Characteristics of Online Health Care Services From China's Largest Online Medical Platform: Cross-sectional Survey Study

Abstract

Background: Internet hospitals in China are in great demand due to limited and unevenly distributed health care resources, lack of family doctors, increased burdens of chronic diseases, and rapid growth of the aged population. The COVID-19 epidemic catalyzed the expansion of online health care services. In recent years, internet hospitals have been rapidly developed. Ping An Good Doctor is the largest, national online medical entry point in China and is a widely used platform providing online health care services.

Objective: This study aims to give a comprehensive description of the characteristics of the online consultations and inquisitions in Ping An Good Doctor. The analyses tried to answer the following questions: (1) What are the characteristics of the consultations in Ping An Good Doctor in terms of department and disease profiles? (2) Who uses the online health services most frequently? and (3) How is the user experience of the online consultations of Ping An Good Doctor?

Methods: A total of 35.3 million consultations and inquisitions over the course of 1 year were analyzed with respect to the distributions of departments and diseases, user profiles, and consulting behaviors.

Results: The geographical distribution of the usage of Ping An Good Doctor showed that Shandong (18.4%), Yunnan (15.6%), Shaanxi (7.2%), and Guangdong (5.5%) were the provinces that used it the most; they accounted for 46.6% of the total consultations and inquisitions. In terms of department distribution, we found that gynecology and obstetrics (19.2%), dermatology (17.0%), and pediatrics (14.4%) were the top three departments in Ping An Good Doctor. The disease distribution analysis showed that, except for nondisease-specific consultations, acute upper respiratory infection (AURI) (4.1%), pregnancy (2.8%), and dermatitis (2.4%) were the most frequently consulted diseases. In terms of user profiles, females (60.4%) from 19 to 35 years of age were most likely to seek consultations online, in general. The user behavior analyses showed that the peak times of day for online consultations occurred at 10 AM, 3 PM, and 9 PM. Regarding user experience, 93.0% of users gave full marks following their consultations. For some disease-related health problems, such as AURI, dermatitis, and eczema, the feedback scores were above average.

Conclusions: The prevalence of internet hospitals, such as Ping An Good Doctor, illustrated the great demand for online health care services that can go beyond geographical limitations. Our analyses showed that nondisease-specific issues and moderate health problems were much more frequently consulted about than severe clinical conditions. This indicated that internet hospitals played the role of the family doctor, which helped to relieve the stress placed on offline hospitals and facilitated people's lives. In addition, good user experiences, especially regarding disease-related inquisitions, suggested that online health services can help solve health problems. With support from the government and acceptance by the public, online health care services could develop at a fast pace and greatly benefit people's daily lives.

Keywords: COVID-19; China; app; digital health; eHealth; internet hospital; mHealth; online consultation; online health care services; user experience.

Figure 1

The process of data selection and the data sets that were used for different analyses.

Figure 2

The number of consultations and inquisitions from all over China out of the original 113.8 million data points. Red dots indicate the capital city of each province and the black dot indicates the city of Kunming. Kunming had the largest volume of consultations and inquisitions in Ping An Good Doctor at the city level.

Figure 3

Departments represented in the consultations and inquisitions: (a) distribution of the departments; (b) change ratios of the distribution of the top 14 departments during and after the outbreak of COVID-19 in China.

Figure 4

Distribution of the top 30 diseases represented in the yearly visits to Ping An Good Doctor; change ratios of the distribution of diseases during and after the outbreak of COVID-19 in China are also shown.

Figure 5

Disease profiles of the top five departments: (a) gynecology and obstetrics, (b) dermatology, (c) pediatrics, (d) general internal medicine, and (e) urology and andrology.

Figure 6

User profiles for the top 14 departments: (a) percentiles of male users by department; (b) age distribution.

Figure 7

Characteristics of users' behaviors regarding the top 15 diseases: (a) distribution of times of day of consultations; (b) distribution of rounds of dialogue between users and physicians.

Figure 8

Users’ satisfaction with the online consultations: (a) the distribution of satisfaction scores; (b) the proportion of users who scored the consultations and inquisitions and the corresponding scores related to the top 20 diseases. Scores range from 1 (least satisfaction) to 5 (most satisfaction).