About
LMI and the UVA School of Data Science are seeking innovative, impactful, and attainable solutions that use artificial intelligence (AI) and/or machine learning (ML) to address a health equity issue.
-
Currently in the United States, and many countries across the world, there is a lack of health equity. Health equity simply means that everyone, regardless of race, education, socioeconomic status, location, etc., can attain their full potential for health and well-being, and are not limited by social, economic, or environmental factors. This lack of equity leads to increased rates of disease, mortality, and disability as well as decreases in length and quality of life for affected individuals. Health inequity also comes at a high cost to both the patient and healthcare providers, taxpayers, and the government.
However, health equity can be achieved through collaboration and large-scale changes by community organizations, healthcare providers, scientists, government, etc. at a local, state, federal, and global level.
-
Your task is to develop a technical solution using your programming, AI, ML, data visualization, and application development skills that will support efforts to reduce health inequities. Because of the complexity of impacting health equity, you must also consider the feasibility and adoptability of your solution – how will people use it? Is it difficult to understand and interact with? How easy is it to distribute it to everyone who needs it? End users of your solution could be: doctors or nurses, patients, healthcare educators, medical students, health insurance companies, community health organizations, device manufacturers, or hospital administrators.
Challenge Expectations
- Form a team of 2-4 people. Consider who to include on the team to address both the data science approach and AI adoption/ change management aspects of the challenge.
- Identify a health equity topic that interests you.* Consider feasibility when selecting a topic, as that largely factors into evaluation. It's OK to address a smaller, but attainable, part of the broader issues.
- Create your solution:
- Build a prototype AI solution that addresses your health equity topic.
- Use data provided, and/or find publicly available data sources that augment what was provided. If you would like to use data that you have access to, but is not publicly available, please contact us.
- For this challenge, you do not have to build a final User Interface, however, your solution should include a way to show outputs and/or facilitate action.
- Develop a change management / adoption strategy -- How will you get people to engage with, and trust, what you built. Consider: who will your change affect, and what are its impacts? How will you communicate the changes and address feedback? How will you deliver training on this new technology?
- Present your solution:
- To register for the challenge, you will need to complete a 1-2 page Executive Summary outlining the topic you chose, your proposed technical solution, and your plan for adoption. Details for how to submit this document can be found on the Rules page.
- At the completion of this challenge, you will deliver a “Shark Tank” style presentation to our panel of judges. You may choose to do a PowerPoint presentation, share a recorded video, do a live demo, or present in another way that best demonstrates your technical solution and adoption strategy.
*For topic inspiration, visit the Resources page.
Registration Materials
Every team that participates in the competition must submit a short Executive Summary to our panel of judges. The purpose of this Executive Summary is to confirm interest in the data challenge and demonstrate progress. Optional feedback sessions will be available in mid-October 2023.
The following information is due by September 29, 2023 and should be submitted via the registration form on the Overview page. You can find a template for this on the Resources page.
- Team Name
- Team members (name, UVA email)
- Project Title (< 10 words)
- Description of project (< 500 words)
- What health equity issue are you focused on?
- What is your technical solution/approach?
- What is your current plan for adoption/change management? (Who is your target population? How will you deliver your solution? How will you communicate about it and train people on it? How will it be maintained?)
- List of data sources (as applicable)
- Do you have every data source you need? Is it publicly available?
Final Presentation
The final presentation will be a “Shark Tank” style presentation to our panel of judges. You may choose to do a PowerPoint presentation, share a recorded video, do a live demo, or present in another way that best demonstrates your technical solution and adoption strategy. Be creative!
You should plan for 15 minutes with the panelists. This includes:
- 10 minute presentation – the structure is up to you, but remember the evaluation criteria so make sure to include:
- What topic did you target?
- What is your technical solution?
- What is the outcome of your solution?
- How are you approach AI adoption and change management?
- 5 minutes Q&A with panel
