远程医疗
医疗保健
情感(语言学)
工作(物理)
服务(商务)
钥匙(锁)
计算机科学
语言模型
远程医疗
知识管理
服务提供商
医疗保健服务
数字健康
服务模式
卫生服务
业务
医学教育
医疗保健系统
护理部
互联网
梅德林
作者
Bin Zhang,Haijing Hao,Yongcheng Zhan,Jiang Wu
标识
DOI:10.1287/isre.2024.1183
摘要
This study introduces an efficient specialized artificial intelligence (AI) tool and the SEPTE model—a comprehensive framework for evaluating healthcare service quality—to help healthcare platforms and hospitals better understand what drives patient demand for online consultations. By analyzing physician reviews from one of China’s largest telehealth platforms, our small language model (Doc-BERT) uses the SEPTE framework to accurately identify key aspects of service quality, such as medical effectiveness and empathy, that matter most to patients. Unlike traditional large language models, our approach is cost-effective and can be readily implemented in real-world healthcare settings. We find that higher service-quality scores, especially in effectiveness and patient-centeredness, lead to greater patient demand for online consultations. These insights offer actionable guidance for healthcare providers and administrators seeking to improve patient experiences, optimize physician performance, and inform platform design and policy. Our work demonstrates that targeted, domain-specific AI—guided by the SEPTE model—can deliver both efficiency and impact for digital health services.
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