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. 2022 Aug 16;10(8):1551.
doi: 10.3390/healthcare10081551.

Study on the Relationships between Doctor Characteristics and Online Consultation Volume in the Online Medical Community

Zhu Chen  1 , Qingli Song  1 , An Wang  1 , Dong Xie  2 , Huiying Qi  3
Affiliations

Study on the Relationships between Doctor Characteristics and Online Consultation Volume in the Online Medical Community

Zhu Chen et al. Healthcare (Basel). .

Abstract

Background: As a new medical service model, the online health community can integrate various medical resources to the maximum extent and improve the accessibility and utilization rate of hospital high-quality medical resources.

Objective: Research based on the characteristics of doctors can enable doctors to display themselves on the network platform better, provide better services for patients, and improve the quality of medical services for doctors.

Method: By crawling the characteristic data of doctors in Good Doctor Online, using dynamic analysis, correlation analysis and regression analysis, this study explores the relationships between each characteristic data and online consultation volume.

Results: The doctor's title and city level representing the static characteristics of the doctor have a weak impact on the doctor's online consultation volume, and the doctor's dynamic characteristics such as the number of patient completions, the number of gifts received, and the number of published articles can have a positive impact on the doctor's online consultation volume. However, the recommended heat will negatively affect the online consultation volume, and the comment text has no significant impact on the doctor's online consultation volume.

Conclusion: Therefore, doctors should actively publicize and show their professional level and constantly optimize their dynamic characteristics, increasing the number of online consultations and thus improving their influence.

Keywords: correlation analysis; doctor characteristic; emotional analysis; online consultation volume; online health community; regression analysis.

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Conflict of interest statement

The authors declare that they have no competing interests.

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