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So, You Need Knee Replacement Surgery…

The Health 2.0 Developer Challenge team recently caught up with the 1st place winner of the RWJF Hospital Price Transparency Challenge (Static Visualization Category), Imaginary Office. Their winning submission, lead by Esther Chak and Mary-Jo Valentino, is an excellent visualization of recently released CMS charge data that helps consumers make a more informed decision when choosing a hospital to receive knee surgery.

Check out what they built and the thought process behind creating the winning submission!

HT: Tell us about Imaginary Office and your larger mission.

Imaginary Office (IO): Imaginary Office is a collaborative graphic design and communications studio founded by the two of us, Mary-Jo Valentino and Esther Chak. We design and develop print and web media for clients who need to communicate complex content — for example, the science behind ocean conservation, the feeling of a piece of classical music, or the effectiveness of public schools. We have been lucky to work with clients whose missions we support, from sustainable seafood, to clean water, to arts education.

HT: Why did you choose to participate in the RWJF Hospital Price Transparency Static Visualization Challenge?

IO: Our motivation to clarify some aspect of the healthcare or health insurance experience stems from a medical emergency that Mary-Jo had a few years ago. It was a wake-up call to both of us to take healthcare and insurance coverage more seriously. But, it’s not easy to understand—for us or for anyone, really.

As self-employed designers we had been following the healthcare reform journalism pretty closely. We clicked through many online articles and eventually stumbled upon a mention of the RWJF Challenge. That was the catalyst to realize an infographic that we had kept in the back of our minds since Mary-Jo’s medical emergency. The RWJF Challenge gave us an opportunity to develop the idea and share the outcome with an audience.

HT: What is your winning solution and how can it help consumers make better health care purchasing decisions?

IO: Our winning solution is a choose-your-own adventure information graphic—a poster. Our hypothetical patient needs knee replacement surgery. You follow her decision making process to choose a hospital, and compare it to your own choices. You then receive the resulting bill and compare it to other possible outcomes. The graphic can help consumers make better decisions by identifying what their choices are or could be. It’s not as simple as which item A or B would you like to buy right now. There are many long-term and short-term decisions that someone must make — Should I invest in health insurance now even though I’m healthy? Am I willing to travel? Is quality of care more important to me than cost? Will I negotiate?— that will impact the cost of healthcare for individuals.

We very deliberately did not develop an interactive piece (even though we have the capability to do so). As we dove deeper into the content we realized how disorienting this content is, and that before someone even looks at the data, any online tool, calculator, or app would need a clearly articulated description of the scenario at hand and what questions need to be asked and answered. That realization framed our approach.

Our primary goal was to make the data accessible, and we crafted an illustrated narrative to do so. When you first look at the data, it’s intimidating. There’s a lot of jargon, and it’s not clear what the terms or the numbers mean. After trying different approaches we determined that narrating one patient’s decision-making process and tracking your own choices against hers, was the clearest approach for this complex path. The graphic communicates both the chaotic complexity of the situation and several key decision-making points in the process.

There’s still a lot about this process that needs to be clarified. We found the most helpful information came from journalism, like Elisabeth Rosenthal’s recent in-depth health care coverage in the New York Times.

HT: What different data sources did you pull into the submission?

IO: We pulled from a variety of sources to understand healthcare-specific spending situations, and also consumer spending behaviors. The content that made it into our final graphic includes:

  • hospital charges and Medicare payments from Medicare’s CMS data
  • hospital quality measures from Medicare patient surveys (These are very murky so we were selective!)
  • the most pressing issues in healthcare purchasing from NY Times articles
  • health coverage statistics from the US Census Bureau and Kaiser Family Foundation
  • hospital ranking data from US News and World Report’s Best Hospitals issue
  • insurance pricing, discounts, plans, and policies for a patient in NYC from United Healthcare

It was important to us to cite accurately, since others might see the graphic and want to find the sources. They are all listed on the poster and on our submission at Visualizing.org.

We also sought feedback from friends and family in the medical field. Their insights were extremely helpful in developing our work, particularly in describing simplified, but more realistic patient paths. For example, even though the challenge focused on price transparency, patients don’t make decisions on cost factors alone. Cost is just one part of a complex process.

HT: How do you plan to make your visualization more available to consumers around the country?

IO: Anyone who’s interested can download the poster from our website: www.imaginaryoffice.com.

It’s shared under a Creative Commons license.

We’d also like to distribute the graphic more widely among our existing social networks, and to media outlets. In addition to our website it’s posted online on Facebook, Good.is, and Visualizing.org.

Categories: Uncategorized

2 replies »

  1. This are great news. It´s really important for citizens to have this kind of information available, this will make people decide better on their health insurance programs. But most importantly, I think that the key piece of the proyect is to make the data accesible in an understandable way so that readers can draw their own conclusions easily.