AI's Impact on North Carolina Healthcare

Published Date : 15-06-2025 

Artificial intelligence (AI) has been making significant strides in various industries, and healthcare is no exception. In North Carolina, healthcare systems are leveraging AI to improve patient care, from early cancer detection to virtual office assistance. However, the rapid adoption of AI in healthcare also raises important regulatory and ethical questions. 

The term “artificial intelligence” has been around since the 1950s, but it wasn’t until a few years ago that the technology became relevant to many Americans. In November 2022, OpenAI released a demo of ChatGPT and attracted over a million users within days. As of January, OpenAI was valued at more than $340 billion as AI is becoming enmeshed in everything from self-driving cars to K-12 classrooms.

North Carolina health care systems are among the first in the country to use generative AI in healthcare, and the use of this burgeoning technology will likely only grow. At Atrium Health, some doctors use the technology to spot early signs of lung cancer. At OrthoCarolina, a tool called Medical Brain works as a sort of virtual office assistant. At Duke Health, AI evaluates patient care data, according to NC Health News and The Charlotte Ledger.

However, the rapid adoption of AI in healthcare has also raised concerns among some state legislators, including those in North Carolina. They are pushing for more regulation around the technology to ensure patient safety and privacy. On this Charlotte Talks, we unpack the promise and peril around artificial intelligence in North Carolina’s medical systems.

Jordan Archer, the chief operating officer for Tryon Medical Partners, discusses how AI is being used to improve patient outcomes and streamline medical processes. Tucker Burks, from CPG Pathology (formerly Carolina Pathology Group), shares insights on the role of AI in pathology and diagnostics. Michelle Crouch, who covers healthcare for The Charlotte Ledger and North Carolina Health News, provides an overview of the regulatory landscape and the ethical considerations surrounding AI in healthcare.

The integration of AI in healthcare offers significant benefits, such as early detection of diseases, personalized treatment plans, and reduced administrative burdens. However, it also poses challenges, including data privacy, potential biases in AI algorithms, and the need for robust regulatory frameworks to ensure patient safety.

As AI continues to evolve, it is crucial for healthcare providers, policymakers, and technology developers to work together to harness its potential while addressing the associated risks. The future of healthcare in North Carolina and beyond will be shaped by how effectively we can balance innovation with regulation and ethical standards. 

Frequently Asked Questions (FAQS): 

Q: What is AI and how is it used in healthcare?

A: AI, or artificial intelligence, refers to the simulation of human intelligence in machines. In healthcare, AI is used for various applications such as early disease detection, personalized treatment plans, and administrative tasks like scheduling and data management.

Q: How is AI being used at Atrium Health?

A: At Atrium Health, AI is used to spot early signs of lung cancer. This helps in early detection and improves patient outcomes by starting treatment sooner.

Q: What is the Medical Brain tool at OrthoCarolina?

A: The Medical Brain tool at OrthoCarolina works as a virtual office assistant, helping with administrative tasks and improving the efficiency of medical practices.

Q: How is AI evaluating patient care data at Duke Health?

A: At Duke Health, AI evaluates patient care data to identify trends, optimize treatment plans, and ensure high-quality care. This helps in making data-driven decisions and improving patient outcomes.

Q: What are the regulatory concerns around AI in healthcare?

A: Some state legislators, including those in North Carolina, are pushing for more regulation around AI in healthcare to ensure patient safety and privacy. Concerns include data privacy, potential biases in AI algorithms, and the need for robust regulatory frameworks. 

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