{"id":5923,"date":"2022-01-18T12:09:36","date_gmt":"2022-01-18T10:09:36","guid":{"rendered":"https:\/\/www.everviz.com\/blog\/?p=5923"},"modified":"2023-09-13T09:04:53","modified_gmt":"2023-09-13T09:04:53","slug":"visualizing-health-data-past-present-future","status":"publish","type":"post","link":"https:\/\/www.everviz.com\/blog\/visualizing-health-data-past-present-future\/","title":{"rendered":"Visualizing health data: Past, present, future"},"content":{"rendered":"\n

This is a guest blog post by Rebeca Pop, founder of Vizlogue<\/a>, a Data Visualization and Storytelling Lab that offers workshops and consulting services. You can find Rebeca on YouTube<\/a>, where she posts data visualization videos. Rebeca has been providing insights and creating data visualizations for almost 10 years. She has worked as a digital analytics leader for top media and analytics companies, and is teaching Data Visualization and Storytelling at the University of Chicago and at Northwestern University. Read more about Rebeca in her bio below.<\/a><\/em><\/p>\n\n\n\n

Let\u2019s start with a few key statistics. Healthcare takes more than 10% of the GDP of most developed countries. In fact, in 2020, 21% of the US GDP was spent on healthcare. That is more than any other US program. Healthcare amounted to 12.8% of the GDP in the UK and 11.3% of the GDP in Norway.<\/p>\n\n\n\n

What\u2019s more, according to RBC Capital Markets, \u201capproximately 30% of the world\u2019s data volume is being generated by the healthcare industry. By 2025, the compound annual growth rate of data for healthcare will reach 36%. That\u2019s 6% faster than manufacturing, 10% faster than financial services, and 11% faster than media & entertainment.\u201d In other words, healthcare is one of the largest and fastest-growing industries in the world.<\/p>\n\n\n\n

Given the large budget allocated to healthcare, the amount of data generated, and the rapid digitalization of the industry, data visualization is critical to understanding patterns, supporting healthcare practitioners, communicating with patients, and tracking digital personal data. In this blog post, I will present notable historical data visualizations, discuss a recent graph from the New York Times, review graphs used in my health apps, and talk about how the future of healthcare data visualization might look like.<\/p>\n\n\n\n

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Early public healthcare data visualizations<\/strong><\/h2>\n\n\n\n

When I think of historical public healthcare data visualizations, the first one that comes to mind is John Snow\u2019s map of the 1854 outbreak of cholera<\/a> in London. Cholera<\/a> was one of the deadliest diseases to affect Britain in the 19th<\/sup> century and at that time the belief was that the disease was transmitted by \u2018bad air\u2019 or \u2018bad smells\u2019 from rotting organic matter. John Snow\u2019s map represented a major contribution to the fight against cholera, as he was able to identify the source of the outbreak as the contaminated public water pump on Broad Street. Snow\u2019s findings literally changed lives. His work and map persuaded the local council to disable the water pump and led to changes in public health policies.<\/p>\n\n\n\n

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\nSource: John Snow \u2013 London Cholera Map<\/em><\/figcaption>
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Another major early example of healthcare data visualization is Florence Nightingale’s Rose Diagram. Nightingale was a nurse and statistician who, in 1858, was treating soldiers wounded in the Crimean War. She recorded the data manually and created a graph that illustrated how more soldiers were dying from infections and diseases than in fight. To date, Nightingale is remembered as a pioneer in visualizing health data. She revolutionized nursing and showed that presenting data in a clean, clear, and beautiful way can positively impact health policies and persuade governments.<\/p>\n\n\n\n

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\nFlorence Nightingale – Rose Diagram<\/em><\/figcaption>
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In more recent history, health data visualization has revolved around COVID-19 data. The majority of the pandemic graphs show trends over time in the form of line graphs or geographical data in the form of maps. The topic of COVID-19 data visualizations is broad and many articles and blog posts have been published. One recent graph that led to intense controversy and that will most likely remain in the history of data visualization as revolutionary was a spiral graph published in the New York Times<\/a>.  The graphic was created by Gus Wezerek and Sara Chodosh, and sparked discussions on whether a spiral graph was the best way to communicate data over time. The post below by Zach Freed went viral on Twitter, with almost 7,000 retweets and over 79k likes.<\/p>\n\n\n\n

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Source: Zach Freed, Twitter. The original graph was published in the New York Times by Gus Wezerek and Sara Chodosh<\/em><\/figcaption><\/figure><\/div>\n\n\n\n

The polarized opinions were not just among the general public, but also among experts in data visualization. Some thought that the spiral was unique and a persuasive approach to communicating with data, while others expressed strong disapproval.<\/p>\n\n\n\n


For example, Dr. Ellie Murray, ScD, an epidemiology assistant professor at the Boston University School of Public Health with over 107K Twitter followers retweeted the spiral graph saying that it was \u201cthe most unhelpful graph\u201d she\u2019s ever seen.<\/p>\n\n\n\n

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Source: Dr, Ellie Murray, ScD, Twitter<\/em><\/figcaption><\/figure><\/div>\n\n\n\n
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Other retweets were sarcastic, such as the one posted by Randall Koutnik, asking \u201ccan you make it more intestinal?\u201d<\/p>\n\n\n\n

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Source: Randall Koutnik, Tweeter<\/em><\/figcaption><\/figure><\/div>\n\n\n\n
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