Empowering Clinicians as Citizen Developers: Leveraging Generative AI and Low-Code Platforms in Healthcare

Authors

  • Preeti Tupsakhare Engineer Lead - Medical Benefit Management Information Technology, Elevance Health, USA. Author

DOI:

https://doi.org/10.70589/JRTCSE.2025.13.5.1

Keywords:

Low-Code platforms, Generative AI, citizen developers, healthcare innovations

Abstract

The rising demand for scalable digital health solutions is reshaping how technology is built and delivered in healthcare. Low-code platforms have already accelerated application development, but many clinicians—those closest to patients—are left out of the design process because they lack coding expertise. Recent advances in generative AI open the door to a new possibility: turning clinicians into empowered “citizen developers” who can shape, customize, and deploy solutions with little to no technical background.

This paper explores how the convergence of generative AI and low-code platforms [1] can bridge the gap between technology and patient care. We highlight frameworks, practical use cases, and the risks involved in giving clinicians a more active role as technology creators. Alongside the promise of shorter development cycles, stronger clinician engagement, and better patient outcomes, we also address challenges such as governance, data privacy, model bias, and regulatory hurdles. To guide this transition, we propose a structured model for integrating generative AI copilots into low-code platforms—demonstrating how this shift could democratize healthcare innovation and move us closer to truly intelligent, clinician-driven solutions.

References

G. Paliwal, A. Donvir, P. Gujar and S. Panyam, "Low-Code/No-Code Meets GenAI: A New Era in Product Development," 2024 IEEE Eighth Ecuador Technical Chapters Meeting (ETCM), Cuenca, Ecuador, 2024, pp. 1-9, doi: 10.1109/ETCM63562.2024.10746160

B. Binzer and T. J. Winkler, “Democratizing software development: a systematic multivocal literature review and research agenda on citizen development,” in Lecture Notes in Business Information Processing, Springer Science and Business Media Deutschland GmbH, 2022, pp. 244–259

J. Martins, F. Branco, and H. Mamede, “Combining low-code development with ChatGPT to novel no-code approaches: a focus-group study,” Intelligent Systems with Applications, vol. 20, 2023, Art. no. 200289. doi: 10.1016/j.iswa.2023.200289

O. Bruhin, E. Dickhaut, E. Elshan, and M. Li, “Generative AI and low code development platforms: Preliminary insights from expert interviews,” in Proc. Hawaii Int. Conf. Syst. Sci. (HICSS), Waikiki, HI, USA, Jan. 3–6, 2024, pp. 10. doi: 10.2572-6862/978-0-9981331-7-1. [Online]. Available: https://www.alexandria.unisg.ch/handle/20.500.14171/118148

L. Bachina and A. Kanagala, “Health revolution: AI-powered patient engagement,” Journal of Chemical and Biochemical Sciences, vol. 24, no. 5, 2023

S. A. Alowais et al., “Revolutionizing healthcare: the role of artificial intelligence in clinical practice,” BMC Medical Education, vol. 23, no. 1, p. 689, 2023.

N. Bragazzi and S. Garbarino, “Toward clinical generative AI: Conceptual framework,” JMIR AI, vol. 3, 2024, Art. no. e55957. doi: 10.2196/55957. [Online]. Available: https://ai.jmir.org/2024/1/e55957.

Y. Chen and P. Esmaeilzadeh, “Generative AI in medical practice: In-depth exploration of privacy and security challenges,” Journal of Medical Internet Research, vol. 26, 2024, Art. no. e53008. doi: 10.2196/53008. [Online]. Available: https://www.jmir.org/2024/1/e53008

Downloads

How to Cite

Preeti Tupsakhare. (2025). Empowering Clinicians as Citizen Developers: Leveraging Generative AI and Low-Code Platforms in Healthcare. JOURNAL OF RECENT TRENDS IN COMPUTER SCIENCE AND ENGINEERING ( JRTCSE), 13(5), 1-8. https://doi.org/10.70589/JRTCSE.2025.13.5.1