Provision of Paid Web-Based Medical Consultation in China: Cross-Sectional Analysis of Data From a Medical Consultation Website

Li, Yumei; Yan, Xiangbin; Song, Xiaolong

doi:10.2196/12126

Cited by 50 publications

(34 citation statements)

References 18 publications

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“…In fact, 26.6% of Chinese internet users use the internet to access online medical service [1]. Internet users adopt online medical platforms and related applications for evaluation of doctors [2], medical inquires [3], and health management [4]. The Chinese government and health practitioners have recognized challenges and opportunities, given the increasing adoption and diffusion of information communication technologies (ICTs) in the health care system [5].…”

Section: Introductionmentioning

confidence: 99%

The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study

Ma¹,

Wu²

2019

J Med Internet Res

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BackgroundThe eHealth Literacy Scale (eHEALS) is the most widely used instrument in health studies to measure individual’s electronic health literacy. Nonetheless, despite the rapid development of the online medical industry and increased rural-urban disparities in China, very few studies have examined the characteristics of the eHEALS among Chinese rural people by using modern psychometric methods. This study evaluated the psychometric properties of eHEALS in a Chinese rural population by using both the classical test theory and item response theory methods.ObjectiveThis study aimed to develop a simplified Chinese version of the eHEALS (C-eHEALS) and evaluate its psychometric properties in a rural population.MethodsA cross-sectional survey was conducted with 543 rural internet users in West China. The internal reliability was assessed using the Cronbach alpha coefficient. A one-factor structure of the C-eHEALS was obtained via principal component analysis, and fit indices for this structure were calculated using confirmatory factory analysis. Subsequently, the item discrimination, difficulty, and test information were estimated via the graded response model. Additionally, the criterion validity was confirmed through hypothesis testing.ResultsThe C-eHEALS has good reliability. Both principal component analysis and confirmatory factory analysis showed that the scale has a one-factor structure. The graded response model revealed that all items of the C-eHEALS have response options that allow for differentiation between latent trait levels and the capture of substantial information regarding participants’ ability.ConclusionsThe findings indicate the high reliability and validity of the C-eHEALS and thus recommend its use for measuring eHealth literacy among the Chinese rural population.

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Section: Introductionmentioning

confidence: 99%

The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study

Ma¹,

Wu²

2019

J Med Internet Res

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“…In this study, the app and review selection strategy benefited research, with better generalization and time-efficiency. Despite many works that have discussed virtual hospitals from the perspective of economics [ 21 ] or doctors [ 9 ], this paper is the first to provide an in-depth report and highlight situations from the users’ perspective.…”

Section: Discussionmentioning

confidence: 99%

“…Importantly, the Chinese government is vigorously promoting this new type of health service to support health care reform [ 4 , 5 ]. Virtual hospitals play an effective role in reinforcing traditional health care and allow for a flexible relationship between physicians and patients [ 6 ] in many countries around the world [ 7 - 9 ].…”

Section: Introductionmentioning

confidence: 99%

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User Perceptions of Virtual Hospital Apps in China: Systematic Search

Yuan¹,

Liu²,

Shi³

et al. 2020

JMIR Mhealth Uhealth

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Background Virtual hospital apps are mobile apps that offer functionalities of online consultation, medical guidance, health community forums, referrals, outpatient appointments or virtual hospital-to-home care services. With an increasing number of online medical and health care consulting services, virtual hospital apps have made health care more accessible and fairer for all, especially in China. However, they have occurred without control or regulation. User evaluation can provide directions to help apps optimize identification, lower risks, and guarantee service quality. Objective We aimed to conduct a systematic search for virtual hospital apps in China. To get a global view, virtual hospital apps were assessed and characterized by means of quantitative analysis. To get a local view, we conducted a content feedback analysis to explore user requirements, expectations, and preferences. Methods A search was conducted of the most popular Apple and Android app stores in China. We characterized and verified virtual hospital apps and grouped apps according to quantification analysis. We then crawled apps and paid attention to corresponding reviews to incorporate users’ involvement, and then performed aspect-based content labeling and analysis using an inductive approach. Results A total of 239 apps were identified in the virtual hospital app markets in China, and 2686 informative corresponding reviews were analyzed. The evidence showed that usefulness and ease of use were vital facts for engagement. Users were likely to trust a consulting service with a high number of downloads. Furthermore, users expected frequently used apps with more optimization to improve virtual service. We characterized apps according to 4 key features: (1) app functionalities, including online doctor consultation, in-app purchases, tailored education, and community forums; (2) security and privacy, including user data management and user privacy; (3) health management, including health tracking, reminders, and notifications; and (4) technical aspects, including user interface and equipment connection. Conclusions Virtual hospitals relying on the mobile internet are growing rapidly. A large number of virtual hospital apps are available and accessible to a growing number of people. Evidence from this systematic search can help various types of virtual hospital models enhance virtual health care experiences, go beyond offline hospitals, and continuously meet the needs of individual end users.

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“…All kinds of online medical and health services also alleviate the lack of medical resources in certain areas and the imbalance of regional distribution in the country [ 1 ]. The analysis of healthcare services based on social media platforms, online doctor reviews, and web-based medical consultation in China are given in [ 2 – 4 ]. However, there are still many problems.…”

Section: Introductionmentioning

confidence: 99%

Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs

Yan

2020

Computational Intelligence and Neuroscience

Self Cite

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The recommendation system in the online medical consultation website is a system to assist patients to find appropriate doctors. Based on the analysis of the current situation of the development of an online medical community (Haodf.com) in China, this paper puts forward recommendation suggestions of finding the right hospital and doctor to promote the rapid integration of Internet technology and traditional medical services. A new recommendation model called Probabilistic Matrix Factorization integrated with Convolutional Neural Network (PMF-CNN) is proposed in the paper. Doctors’ data in Haodf.com were used to evaluate the performance of our system. The model improves the performance of medical consultation recommendations by fusing review text and doctor information based on CNN (Convolutional Neural Network). Specifically, CNN is used to learn the feature representation of the review text and the doctors’ information. Furthermore, the extended matrix factorization model is exploited to fuse the review information feature and the initial value of the doctors’ information for recommendation. As is shown in the experimental results on Haodf.com datasets, the proposed PMF-CNN achieves better recommendation performances than the other state-of-the-art recommendation algorithms. And the recommendation system in an online medical website improves the utilization efficiency of doctors and the balance of public health resources allocation.

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Provision of Paid Web-Based Medical Consultation in China: Cross-Sectional Analysis of Data From a Medical Consultation Website

Cited by 50 publications

References 18 publications

The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study

The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study

User Perceptions of Virtual Hospital Apps in China: Systematic Search

Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs

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