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An Extended Hackathon Model for Collaborative Education in Medical Innovation
Jason K Wang1, Ravinder D Pamnani2, Robson Capasso2,3
1Mathematical and Computational Science Department, Stanford University, Stanford, CA, USA.
This study introduces a novel "extended hackathon" educational model to make medical innovation training accessible. Participants showed over a twofold increase in medical innovation knowledge, highlighting the program
Area of Science:
- Biomedical Engineering Education
- Healthcare Innovation Training
- Medical Device Development
Background:
- Current medical innovation education is limited to traditional, long-term university courses and fellowships.
- This limits accessibility for a broad range of students and early-career professionals.
- There is a need for more accessible and widely adoptable training models in medical innovation.
Purpose of the Study:
- To describe the structure and preliminary outcomes of a 1-2 week "extended hackathon" course.
- To assess the accessibility and adoptability of this model for academic medical centers.
- To evaluate the impact of the extended hackathon on participants' medical innovation knowledge.
Main Methods:
- Eight extended hackathons were conducted in five international locations, involving 245 participants.
- Participants represented diverse educational backgrounds and professional expertise.
- Pre- and post-hackathon surveys assessed self-perceived knowledge in ten medical innovation categories.
Main Results:
- Participants reported a significant average increase of 114.1% in medical innovation knowledge (n=161).
- Knowledge gains were observed across all ten assessed categories.
- The extended hackathon model proved effective in enhancing foundational medical innovation skillsets.
Conclusions:
- The extended hackathon is a viable and effective educational model for medical innovation.
- This model significantly increases accessibility to foundational medical innovation training.
- Further research requires standardized assessments and larger participant samples to robustly evaluate educational value.
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