Nature July 15, 2024
Peixing Wan, Zigeng Huang, Wenjun Tang, Yulan Nie, Dajun Pei, Shaofen Deng, Jing Chen, Yizhi Zhou, Hongru Duan, Qingyu Chen & Erping Long

Abstract

Reception is an essential process for patients seeking medical care and a critical component influencing the healthcare experience. However, current communication systems rely mainly on human efforts, which are both labor and knowledge intensive. A promising alternative is to leverage the capabilities of large language models (LLMs) to assist the communication in medical center reception sites. Here we curated a unique dataset comprising 35,418 cases of real-world conversation audio corpus between outpatients and receptionist nurses from 10 reception sites across two medical centers, to develop a site-specific prompt engineering chatbot (SSPEC). The SSPEC efficiently resolved patient queries, with a higher proportion of queries addressed in...

Today's Sponsors

LEK
ZeOmega

Today's Sponsor

LEK

 
Topics: AI (Artificial Intelligence), Nursing, Provider, Technology
Majority of physicians express concern over lack of training for NPs: Poll
One healthcare job poised for the greatest shortage
Cracking the code: Deploying an AI-enabled nursing workforce
Healthcare Leaders: 4 Lessons CEOs Can Learn From Nurses
Infographic: 4 Qualities of a Career-Ready Nurse

Share This Article