Leveraging Generative AI tools to support the development of digital solutions in healthcare research: case study (Preprint)

Abstract

Generative artificial intelligence (GenAI) has the potential to revolutionize health technology product development by improving coding quality, efficiency, documentation, quality assessment and review, and troubleshooting.

This paper explores the application of a commercially available GenAI tool (ChatGPT) to the development of a digital health behavior change intervention designed to support patient engagement in a commercial digital diabetes prevention program.

We examine the capacity, advantages, and limitations of ChatGPT to support digital product idea conceptualization, intervention content development, and the software engineering process including software requirement generation, software design, and code production. Eleven participants with fields of study ranging from medicine, implementation science and computer science and years in field of work of average 15 years, participated in the output review process (ChatGPT vs Human generated outcome). All had familiarity or prior exposure to the original PAMS intervention.

Eleven experienced evaluators rated the ChatGPT-produced outputs in terms of understandability, usability, novelty, relevance, completeness and efficiency. Results were positive for most of the metrics. We identified that ChatGPT can 1) support developers in achieving high-quality products in a shorter development time, and 2) facilitate non-technical communication and system understanding between technical and non-technical team members, with the goal of driving the development of rapid and easy-to-build computational solutions for medical technologies.

Overall, we have found that ChatGPT served as a usable facilitator for researchers engaging in the software development life cycle, from product conceptualization to feature identification, and user story development to code generation.