ADVANCING ACCESSIBILITY WITH AUTOMATION: AI FOR INCLUSIVE HEALTHCARE ACROSS AGING AND DIVERSE GROUPS

Authors

  • Ashim Gautam Upadhaya Graduate Student, College of Graduate and Professional Studies, Trine University, Indiana, United States. Author
  • Datta Snehith Dupakuntla Naga Senior Software Engineer - QA Automation, Teladoc Health, North Carolina, United States. Author

DOI:

https://doi.org/10.34218/IJCET_16_02_019

Keywords:

Artificial Intelligence In Healthcare, Healthcare Accessibility, Digital Health Equity, AI-Driven Web Accessibility, Natural Language Processing, Voice-Activated Interfaces, Algorithmic Fairness, Ethical AI In Healthcare, Automation In Healthcare, Accessibility With Automation, Web Automation, Automated Fairness Testing, Synthetic Data Testing, CI/CD Integration

Abstract

Increasing digitalization of healthcare in the United States provides opportunities and challenges for the burgeoning older adult population, who most often experience significant barriers in accessing and utilizing online health information and services due to physical and cognitive changes related to age, along with some socioeconomic factors and even instances of ageism. The importance of artificial intelligence (AI) can have in transforming web accessibility for bridging this digital divide to ensure more equitable healthcare across society. After reviewing the specific challenges faced by this population, several AI-driven solutions are outlined: custom interfaces, natural language processing for content simplification, and voice-activated navigation. Also highlighted are important legal and ethical issues that should be considered concerning healthcare AI, such as algorithmic fairness, transparency, and patient autonomy respecting privacy. Case studies and possible future uses of AI in making healthcare easy to get show how important this study is around the country in making a better and working healthcare system for older people, including automation to flag any deviations in expected outcomes.

 

References

Padmanabhan, P., & Jiao, Y. (2025). Perspectives on and Acceptability of Artificial Intelligence-Led Health Technologies Among Older Adults: A Qualitative Study. JMIR Aging, 8(1), e66778. https://doi.org/10.2196/66778

Ho, A. (2020). Are we ready for artificial intelligence health monitoring in elder care? BMC Geriatrics, 20(1), 358. https://doi.org/10.1186/s12877-020-01755-7

Lee, C. H., Wang, C., Fan, X., Li, F., & Chen, C. H. (2023). Artificial intelligence-enabled digital transformation in elderly healthcare field: scoping review. Advanced Engineering Informatics, 55, 101874. https://doi.org/10.1016/j.aei.2023.101874

Czaja, S. J., & Ceruso, M. (2022). The promise of artificial intelligence in supporting an aging population. Journal of Cognitive Engineering and Decision Making, 16(4), 182-193. https://doi.org/10.1177/15553434221100498

Chu, C. H., Nyrup, R., Leslie, K., Nabavi, N., Boneh, N., & Chen, F. K. (2022). Digital ageism: challenges and opportunities in artificial intelligence for older adults. The Gerontologist, 62(7), 947-955. https://doi.org/10.1093/geront/gnac044

Fritsch, S. J., Blankenheim, A., Wahl, A., Esser, A., Mahler, C., & Harendza, S. (2022). Attitudes and perception of artificial intelligence in healthcare: a cross-sectional survey among patients. Digital Health, 8, 20552076221116772. https://doi.org/10.1177/20552076221116772

Nadarzynski, T., Miles, O., Cowie, A., & Ridge, D. (2019). Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: a mixed-methods study. Digital Health, 5, 2055207619871808. https://doi.org/10.1177/2055207619871808

Shinners, L., Aggar, C., Grace, S., & Smith, S. (2020). Exploring healthcare professionals’ understanding and experiences of artificial intelligence technology use in the delivery of healthcare: an integrative review. Health Informatics Journal, 26(2), 1225-1236. https://doi.org/10.1177/1460458219888308

Shandilya, E., & Fan, M. (2022). Understanding older adults’ perceptions and challenges in using AI-enabled everyday technologies. In Chinese CHI 2022: The Tenth International Symposium of Chinese CHI (pp. 105-116). https://doi.org/10.1145/3564059.3564071

Wong, A. K. C., Wong, F. K. Y., Chow, K. K. S., Wong, S. M., Bayuo, J., & Ho, A. K. Y. (2022). Effect of a mobile health application with nurse support on quality of life among community-dwelling older adults in Hong Kong: a randomized clinical trial. JAMA Network Open, 5(11), e2241137. https://doi.org/10.1001/jamanetworkopen.2022.41137

Downloads

Published

2025-04-18

How to Cite

Ashim Gautam Upadhaya, & Datta Snehith Dupakuntla Naga. (2025). ADVANCING ACCESSIBILITY WITH AUTOMATION: AI FOR INCLUSIVE HEALTHCARE ACROSS AGING AND DIVERSE GROUPS. INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY, 16(2), 265-279. https://doi.org/10.34218/IJCET_16_02_019