OpenAI for Healthcare Aims to Streamline Clinical Workflows, Reduce Administrative Burden

As OpenAI for Healthcare, the company’s latest artificial intelligence (AI) tools roll out to leading health care organizations nationwide, experts emphasize the need for careful adoption to address ethical and bias concerns.

New OpenAI Solutions Aim to Support Clinicians, Improve Care Delivery

Last Thursday, OpenAI introduced OpenAI for Healthcare, a suite of secure AI products designed to help health care organizations deliver more high-quality care, reduce administrative burden, and power custom clinical solutions while supporting Health Insurance Portability and Accountability Act (HIPAA) compliance by protecting patient data.¹ The offerings include the OpenAI Application Programming Interface (API) and ChatGPT for Healthcare, both powered by GPT-5.2 models and developed through ongoing research and real-world evaluation to reflect how clinicians use AI in practice.

The OpenAI API platform enables developers to build tools and products using the company’s latest models and embed AI directly into health care systems and workflows; OpenAI noted that eligible consumers can apply for a Business Associate Agreement (BAA) to support HIPAA compliance requirements. In practice, teams are using OpenAI APIs to develop applications for health care team coordination, patient chart summarization, and discharge workflows.

Meanwhile, ChatGPT for Healthcare allows clinical teams to synthesize medical evidence alongside institutional guidance and apply it to specific patient contexts. The tool may also be used to draft clinical and administrative documentation and adapt patient-facing education materials for readability and translation. According to OpenAI, these capabilities can help reduce time spent on administrative tasks, promote adherence to shared standards of care, and support a better patient experience.

Responses generated by ChatGPT for Healthcare draw from millions of peer-reviewed studies, public health guidance, and clinical guidelines, with citations that include article titles, journals, and publication dates. OpenAI said this supports source verification and helps clinicians reason through cases with greater confidence, enabling patients to receive accurate diagnoses and begin treatment sooner.

ChatGPT for Healthcare can also integrate with enterprise tools, such as Microsoft SharePoint, allowing responses to incorporate an institution’s approved policies, clinical pathway, and operational guidance. Additionally, the platform supports shared templates for common tasks, like drafting discharge summaries, patient instructions, and prior authorization support; this helps teams spend less time rewriting and searching while improving care transitions and clarity for patients.

The platform also provides a centralized workspace with role-based access controls and organization-wide user management, giving health care organizations greater governance and visibility when deploying AI across clinical, research, and administrative teams. Lastly, patient data and protected health information remain under each organization’s control, with options for data residency, audit logs, customer-managed encryption keys, and a BAA with OpenAI to support HIPAA-compliant use. OpenAI emphasized that content shared with ChatGPT for Healthcare is not used to train its models.

ChatGPT for Healthcare became available last Thursday and is already being rolled out to leading health care institutions, including AdventHealth, Memorial Sloan Kettering Cancer Center, and Cedars-Sinai Medical Center.

“At AdventHealth, we’re working with OpenAI to apply AI in ways that directly benefit our consumers: reducing friction, improving access to clear and timely information, and giving our care teams more time to focus on what matters most—delivering whole-person care with compassion and consistency,” Rob Purinton, AdventHealth’s chief AI officer, said in a news release.

ChatGPT Health Helps Patients Navigate Care with Personalized Insights

The launch of ChatGPT for Healthcare came one day after the introduction of ChatGPT Health, a consumer-facing tool designed to combine health information with ChatGPT’s capabilities to help patients feel more informed, prepared, and confident when navigating their care.² OpenAI reported that more than 230 million people globally ask health- and wellness-related questions on ChatGPT each week. Building on this interest, ChatGPT Health personalizes responses using patients’ health information and context and can securely connect to medical records and wellness apps. These features can help users understand recent test results, prepare for physician visits, receive guidance on diet and exercise, and weigh insurance options based on individual health care patterns.

“[ChatGPT] Health is designed to support, not replace, medical care,” OpenAI stated in a news release. “It is not intended for diagnosis or treatment. Instead, it helps you navigate everyday questions and understand patterns over time—not just moments of illness—so you can feel more informed and prepared for important medical conversations.”

OpenAI is encouraging patients interested in ChatGPT Health to join the waitlist. The company is initially providing access to a small group of early users as it continues refining the tool, with plans to expand availability to all users on web and iOS in the coming weeks.

Balancing Innovation, Responsibility When Integrating AI in Health Care

In recent years, experts have weighed the potential benefits and drawbacks of AI integration in health care as its use has become more widespread. Jason Spangler, MD, MPH, FACPM, then-president and CEO of the Center for Innovation & Value Research, and John Nosta, president of NostaLab, explored both ends of the spectrum in a 2024 contributor article published on AJMC.com.³

The experts highlighted “exciting areas” where AI shows promise, including in evidence generation and interpretation. Traditionally, evidence is gathered through large-scale clinical trials or observational studies, which can take years and cost millions of dollars. AI, however, has the potential to streamline this process, enabling faster and more precise evidence generation.

They especially highlighted the role of large language models in enhancing data perspective and analysis. In the context of evidence generation, the researchers explained that AI can learn from each piece of information, refining its approach over time, which could revolutionize future clinical trial designs.

“Imagine trials that adapt dynamically to new data inputs—changing protocols or end points in real time based on statistically sound predictive insights from AI,” Spangler and Nosta wrote. “The implications for personalized medicine are profound, offering the possibility of truly individualized treatment plans based on a continuously evolving dataset.”

Despite these benefits, the experts emphasized that AI adoption in health care must be approached cautiously, particularly because of ethical challenges. Bias in AI algorithms is one major concern, as flawed systems can directly impact patient outcomes. They explained that using biased data or poorly designed algorithms can inadvertently reinforce existing health disparities. Because of this, Spangler and Nosta stressed that AI integration into health care systems requires thoughtful regulation, rigorous validation, and ethical oversight.

“The broader narrative of AI’s role in health care is not just about revolutionizing systems but ensuring that this revolution leads to a more equitable, transparent, and patient-focused future,” the experts concluded. “The promise is immense but realizing that promise requires a delicate balance of innovation and responsibility.”

References

1. Introducing OpenAI for Healthcare. News release. OpenAI. January 8, 2026. Accessed January 12, 2026. https://openai.com/index/openai-for-healthcare/
2. Introducing ChatGPT Health. News release. OpenAI. January 7, 2026. Accessed January 12, 2026. https://openai.com/index/introducing-chatgpt-health/
3. Spangler J, Nosta J. Contributor: the promise of AI in health care. AJMC^®. September 30, 2024. Accessed January 27, 2026. https://www.ajmc.com/view/contributor-the-promise-of-ai-in-healthcare