How Physician Reviews Affect Online Consultation Demand: An Innovative Small Language Model with Fine-Tuning

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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Publication Details

Journal
Information Systems Research
Published
2026-05-08
DOI
https://doi.org/10.1287/isre.2024.1183
Primary Topic
Health Literacy and Information Accessibility
Type
article
Field-Weighted Citation Impact
0.00
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article

How Physician Reviews Affect Online Consultation Demand: An Innovative Small Language Model with Fine-Tuning

Yongcheng Zhan, Haijing Hao, Jiang Wu, Bin Zhang
Information Systems Research
Health Literacy and Information Accessibility
article

How Physician Reviews Affect Online Consultation Demand: An Innovative Small Language Model with Fine-Tuning

Yongcheng Zhan, Haijing Hao, Jiang Wu, Bin Zhang
article en

Abstract

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.

Information Systems Research
Bentley University (US), California Polytechnic State University (US), Wuhan University (CN), Texas A&M University (US)
Openalex Percentile: Top 4%
Health Literacy and Information Accessibility
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