Feb 01

Visualize your data

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Data visualization describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software. I decided to put this to the test and visualize our international eHealth experience at eHealthMasterminds. In Healthcare data visualization can also take on a whole new meaning.



3 ways that data visualization can help in healthcare

  • Patient treatment with alerts to healthcare providers about patients that need urgent attention that may otherwise go undetected or improving medication tracking and decision support.
  • Advancing Research by providing a way to summarize, filters, and present large amounts of information with visualization tools. Also helping to perform scenario analysis, such as, how intervention delivers different outcomes for patients in different age groups.
  • Public Health with visualization approaches for early detection of disease and other global health concerns such as flu pandemics and bioterrorism.

3 major lessons we have learned about data visualization in eHealth

  • While there is a lot of good resources available there has been limited uptake
  • Poor quality data will display poor quality results. However, on the flip side visualization may allow you to quickly sometimes see potentially dangerous errors and omissions. Data visualization can be worthwhile for the data cleaning capabilities alone.
  • Multi-disciplinary teams need to work together to understand and display data that is meaningful to the user.

Data visualization not only provides a new way of viewing data but also raises question on what data you can use. According to Roni Zeiger, former Chief Health Strategist at Google,  “Google Flu Trends re-imagined how we gather medical information and track diseases. Flu Trends monitors the spread of the flu around the United States by processing how often people search for “flu” on Google. Its results are almost identical with those of the U.S. Centers for Disease Control and are available weeks before the official numbers.”

However, the true promise of data visualisation to advance medicine will come when we can statistically analyze anonymized electronic health records of large populations. The secrets of treatment success and failures are locked within the accumulating data of electronic medical records but those benefits will only be realized when the interoperability of medical records improves.


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