An increasing number of patients share their medical experience on social media, which are valuable resources for improving medical services and patient experience. This study focused on several top-tier large general Grade-A tertiary hospitals in China. It collected and organized patients’ medical experience reviews about these hospitals from a renowned domestic online review platform. Using the text-analysis software ROST CM 6.0 combined with Python programming, this research performed data collection, high-frequency word analysis, semantic network analysis, sentiment analysis and trend analysis on the online review corpus. Results showed that patients paid the most attention to medical staff’s service attitude and medical convenience. Their focus on medical service quality diverged around these two aspects. Patients’ sentiments toward medical services were roughly split between positive and negative: positive emotions centered on appointments and facilities, while negative ones focused on process order and doctor-patient communication. Patients’ concerns and sentiments showed certain temporal patterns. Reviews concentrated on non-technical factors like attitude, process and waiting time, with low attention to technical factors, highlighting the impact of non-technical factors on medical experience. Top large medical institutions should emphasize improving service attitude, communication, convenient processes and medical experience while focusing on professional technology. This study further validates that analyzing patients’ online reviews is a feasible approach for researching medical services.
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Liu et al. (2026) studied this question.
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