Healthcare Data Visualization

Transform Healthcare Data Into Compelling Visual Stories  

Healthcare organizations collect vast quantities of complex data from disparate sources, but this data is of limited use if its locked in silos, buried in tables, and lacking context. To get the full value of data, healthcare professionals need the insight provided by data visualization. 

Clinicians who are skilled in data visualization tools and techniques can efficiently recognize patterns and identify correlations. They can bring into focus the key points of any dataset and transform complex information into easily interpreted stories. The result is improved patient outcomes, enhanced health delivery system performance, and optimized business operations.

A SELF-PACED Micro-Course

In this asynchronous micro-course, you will learn how to use open source tools to tell data stories. We will examine, cleanse and transform publicly available datasets based on COVID-19 transmission rates. Then we we will recreate – and improve upon – the original visuals that were provided by Georgia's Department of Health.

The course is offered in conjunction with Stony Brook's School of Health Professions and was created and will be led by Dr. Hants Williams, who is both a public health nurse and a data specialist. While the course is self-paced, Dr. Williams will be available for guidance through a Microsoft Teams channel.

Who Should Take This Course

This is a class for practitioners. You do not need to be a data scientist or have specialized knowledge to benefit from this course. The course will have the most value for:

• Physicians, physician assistants, nurse practitioners, nurses, and clinicians 
• Healthcare staff in hospitals, medical groups, clinics, and community care centers
• Professionals working in life science, health science, public health, medical insurance, pharma industries, and other related fields
• Data analysts, medical informatics analysts, technical specialists,  healthcare consultants, and anyone seeking careers in healthcare analytics

Tools You Will Use

You will learn to use open-source software packages, such as Python and Jupyter Notebooks (Google Colab), along with common data transformation and visualization packages that include Pandas and Plotly.

COurse OUtcomes

By the end of this course, participants will be able to:

• Understand the principles of data preparation, analysis, and visualization in Python
• Know sources and techniques for the acquisition and management of publicly available health data
• Understand the methods and techniques for the visualization of longitudinal, population health data
• Be introduced to common Python visualization libraries (Seaborn, Matplotlib, Plotly) in the creation of visualizations that range from simple to complex