AI Chatbots and Challenges of HIPAA Compliance for AI Developers and Vendors
Open accessAbstract
Developers and vendors of large language models ("LLMs") - such as ChatGPT, Google Bard, and Microsoft's Bing at the forefront-can be subject to Health Insurance Portability and Accountability Act of 1996 ("HIPAA") when they process protected health information ("PHI") on behalf of the HIPAA covered entities. In doing so, they become business associates or subcontractors of a business associate under HIPAA.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
LLMs lower the barrier to quantitative work by translating plain-language requests into statistical code or running analyses directly.
“Beyond search, LLMs lower the barrier to quantitative work by translating plain-language requests into statistical code or running analyses directly [67].”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [67]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Sequence to Sequence Learning with Neural Networks
Sutskever, I., Vinyals, O., & Le, Q. V. (2014) · arXiv · doi:10.48550/arxiv.1409.3215 · Cited by 17,766 · see citing works
Privacy in the age of medical big data
Price, W. N., & Cohen, I. G. (2019) · Nature Medicine · doi:10.1038/s41591-018-0272-7 · Cited by 1,522 · see citing works
Artificial Intelligence Risk Management Framework (AI RMF 1.0)
Tabassi, E. (2023) · doi:10.6028/nist.ai.100-1 · Cited by 1,136 · see citing works
AI-Generated Medical Advice—GPT and Beyond
Haupt, C. E., & Marks, M. (2023) · JAMA · doi:10.1001/jama.2023.5321 · Cited by 346 · see citing works
HIPAA and protecting health information in the 21st century
Cohen, I. G., & Mello, M. M. (2018) · JAMA · doi:10.1001/jama.2018.5630 · Cited by 273 · see citing works
The Challenges for Regulating Medical Use of ChatGPT and Other Large Language Models
Minssen, T., Vayena, E., & Cohen, I. G. (2023) · JAMA · doi:10.1001/jama.2023.9651 · Cited by 171 · see citing works
Generative AI in Health Care and Liability Risks for Physicians and Safety Concerns for Patients
Duffourc, M., & Gerke, S. (2023) · JAMA · doi:10.1001/jama.2023.9630 · Cited by 132 · see citing works
Privacy aspects of direct-to-consumer artificial intelligence/machine learning health apps
Gerke, S., & Rezaeikhonakdar, D. (2022) · Intelligence-Based Medicine · doi:10.1016/j.ibmed.2022.100061 · Cited by 27 · see citing works
Self-citationDiscrimination By Artificial Intelligence In A Commercial Electronic Health Record—A Case Study
(2020) · Forefront Group · doi:10.1377/forefront.20200128.626576 · Cited by 17 · see citing works
Becker, J., Gerke, S., & Cohen, I. G. (2023) · Collaborative bioethics · doi:10.1007/978-3-031-29451-8_24 · Cited by 6 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- [1]S. Gerke, “ Nutrition Facts Labels’ for Artificial Intelligence/Machine Learning-Based Medical Devices — The Urgent Need for Labeling Standards,” The George Washington Law Review 91, no. 1 (2023): 79– 163.
- [18]P. Zikopoulos, D. deRoos D, K. Parasuraman, T. Deutsch, D. Corrigan, and J. Giles, Harness the Power of Big Data: the IBM Big Data Platform (New York: McGraw-Hill, 2013).
Cited by
Sorted by citations
The role of agentic AI in shaping a smart future: A systematic review
Hosseini, S., & Seilani, H. (2025) · Array · doi:10.1016/j.array.2025.100399 · Cited by 280 · see citing works
Chatbots in cancer applications, advantages and disadvantages: all that glitters is not gold
Goumas, G., Dardavesis, T. I., Syrigos, K., Syrigos, N., & Simou, E. (2024) · Journal of Personalized Medicine · doi:10.3390/jpm14080877 · Cited by 24 · see citing works
“Particularly in the field of healthcare, to be able to identify specific patterns in big data, developers and suppliers of AI/machine learning-driven medical products need a significant amount, speed, variety, and veracity of medical data [76].”
BackgroundLeon, M., Ruaengsri, C., Pelletier, G., Bethencourt, D., Shibata, M., Flores, M. Q., & Shudo, Y. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13216543 · Cited by 12 · see citing works
Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery
Kuno, M., Osumi, H., Udagawa, S., Yoshikawa, K., Ooki, A., Shinozaki, E., Ishikawa, T., Oba, J., Yamaguchi, K., & Sakurada, K. (2025) · Current Oncology · doi:10.3390/curroncol32110588 · Cited by 7 · see citing works
- Authors
- Rezaeikhonakdar, D.
- Affiliations
- Pennsylvania State University (US)
- Corresponding author
- Rezaeikhonakdar, Delaram
- Venue
- Journal of Law, Medicine & Ethics
- Publisher
- Cambridge University Press (CUP)
- Published
- 2023
- Volume
- 51
- Issue
- 4
- Pages
- 988-995
- ISSN
- 1073-1105 (ISSN-L)
- 1748-720X
- PMC
- PMC10937180
- OpenAlex
- W4392776387
- Cited by
- 67
- References
- 11
- Citations by year
- 2026: 25 · 2025: 27 · 2024: 14 · 2022: 1
- FWCI
- 15.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- The Journal of Law Medicine & Ethics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Thoreau and American Literature
- Social Sciences › Law › Digitalization, Law, and Regulation
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- HIPAA compliance, large language models, AI chatbots, business associates, subcontractors, protected health information, health data privacy, covered entities, ChatGPT, Google Bard, Microsoft Bing
- MeSH terms
- Commerce, Humans, United States, Guideline Adherence, Health Insurance Portability and Accountability Act
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
