Today, I came across an interesting research letter published in JAMA Network Open that sheds light on how healthcare professionals perceive the use of large language models, such as AI chatbots, in patient communication. The study, conducted across 9 clinics with 166 users including nurses, medical assistants, advanced practice clinicians, and physicians, revealed that nurses were more receptive to the AI chatbot compared to other healthcare professionals.
According to the findings, approximately 92 percent of nurses believed that the AI chatbot, which generated responses to patients’ portal requests, helped enhance efficiency, empathy, and tone. In contrast, other healthcare professionals expressed less favorable opinions. Nurses were also more inclined to agree that the chatbot reduced the necessity of forwarding patient messages to physicians and advanced practice clinicians. This could be attributed to the complexity of the messages forwarded to physicians and APCs, making it challenging for the chatbot to effectively process them.
The study highlighted the need for large language models to be tailored to recognize the intended recipient of the message, whether it be a medical assistant, nurse, physician, or APC, in order to generate appropriate responses. It also noted that the current utilization rate of chatbots stood at around 12 percent, indicating room for improvement in optimizing their functionality.
In another development, I had the opportunity to speak with physician Abdel Mahmoud, who leads Anterior, a health AI startup focused on streamlining administrative workflows, particularly in the realm of prior authorization. Anterior recently secured a $20 million Series A funding round led by New Enterprise Associates and offers generative AI technology to aid nurses and doctors in conducting medical reviews for health insurance approval.
Contrary to concerns about AI automating healthcare decisions, Mahmoud emphasized that Anterior’s tool does not replace human judgment but rather assists clinicians in assessing the medical necessity of treatments. The tool is designed to extract pertinent information from medical records and policy documents to facilitate informed decision-making by reviewers. Additionally, Mahmoud revealed that a significant portion of Anterior’s workforce comprises clinicians, underscoring the company’s commitment to integrating healthcare expertise into its technology.
As the healthcare landscape continues to evolve with the integration of AI, it is crucial to maintain a balance between leveraging technological advancements and preserving the human touch in patient care. The insights gleaned from these studies and interviews offer valuable perspectives on the role of AI in healthcare communication and decision-making, pointing towards a future where innovation and empathy work hand in hand to enhance patient outcomes.
