Efficient, meaningful data analysis is at the core of some of today’s most important medical studies. It’s also essential for physicians, nurses, and other health professionals during their day-to-day practice as they interact with health interfaces and databases, generate reports, and review patient information and trends.
But a mountain of data is of little use without data visualization. Data visualization brings the most important takeaways in the health industry into focus, helps us identify patterns and correlations, and makes data analysis more efficient.
Most people don’t need to know every detail of how a study was conducted; they need quick, actionable takeaways. That’s where data visualization can help.
For all these reasons, it’s safe to say that the health industry today could hardly survive without data visualization. In this post, we’ll dive into all the ways health care institutions are harnessing this essential medium — and offer some ideas on how you can too.
The common misconception about sharing big datasets is the more data, the better. This is certainly true when you’re conducting a medical study. When you’re sharing the results of that study, however, it’s not always the case.
When you’re publishing a paper, you’ll probably want to include complete datasets in a series of appendices. This is standard in health care and the sciences, and is done for the sake of transparency, as well as to provoke discussion.
But you might also want to include data visualizations that present key takeaways, and these shouldn’t try to visualize everything — far from it. You’ll want to highlight only the most compelling data, and represent that data clearly by making sure it’s not cluttered with other, less compelling information. Check out the infographics that the Agency for Healthcare Research and Quality is publishing for some examples.
These same types of visualizations can be used for sharing important information with patients or customers. They don’t need to know every detail of how a study was conducted; they need quick, actionable takeaways. Data visualizations of single data points, or mini-infographics featuring a small dataset, are ideal for sharing on social media. This social-media micro-narrative for medical equipment company ResMed offers a prime example of how impactful a mini-infographic can be:
Longer-form scrolling infographics are great for sharing on your website or in a blog post. Take a look at this excerpt from an infographic made for Breast Cancer Awareness Month, which takes a look at how donations are used:
Dashboards that help medical professionals quickly analyze large sets of data can save time and can even save lives. In one case study, the development of a dashboard to visualize electronic health record data resulted in a 65% reduction in time spent on data analysis in the first year alone, with further gains projected for the future.
Health industry leaders acknowledge the power of such tools.
“We have all of these disparate sources coming together, and leaders want to know how they use that to figure out why something is happening, what to do about it, and what to expect in the future,” explained Sanket Shah, director of client management at Blue Health Intelligence, in an interview with Health IT Analytics. “You can only get those answers by getting your hands on the actual data — and you can only understand it when it’s presented in a human-readable way. … Much of the time, unless you’re a highly trained data analyst, a visualization is the best way to make data comprehensible to the end user.”
A number of health organizations have started to publish graphs and charts that are custom made for the data they’re presenting. What’s more, they’re interactive and customizable according to the data the viewer wishes to see. (More on interactive content below.)
Data visualization brings the most important takeaways in the health industry into focus, helps us identify patterns and correlations, and makes data analysis more efficient.
The Institute for Health Metrics and Evaluation is just one of the many organizations sharing such visualizations. Check out their customizable visualization of cause-of-death data here.
The National Center for Health Statistics also offers some fantastic customizable graphs that distill huge datasets into usable data visualizations.
When you have a huge set of data to share, you can’t always select just a few key points to highlight. This is often the case when, for example, you’re looking at state-by-state health data across a variety of metrics. After all, certain aspects of that data may be more important than others to different members of your audience. Alaska doctors, for example, might primarily be interested in Alaska trends.
If this describes the kind of dataset you’re working with, an interactive widget may be the best fit for your content. Interactivity allows the viewer to customize the content or dataset to his or her needs and find that data quickly without having to wade through a lot of content they’re just not interested in.
For an example, click here to check out an interactive map from the American Academy of Pediatrics. Here’s a still image of the map, to give you an idea of what to expect:
If you’ve got a series of data visualizations that work together to tell a larger story, you might find it’s best to present them in the form of a motion graphic. While a live-action video is also an option if you have great footage, the data visualization will require at least some animation overlay.
“Much of the time, unless you’re a highly trained data analyst, a visualization is the best way to make data comprehensible to the end user.”
—Sanket Shah, Blue Health Intelligence
For an example of a fully animated video, take a look at “The History of Vaccines,” a motion graphic for Carrington College. The piece shares some fundamental information about how vaccines work and how they’ve been used over time, organized in such a way to create a narrative, a clear trajectory of thought. It’s a strong example of how the health industry can break down complex ideas so the average person can understand them:
The type of data you’re working with and the audience you’re targeting will both determine the best type of medium and data visualization to use. In just about any case, however, data visualizations make crunching big datasets more efficient, and yield bigger insights as a result. How can your organization use data visualization?
