Is ChatGPT Health Care’s Next Big Thing?
Artificial intelligence has many applications in health care, but hurdles to widespread adoption remain.
In November 2022 the world was introduced to ChatGPT, an artificial intelligence (AI)–powered chatbot capable of mirroring intuitive human conversation. Since then, this technology has captured the attention of millions, who have used it to write everything from songs and poetry to essays and Python code.
In health care, ChatGPT is a major topic of conversation among providers and patients alike. But as with other AI systems, ChatGPT has challenges and needs to undergo further testing before achieving widespread use in health care.
What Is ChatGPT?
ChatGPT is the latest evolution of a language model developed by OpenAI known as GPT-3,1 trained on extensive amounts of data to learn language patterns. The process is designed to ensure accuracy when predicting what comes next in a sequence of words. ChatGPT is taught and refined using a combination of supervised and reinforcement learning, an approach that instructs computers on how to learn or identify topics.
ChatGPT is optimized through reinforcement learning from human feedback. Here, human experts teach the machine likely and ethical responses, or decisions to support users. Open AI describes ChatGPT’s dialogue features as being able to “answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.”2
Potential Uses of ChatGPT
ChatGPT amassed 1 million users within its first week.2 Among these users are health care professionals leaning into AI as the near future of health care management. ChatGPT is ushering in a new phase of health care assistance in the following ways:
Summarizing patient records. By wielding the powers of AI and machine learning, ChatGPT may be able to act as a digital assistant to providers, extracting essential information from patient records, grouping relevant data, and more. With this information readily available, providers can assess patients more quickly.
Enhancing clinical decision support systems. These systems have long played an important role in recommendations for patient care. Enhancing these systems using AI and machine learning may improve patient outcomes and treatment decisions.
“In my view, patient interactions and care should be offered inherently through chat first, virtual care second, and in-person care third,” said Ali Parsa, MD, founder and CEO of Babylon, a global AI and digital health platform. “Moving to conversational systems powered through AI models such as GPT-3 (and others), which are contextualized with patient information, will provide more personalized and clinically accurate answers for patients.”
Automating administrative functions. Data from studies3 have shown that health care providers and their staff spend approximately 16.4 hours per week navigating insurance approvals for patient medication, procedures, and other medical services. Focusing on administrative duties means less time for providing medical care. But using suitable prompts, ChatGPT can be trained to draft letters seeking prior authorizations, appeals of insurance denials, and other claims, Parsa noted.
Improving patient education. Using the algorithm’s simplified syntax, providers may use ChatGPT to keep patients informed throughout treatment. Clinical notes are typically written in professional language, making them difficult for patients to understand. ChatGPT may one day learn to simplify medical notes, prescription information, or even suggested lifestyle modifications for better patient comprehension.
Providing answers to FAQs. Health care is fast paced, and it can be difficult to find the time to answer patient questions. ChatGPT can support providers by filling the gaps in care information and answering questions about diagnosing or managing conditions.
Challenges to ChatGPT Adoption
However, there are challenges preventing the widespread adoption of ChatGPT in health care settings. For example, the information used to train the algorithm only goes through 2021, limiting its usefulness. Users also need help with determining the accuracy of answers, as ChatGPT has been known to make up references or provide incorrect information without caveats for potential error.
“The challenge of mass adoption of ChatGPT is the same challenge of revolutionizing health care in the United States in general; it’s a complicated system that takes time to change,” Parsa said. “The building blocks are in place, and it will be up to the innovators to unlock the value on a day-to-day basis, by leveraging technologies such as ChatGPT that can be personalized to health care.”
A version of this article originally appeared on Medical Economics.
References
- Lutkevich B, Schmelzer R. GPT-3. TechTarget. Accessed February 8, 2023. https://www.techtarget.com/searchenterpriseai/definition/GPT-3
- What is machine learning? IBM. Accessed February 8, 2023. https://www.ibm.com/topics/machine-learning
- Mollman S. ChatGPT gained 1 million users in under a week. Here’s why the AI chatbot is primed to disrupt search as we know it. Yahoo! Finance. December 9, 2022. Accessed February 8, 2023. https://finance.yahoo.com/news/chatgpt-gained-1-million-followers-224523258.html
- Corder JC. Streamlining the insurance prior authorization debacle. Mo Med. 2018;115(4):312-314.
