The digital healthcare transformation in the United States creates new ways for patients to access medical services. AI-based chatbots function as useful communication platforms that perform triage duties and support patients with chronic diseases to enhance their healthcare experience. The research investigates how these systems affect healthcare accessibility, service delivery quality, and cybersecurity protection throughout the national digital health system. The research combines peer-reviewed studies with federal policy frameworks to analyze AHRQ (2023), HHS (2023), and other U.S. cybersecurity programs. The research demonstrates that AI chatbots enhance healthcare accessibility for remote areas and decrease administrative tasks, yet their rapid expansion creates security risks for patient information and ethical management challenges. The AI-Health-Equity and Cybersecurity Integration Model (AI-HECIM) demonstrates how secure system design, combined with policy coordination and inclusive system development, can build digital healthcare trust. AI-powered chatbots under proper management will establish a healthcare system that connects patients better while providing equal access and enhanced system stability in the United States.
References
[1]
Agency for Healthcare Research and Quality (AHRQ) (2023) National Healthcare Quality and Disparities Report. U.S. Department of Health and Human Services. https://www.ahrq.gov/research/findings/nhqrdr/index.html
[2]
Akter, J., Nilima, S.I., Hasan, R., Tiwari, A., Ullah, M.W. and Kamruzzaman, M. (2024) Artificial Intelligence on the Agro-Industry in the United States of America. AIMS Agriculture and Food, 9, 959-979. https://doi.org/10.3934/agrfood.2024052
[3]
Razzak, M.I., Imran, M. and Xu, G. (2019) Big Data Analytics for Preventive Medicine. Neural Computing and Applications, 32, 4417-4451. https://doi.org/10.1007/s00521-019-04095-y
[4]
U.S. Department of Health and Human Services (HHS) (2023) Health IT and Underserved Populations. https://www.healthit.gov/
[5]
U.S. Agency for International Development (USAID) (2020) Digital Strategy 2020-2024.
[6]
Hasan, R., Chy, M.A.R., Johora, F.T., Ullah, M.W. and Saju, M.A.B. (2024) Driving Growth: The Integral Role of Small Businesses in the U.S. Economic Landscape. American Journal of Industrial and Business Management, 14, 852-868. https://doi.org/10.4236/ajibm.2024.146043
[7]
Bhuiyan, M.R.I., Ullah, M.W., Ahmed, S., Bhuyan, M.K., Sultana, T. and Amin, A. (2024) Information Security for an Information Society for Accessing Secured Information: A PRISMA Based Systematic Review. International Journal of Religion, 5, 932-946. https://doi.org/10.61707/frfnr583
[8]
Akter, J., Kamruzzaman, M., Hasan, R., Khatoon, R., Farabi, S.F. and Ullah, M.W. (2024) Artificial Intelligence in American Agriculture: A Comprehensive Review of Spatial Analysis and Precision Farming for Sustainability. 2024 IEEE International Conference on Computing, Applications and Systems (COMPAS), Bangladesh, 25-26 September 2024, 1-6. https://doi.org/10.1109/compas60761.2024.10796075
[9]
Schachner, T., Keller, R. and v Wangenheim, F. (2020) Artificial Intelligence-Based Conversational Agents for Chronic Conditions: Systematic Literature Review. Journal of Medical Internet Research, 22, e20701. https://doi.org/10.2196/20701
[10]
van der Schyff, E.L., Ridout, B., Amon, K.L., Forsyth, R. and Campbell, A.J. (2023) Providing Self-Led Mental Health Support through an Artificial Intelligence-Powered Chat Bot (Leora) to Meet the Demand of Mental Health Care. Journal of Medical Internet Research, 25, e46448. https://doi.org/10.2196/46448
[11]
Abdelwanis, M., Simsekler, M.C.E., Gabor, A.F., Sleptchenko, A. and Omar, M. (2026) Artificial Intelligence Adoption Challenges from Healthcare Providers’ Perspectives: A Comprehensive Review and Future Directions. Safety Science, 193, Article ID: 107028. https://doi.org/10.1016/j.ssci.2025.107028
[12]
Kurniawan, M.H., Handayani, P.W. and Azzahro, F. (2024) A Systematic Review of Artificial Intelligence-Powered Chatbots for Chronic Disease Self-Management. Annals of Medicine, 56, Article ID: 2302980.
[13]
Clark, M. and Bailey, S. (2024) Chatbots in Health Care: Connecting Patients to Information. Canadian Journal of Health Technologies, 4, 1-22. https://doi.org/10.51731/cjht.2024.818
[14]
Parmar, P., Ryu, J., Pandya, S., Sedoc, J. and Agarwal, S. (2022) Health-Focused Conversational Agents in Person-Centered Care: A Review of Apps. NPJ Digital Medicine, 5, Article No. 21. https://doi.org/10.1038/s41746-022-00560-6
[15]
Gajarawala, S.N. and Pelkowski, J.N. (2021) Telehealth Benefits and Barriers. The Journal for Nurse Practitioners, 17, 218-221. https://doi.org/10.1016/j.nurpra.2020.09.013
[16]
Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J. and Hughes, G. (2023) A Sociotechnical Lens on Scaling Digital Health. Milbank Quarterly, 101, 1012-1050.
[17]
Lin, X., Martinengo, L., Jabir, A.I., Ho, A.H.Y., Car, J., Atun, R., et al. (2023) Scope, Characteristics, Behavior Change Techniques, and Quality of Conversational Agents for Mental Health and Well-Being: Systematic Assessment of Apps. Journal of Medical Internet Research, 25, e45984. https://doi.org/10.2196/45984
[18]
Caruana, A., Bandara, M., Musial, K., Catchpoole, D. and Kennedy, P.J. (2023) Machine Learning for Administrative Health Records: A Systematic Review of Techniques and Applications. Artificial Intelligence in Medicine, 144, Article ID: 102642. https://doi.org/10.1016/j.artmed.2023.102642
[19]
Zhang, J., Linde, L., Puma, D., Millones, A.K., Tintaya, K., Jimenez, J., et al. (2025) Adaptive Bandit Algorithms Increase Efficiency of Mobile Tuberculosis Screening Programs. Scientific Reports, 16, Article No. 1497. https://doi.org/10.1038/s41598-025-31829-x
[20]
Aggarwal, M., Khullar, V., Rani, S., Prola, T.A., Bhattacharjee, S.B., Shawon, S.M., et al. (2024) Federated Learning on Internet of Things: Extensive and Systematic Review. Computers, Materials & Continua, 79, 1795-1834. https://doi.org/10.32604/cmc.2024.049846
[21]
Khoong, E.C., Casillas, A., Gutierrez, G., Lyles, C.R., Pandita, D., Richardson, S., et al. (2025) Centering Health Equity in an Increasingly Digital Environment. Perspectives in Biology and Medicine, 68, 351-369. https://doi.org/10.1353/pbm.2025.a962029
[22]
National Institute of Standards and Technology (NIST) (2025) Special Publication 800-61 Revision 3: Computer Security Incident Handling Guide. U.S. Department of Commerce. https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-61r3.pdf
[23]
The White House (2023) National Cybersecurity Strategy. https://bidenwhitehouse.archives.gov/wp-content/uploads/2023/03/National-Cybersecurity-Strategy-2023.pdf
[24]
Cybersecurity and Infrastructure Security Agency (CISA) (2024) Behavioral Cyber-security Framework. U.S. Department of Homeland Security.
[25]
Al Mahmud, M.A., Hossain, M.A., Saju, M.A.B., Ullah, M.W., Hasan, R. and Suzer, G. (2024) Information Technology for the Next Future World: Adoption of IT for Social and Economic Growth: Part II. International Journal of Innovative Research in Technology, 10, 2349-6002. https://ijirt.org/publishedpaper/IJIRT164330_PAPER.pdf
[26]
Ullah, M.W., Rahman, R., Nilima, S.I., Tasnim, A.F. and Aziz, M.B. (2024) Health Behaviors and Outcomes of Mobile Health Apps and Patient Engagement in the USA. Journal of Computer and Communications, 12, 78-93. https://doi.org/10.4236/jcc.2024.1210007
[27]
Obermeyer, Z., Powers, B., Vogeli, C. and Mullainathan, S. (2019) Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations. Science, 366, 447-453. https://doi.org/10.1126/science.aax2342
[28]
UNESCO (2023) Recommendation on the Ethics of Artificial Intelligence. https://unesdoc.unesco.org/ark:/48223/pf0000381137
[29]
HIMSS Foundation (2024) Digital Health Equity Framework. https://www.himss.org/resources/measuring-digital-health-equity-impact/
[30]
Amann, J., Blasimme, A., Vayena, E., Frey, D. and Madai, V.I. (2020) Explainability for Artificial Intelligence in Healthcare: A Multidisciplinary Perspective. BMC Medical Informatics and Decision Making, 20, Article No. 310. https://doi.org/10.1186/s12911-020-01332-6
[31]
Khalid, N., Qayyum, A., Bilal, M., Al-Fuqaha, A. and Qadir, J. (2023) Privacy-Preserving Artificial Intelligence in Healthcare: Techniques and Applications. Computers in Biology and Medicine, 158, Article ID: 106848. https://doi.org/10.1016/j.compbiomed.2023.106848
[32]
Bodas, H. (2024) Optimizing Healthcare with AI Chatbots: Addressing Challenges and Opportunities. SSRN Working Paper No. 5148492, Social Science Research Network. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5148492
[33]
Ng, J.Y., Maduranayagam, S.G., Suthakar, N., Li, A., Lokker, C., Iorio, A., et al. (2025) Attitudes and Perceptions of Medical Researchers towards the Use of Artificial Intelligence Chatbots in the Scientific Process: An International Cross-Sectional Survey. The Lancet Digital Health, 7, e94-e102. https://doi.org/10.1016/s2589-7500(24)00202-4
[34]
Wu, P.F., Summers, C., Panesar, A., Kaura, A. and Zhang, L. (2024) AI Hesitancy and Acceptability—Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study. JMIR Human Factors, 11, e51086. https://doi.org/10.2196/51086
[35]
World Health Organization (WHO) (2023) Ethics and Governance of Artificial Intelligence for Health.
[36]
Ullah, M.W., Alam, M.T., Sultana, T., Rahman, M.M., Faraji, M.R. and Ahmed, M.F. (2024) A Systematic Review on Information Security Policies in the USA Banking System and Global Banking: Risks, Rewards, and Future Trends. Edelweiss Applied Science and Technology, 8, 8437-8453. https://doi.org/10.55214/25768484.v8i6.3816
[37]
Hasan, R., Farjana Farabi, S., Tuz Johora, F., Ullah, W., Al Mahmud, A. and Hossain, A. (2025) Evaluating and Analyzing the Innovative Branding and Marketing Strategies of International Brand: A Study of Kellogg’s Pringles. Westcliff International Journal of Applied Research, 9, 30-42. https://doi.org/10.47670/wuwijar20251rsfwaa
[38]
Roy, S., Lartey, S.T., Durneva, P., Jha, N., Ofori, M.A., Zeba, Z., et al. (2025) Digital Health Technology Infrastructure Challenges to Support Health Equity in the United States: Scoping Review. Journal of Medical Internet Research, 27, e70856. https://doi.org/10.2196/70856
[39]
Chang, E., Penfold, R.B. and Berkman, N.D. (2024) Patient Characteristics and Telemedicine Use in the US, 2022. JAMA Network Open, 7, e243354. https://doi.org/10.1001/jamanetworkopen.2024.3354
[40]
Rony, M.K.K., Deb, T.R., Khatun, M.T., Nesa, L., Begum, J., Afrin, M., et al. (2025) Attitudes of Older Patients toward Artificial Intelligence in Decision-Making in Healthcare. Journal of Medicine, Surgery, and Public Health, 6, Article ID: 100193. https://doi.org/10.1016/j.glmedi.2025.100193
[41]
Mehta, N. and Gupta, A. (2023) Adoption of AI Technologies in U.S. Hospitals. Health Policy and Technology, 12, Article ID: 100742.
[42]
Hindelang, M., Sitaru, S. and Zink, A. (2024) Transforming Health Care through Chatbots for Medical History-Taking and Future Directions: Comprehensive Systematic Review. JMIR Medical Informatics, 12, e56628. https://doi.org/10.2196/56628
[43]
American Hospital Association (AHA) (2023) The Importance of Cybersecurity in Protecting Patient Safety.
[44]
Longoni, C., Bonezzi, A. and Morewedge, C.K. (2019) Resistance to Medical Artificial Intelligence. Journal of Consumer Research, 46, 629-650. https://doi.org/10.1093/jcr/ucz013
[45]
Kühne, S., Jacobsen, J., Legewie, N. and Dollmann, J. (2025) Attitudes toward AI Usage in Patient Health Care: Evidence from a Population Survey Vignette Experiment. Journal of Medical Internet Research, 27, e70179. https://doi.org/10.2196/70179
[46]
Wakeman, M., Buckman, D.W. and El-Toukhy, S. (2025) Disparities in Digital Health Care Use in 2022. JAMA Network Open, 8, e255359. https://doi.org/10.1001/jamanetworkopen.2025.5359
[47]
Foresman, G., Biro, J., Tran, A., MacRae, K., Kazi, S., Schubel, L., et al. (2025) Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation. Journal of Participatory Medicine, 17, e69564. https://doi.org/10.2196/69564
[48]
Rangachari, P., Al Arkoubi, K. and Shindi, R. (2025) A Multi-Level Framework for Advancing Digital Health Equity in Learning Health Systems: Aligning Practice and Theory with the Quintuple Aim. International Journal for Equity in Health, 24, Article No. 253. https://doi.org/10.1186/s12939-025-02663-4
[49]
Christensen, H. and Mackinnon, A. (2006) The Law of Attrition Revisited. Journal of Medical Internet Research, 8, e20. https://doi.org/10.2196/jmir.8.3.e20
[50]
Feng, Y., Hang, Y., Wu, W., Song, X., Xiao, X., Dong, F., et al. (2025) Effectiveness of AI-Driven Conversational Agents in Improving Mental Health among Young People: Systematic Review and Meta-Analysis. Journal of Medical Internet Research, 27, e69639. https://doi.org/10.2196/69639
[51]
HIMSS (2025) Digital Health Transformation: Gains, Gaps, and the Growth of AI. Healthcare Information and Management Systems Society. https://www.himss.org/resources/digital-health-transformation-gains-gaps-and-the-growth-of-ai/
[52]
Barreda, M., Cantarero-Prieto, D., Coca, D., Delgado, A., Lanza-León, P., Lera, J., et al. (2025) Transforming Healthcare with Chatbots: Uses and Applications—A Scoping Review. Digital Health, 11, 20552076251319174. https://doi.org/10.1177/20552076251319174
[53]
Moore, A.A., Ellis, J.R., Dellavalle, N., Akerson, M., Andazola, M., Campbell, E.G., et al. (2025) Patient-Facing Chatbots: Enhancing Healthcare Accessibility While Navigating Digital Literacy Challenges and Isolation Risks—A Mixed-Methods Study. Digital Health, 11, 20552076251337321. https://doi.org/10.1177/20552076251337321
[54]
Shaver, J. (2022) The State of Telehealth before and after the COVID-19 Pandemic. Primary Care: Clinics in Office Practice, 49, 517-530. https://doi.org/10.1016/j.pop.2022.04.002
[55]
Di Palma, G., Scendoni, R., Ferorelli, D., De Benedictis, A., Tambone, V. and De Micco, F. (2025) AI-Induced Cybersecurity Risks in Healthcare: A Narrative Review of Blockchain-Based Solutions within a Clinical Risk Management Framework. Risk Management and Healthcare Policy, 18, 3479-3497. https://doi.org/10.2147/rmhp.s544523
