Evaluation Criteria
Problem Identification and Relevance (10%)
Definition: Assess how well the team identifies and articulates a significant healthcare problem that their solution addresses.
Key Considerations:
Clarity: Is the healthcare problem clearly defined and focused?
Audience Insight: Does the team understand the needs of their target audience (e.g., patients, providers)?
Relevance: Is the problem relevant to current healthcare challenges?
Rubric:
5: Clear, relevant, and deeply insightful on a high-impact healthcare issue.
3: Defined but lacks specificity or relevance.
1: Vague or minimally relevant to healthcare needs.
Technical Implementation (25%)
Definition: Assess the solution’s functionality, architecture, and overall technical execution, emphasizing effective use of tools and technologies.
Key Considerations:
Functionality: Does the solution work as intended and meet user needs?
Tool Integration: How effectively does it leverage generative AI and other open-source tools?
Architecture: Is the solution’s architecture well-designed and scalable?
Rubric:
5: High functionality, effective tool integration, and a robust, scalable architecture.
3: Mostly functional but lacks optimization in tool use or architecture.
1: Basic functionality with limited technical sophistication.
Innovation and Creativity (20%)
Definition: Assess the originality of the approach and features of the solution, including how it distinguishes itself from existing applications.
Key Considerations:
Novelty: Unique features or methods that improve healthcare delivery, especially using generative AI and frameworks like OpenCHA or NVIDIA Toolkit.
Creative Problem-Solving: Innovative techniques employed to navigate common healthcare challenges, showing adaptability in real-world scenarios.
Market Distinction: Scalability, user experience, or addressing underserved needs.
Rubric:
5: Highly creative, introducing groundbreaking ideas clearly distinct from existing solutions.
3: Moderately creative, with some innovative elements that add value but may not fully set it apart.
1: Minimal creativity, relying on established methods.
Impact and Value Proposition (15%)
Definition: Evaluate the solution’s anticipated real-world impact, usability, and value for patients, providers, and the healthcare system.
Key Considerations:
Positive Outcomes: How well does the solution address the healthcare need, with potential for measurable impact on patient outcomes, accessibility, or efficiency?
Usability and Scalability: Is it user-friendly and adaptable for real-world healthcare? Can it scale across different contexts or populations?
Path to Productization: Does the project have a clear pathway to becoming a marketable product or solution, with considerations for deployment, user adoption, or sustainability in healthcare settings?
Industry Alignment: How well does the solution align with current healthcare challenges and trends, and does it provide a unique or valuable contribution?
Rubric:
5: High-impact, scalable solution with clear market potential, strongly aligned with urgent healthcare needs.
3: Moderate impact with some benefits; partially scalable, needs refinement for market.
1: Minimal impact, limited usability or scalability, and weak market potential.
Privacy, Inclusion, and Ethical Considerations (15%)
Definition: Assess the solution’s attention to patient privacy, inclusivity, safety, and ethical concerns in healthcare. The goal is to encourage awareness of standards that enhance patient trust and well-being, even in an early prototype or concept phase.
Key Considerations:
Data Privacy: Basic steps taken to protect any patient data, even in a simulated setting.
Patient Safety and Risk Mitigation: Awareness of potential patient risks (e.g., incorrect diagnoses or recommendations, AI bias) and strategies to address them. Emphasis should be on risk awareness rather than comprehensive fail-safes or testing.
Inclusivity and Accessibility: Awareness of inclusivity, accessibility, and bias mitigation should be demonstrated.
Ethical AI Practices: Outline considerations around AI ethics, such as generative AI’s transparency, user control, or potential bias.
Rubric:
5: Strong awareness of privacy, safety, inclusivity, and ethics with clear risk awareness and appropriate mitigations for a prototype.
3: Addresses most privacy, safety, and ethics aspects but may lack depth in some areas.
1: Minimal attention to privacy, safety, or ethics, with potential for harm or inequitable outcomes.
Presentation and Communication Quality (10%)
Definition: Evaluate the effectiveness of the team’s presentation in communicating their solution and its value.
Key Considerations:
Clarity and Engagement: Ability to succinctly explain the problem, solution, and technological implementation.
Visuals and Demos: Quality of visual aids and demonstrations that enhance understanding
Presentation Skills: Professionalism and engagement in delivery.
Rubric:
5 - Clear, engaging, and well-structured presentation with effective visual aids.
3 - Mostly clear but may lack some engagement or structure.
1 - Poorly organized or unclear presentation, limited audience engagement.
Team Collaboration and Execution (5%) (to be evaluated by Technical POCs throughout the week)
Definition: Assess how well the team collaborates and executes their project throughout the hackathon.
Key Considerations:
Teamwork: Evidence of teamwork in coding, problem-solving, and project management.
Communication: Clear internal communication and task distribution.
Adaptability: Ability to handle/adapt to challenges that arose during the hackathon.
Rubric:
5 - High degree of collaboration, adaptability, and effective execution.
3 - Some evidence of teamwork but with minor challenges or issues.
1 - Minimal collaboration or issues that significantly hindered execution.
Additional Questions?
Please contact us at contact@healthunity.org.