The Impact and Acceptance of Large Language Models in Healthcare: A Perspective from China

Abstract

This research explores the impact of Large Language Models like GPT on the healthcare industry, focusing on operational efficiency, patient experience, and cost structures to promote greater inclusive innovation. Employing a mixed-methods approach, this study integrates quantitative data from structured surveys with qualitative insights from interviews. Grounded in empirical evidence from 66 valid surveys conducted among healthcare professionals and patients in China, this study employs SmartPLS for robust statistical analysis. The findings suggest a significant potential of LLMs in enhancing healthcare delivery, marked by improvements in operational efficiency and patient experience. While LLMs are perceived to potentially lower costs, the study reveals that cost reduction alone does not significantly influence the acceptance of LLM-integrated healthcare solutions in the Chinese context. The high level of trust and acceptance in using LLMs for diagnosis and treatment planning among respondents underscores a shift towards prioritizing quality and effectiveness in healthcare over mere cost savings. This study contributes to the discourse on AI adoption in healthcare, challenging existing assumptions and indicating a future where quality and outcome improvements may be more significant factors for technology acceptance. The research advocates for a balanced approach to LLM integration, emphasizing the importance of both economic and qualitative benefits in enhancing healthcare practices.