Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 29, 2021
Date Accepted: May 20, 2021

The final, peer-reviewed published version of this preprint can be found here:

Consultation Pricing of the Online Health Care Service in China: Hierarchical Linear Regression Approach

Chiu YL, Wang JN, Yu H, Hsu YT

Consultation Pricing of the Online Health Care Service in China: Hierarchical Linear Regression Approach

J Med Internet Res 2021;23(7):e29170

DOI: 10.2196/29170

PMID: 34259643

PMCID: 8319787

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Consultation Pricing of Online Healthcare Service in China: A Hierarchical Linear Regression Approach

  • Ya-Ling Chiu; 
  • Jying-Nan Wang; 
  • Haiyan Yu; 
  • Yuan-Teng Hsu

ABSTRACT

Background:

The online healthcare service is a possible solution to alleviate the lack of medical resources in rural areas, and further understanding of the related medical service pricing system would contribute to the improvement of the online healthcare industry (OHI). Although many studies have investigated OHI, the impact of physicians’ reputation and the wage level on consulting price in the OHI has rarely been discussed in the existing literature.

Objective:

This study was designed to explore the determinants of consulting prices in the OHI. We addressed the following questions. (1) Are there consulting prices of the online health consultation services affected by the wage level of the doctor’s location? (2) How would a physician’s online and offline reputation affect his/her consulting prices?

Methods:

All data were collected from the Good Doctor website, which is the largest online healthcare community (OHC) in China. We first used descriptive statistics to investigate the determinants of consulting prices in its entirety. Then, since there are multiple levels of data structure, hierarchical linear modeling is used to verify the relationships between the online healthcare consulting price and these determinants.

Results:

Our sample included 16,008 physicians from 1,628 traditional hospitals, and 30 different provinces. Findings indicate that if doctors have more elevated clinic titles, higher academic ranks, better online reputations, and/or more past sales, their consulting prices will be higher. Additionally, the wage level of the city in which the doctor is working determines his or her opportunity cost and therefore also affects consulting prices.

Conclusions:

The findings indicate that the characteristics of the doctor, online reputation, past sales affect the consulting price. In particular, the results of the wage level of the city affect the price of the consultation. Findings highlight the importance of OHI can indeed break geographical restrictions and give rural residents the opportunity to obtain medical service from big cities. However, doctors from cities often charge higher fees because of higher opportunity cost. Results reveal that one of the most important functions of OHI is to reduce the medical disparity between urban and rural areas, but people seem to ignore the fact that rural residents with lower incomes may not be able to afford such high medical consultation costs. Therefore, the government can provide incentives to encourage urban doctors to give some discounts to rural residents or can directly provide appropriate subsidies.


 Citation

Please cite as:

Chiu YL, Wang JN, Yu H, Hsu YT

Consultation Pricing of the Online Health Care Service in China: Hierarchical Linear Regression Approach

J Med Internet Res 2021;23(7):e29170

DOI: 10.2196/29170

PMID: 34259643

PMCID: 8319787

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.