The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT
Open accessAbstract
Background: Healthcare crowdsourcing events (e.g. hackathons) facilitate interdisciplinary collaboration and encourage innovation. Peer-reviewed research has not yet considered a healthcare crowdsourcing event focusing on generative artificial intelligence (GenAI), which generates text in response to detailed prompts and has vast potential for improving the efficiency of healthcare organizations. Our event, the New York University Langone Health (NYULH) Prompt-a-thon, primarily sought to inspire and build AI fluency within our diverse NYULH community, and foster collaboration and innovation. Secondarily, we sought to analyze how participants’ experience was influenced by their prior GenAI exposure and whether they received sample prompts during the workshop. Methods: Executing the event required the assembly of an expert planning committee, who recruited diverse participants, anticipated technological challenges, and prepared the event. The event was composed of didactics and workshop sessions, which educated and allowed participants to experiment with using GenAI on real healthcare data. Participants were given novel “project cards” associated with each dataset that illuminated the tasks GenAI could perform and, for a random set of teams, sample prompts to help them achieve each task (the public repository of project cards can be found at https://github.com/smallw03/NYULH-Generative-AI-Prompt-a-thon-Project-Cards). Afterwards, participants were asked to fill out a survey with 7-point Likert-style questions. Results: Our event was successful in educating and inspiring hundreds of enthusiastic in-person and virtual participants across our organization on the responsible use of GenAI in a low-cost and technologically feasible manner. All participants responded positively, on average, to each of the survey questions (e.g., confidence in their ability to use and trust GenAI). Critically, participants reported a self-perceived increase in their likelihood of using and promoting colleagues’ use of GenAI for their daily work. No significant differences were seen in the surveys of those who received sample prompts with their project task descriptions Conclusion: The first healthcare Prompt-a-thon was an overwhelming success, with minimal technological failures, positive responses from diverse participants and staff, and evidence of post-event engagement. These findings will be integral to planning future events at our institution, and to others looking to engage their workforce in utilizing GenAI.
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Current faculty development opportunities are often offered either as one-off workshops/prompt-a-thons or as formalized multi-session programs requiring substantial institutional support and time commitment.
“Current faculty development opportunities are often offered at one of two ends: workshops [2] or “prompt-a-thons” that engage participants in brief one-off events [3] or formalized programs that weave genAI training into multi-session curricula requiring substantial institutional support and time commitment [4].”
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- Authors
- Small, W. R., Malhotra, K., Major, V. J., Wiesenfeld, B., Lewis, M., Grover, H., Tang, H., Banerjee, A., Jabbour, M. J., Aphinyanaphongs, Y., Testa, P., & Austrian, J. S.
- Affiliations
- NYU Langone Health (US)
- New York University (US)
- Microsoft (United States) (US)
- Corresponding author
- Small, William R.
- ORCID
- Venue
- PLOS Digital Health
- Publisher
- Public Library of Science (PLoS)
- Published
- 2024-07-23
- Volume
- 3
- Issue
- 7
- Pages
- e0000394
- ISSN
- 2767-3170 (ISSN-L)
- PMC
- PMC11265701
- OpenAlex
- W4400912966
- Cited by
- 17
- References
- 25
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 3
- FWCI
- 1.59
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLOS Digital Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Engineering › Biomedical Engineering › Biomedical and Engineering Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- generative AI, hackathons, employee engagement, ChatGPT, AI fluency, responsible AI use, health data, participant experiences, trust in AI
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