Developing Attributes and Levels for a Discrete Choice Experiment on Internet Hospital Service Preferences Among Chinese Patients with Chronic Diseases: A Mixed-Methods Study.

BACKGROUND

Internet hospitals are increasingly used to support chronic disease care in China. Although previous research has examined online healthcare preferences, evidence on the systematic development of context-specific attributes and levels for Chinese patients with chronic diseases remains limited.

OBJECTIVE

This study aimed to develop candidate attributes and levels for a future discrete choice experiment (DCE) on Internet hospital preferences among Chinese patients with chronic diseases.

METHODS

A mixed-methods approach was applied to systematically develop the relevant attributes and levels. Potential attributes were first identified through a systematic literature review. Next, qualitative interviews with 24 patients with chronic diseases were conducted to elicit contextual attributes. These attributes were then evaluated by 12 experts, and the expert ranking method was applied to prioritize the most relevant ones. Finally, the attributes and levels were determined in accordance with the established principles for developing DCE attributes and levels.

RESULTS

The literature review included 11 studies and generated 34 potential attributes. Patient interviews identified 29 candidate attributes across four dimensions: platform and institutional characteristics, physician service quality, specific services, and drug delivery and related costs. After expert consultation and ranking, seven candidate attributes with 18 levels were retained for a future DCE: out-of-pocket cost, ease of use, physician's professional title, mode of consultation, upload of self-monitoring data and automatic alerts for abnormal readings, access to electronic medical records and test results, and patient ratings.

CONCLUSION

This study developed a preliminary attribute-level framework for a future DCE. The framework provides a structured basis for pilot testing and subsequent preference elicitation, and may inform patient-centered Internet hospital service design after further validation.