health centers bring to their communities and the nation as a whole.  

Below are a few suggestions for making the most of your UDS data for health center advocacy, along with some other easy-to-navigate data resources at the end. This is far from a complete tutorial. Instead, we list some of the most useful rules for data presentations among the research staff here at NACHC. At its core, the best way to demonstrate health centers’ value with data is actually really simple. First, choose the right number. Second, make the number look really important.

Choosing the right number

A big problem with picking the right number is that you can say whatever you want with just about any number. Books like How to Lie with Statistics and How to Lie with Maps have great examples of this trickery. In the end, it’s all about how you frame your data and tell a story. That is not to say all data and numbers are untrue or outright lies, but rather, numbers are only as good as their story and it helps when the numbers are put in the proper context.

A few concrete tips for picking numbers:

  • It always helps people to have a reference point for a number. Some reference points are better than others. Don’t just say your health center serves 1,000 Medicaid beneficiaries, compare that with the nreseach_graphic1.pngumber of Medicaid beneficiaries in your service area. Alternatively, you can use percentages to compare your patient population (say, 50% are covered by Medicaid) to a suitable, geographical population (such as 22% of the U.S. non-elderly population covered by Medicaid).
    • To get those numbers on health insurance type, you can use UDS Mapper, which is especially useful for getting useful data in your health center’s service area.
  • Definitions are important. Make sure you know what your numbers mean. In the above bullet-point, I used the national non-elderly population to describe Medicaid enrollment. I essentially left out all people 65 and older, but the percentage I used is probably more honest because people 65 and older are enrolled in another public insurance program, Medicare, but the two programs are not mutually exclusive.
  • Always be honest and transparent with your numbers. It’s generally a good idea to cite your sources and let people know how you got to your findings. People will typically have questions about your findings, which is a good opportunity to underscore your larger narrative. Also, don’t be offended when people critique your numbers—be humble, be professional, and keep your composure. Use those critiques when you are anticipating future discussions or presentations.

Making the number look really good

Once you have found the right number, you want people to realize how important it is. Obviously, this means catering to your audience, but we suggest a few general guidelines to make your message more impactful. For most lay audiences, visuals are helpful, especially for getting a message across at a glance. Here at NACHC, we use a few different publishing programs, but one of our favorites—and one that is also 100% free—is piktochart.com, which is great for infographics and has a huge library of icons to accent your data points. You can also expand your skills on the standard Microsoft Office software. Our Funding Cliff Impact Estimator was done in Excel, for example, which produces a beautiful infographic once you enter your health center’s data.

A few concrete tips for better data visualizations:

Sample__Research_Blog_Graphic_(4).png

  • Have a reference point for your numbers (this is worth repeating). No one looks at a bar chart with one bar, or a pie chart with one slice. Give readers a baseline, and hopefully something they are familiar with.
  • Keep it simple and easy to read. You don’t need to visualize every data point, just the most striking. Whenever possible, sort your data from largest to smallest (or vice versa) to help people interpret your numbers quickly and easily.
  • When making charts, use as little ink as possible. This goes along with keeping it simple, but also think about the format of your chart. Do you have an axis and data labels? You really only need one. Are you showing how only one variable (say, revenues) changed since last year? There’s no need for a legend if there is only one option, but make sure the title clearly states what is in the chart.
  • Using the right colors can help people quickly identify the key data points in your visualizations. It also helps from a branding perspective and makes you look more professional. If you haven’t already, get the color codes (such as RGB codes common in Microsoft Office) for your organization to make the most of your visualizations.

A few references to get you started

Here are some easy to navigate data resources in case you want some reference points for your UDS data (in addition to UDS Mapper listed above):

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