Developing a Framework for Online Review-Based Health Care Service Quality Assessment: Text-Mining Study

Area of Science:

• Health Services Research
• Digital Health
• Text Mining

Background:

• Online patient reviews are crucial for assessing medical service quality.
• Critical quality dimensions within textual reviews are underexplored.

Purpose of the Study:

• To develop a comprehensive medical service quality assessment framework using online review data.
• To enable efficient quality assessment for numerous doctors on large platforms.

Main Methods:

• Utilized a text-mining approach with theory-driven topic extraction from online reviews.
• Developed a framework based on topic and sentiment classification.
• Conducted empirical analysis to validate the framework by examining sentiment effects on patient demand.

Main Results:

• Established a 5-dimensional healthcare service quality framework (HSQ-5D model).
• Identified key dimensions: expertise, service delivery process, attitude, empathy, and outcome.
• Demonstrated that these dimensions significantly affect patient demand, explaining 85.52% of variance.

Conclusions:

• The HSQ-5D model is valid and practically valuable for assessing healthcare service quality.
• Integrates text-mining with service quality frameworks for digital health contexts.
• Aims to reduce information asymmetry, strengthen patient-provider relationships, and promote patient-centered care.