Electronic consultation accessibility influence on patient assessments: A case-control study with user-generated tags of physician expertise.

Objective: In online health communities (OHCs), patients often list their physicians' expertise by user-generated tags based on their consulted diseases. These expertise tags play an essential role in recommending the match of physicians to future patients. However, few studies have examined the impact of the accessibility of e-consults on patient assessments using marking of the physicians' expertise in OHCs. This study aims to investigate what are the patient assessments of the physicians' expertise if they have e-consult accessibility. Methods: Through a case-control study, this article examined the effect of e-consult accessibility on patient-generated tags of physician expertise in OHCs. With data collected from the Good Doctor website, the samples consisted of 9841 physicians from 1255 different hospitals widely distributed in China. The breadth of voted expertise (BE) is measured by the number of consulted disease-related labels marked by a physician's served patients (SP). The volume of votes (VV) is measured by the number of a physician's votes given by the SP. The degree of voted diversity (DD) is measured by the information entropy of each physician's service expertise (labeled and voted by patients). The data analysis of e-consult accessibility is conducted by estimating the average treatment effect on the DD of physicians' expertise. Results: For the BE, its mean was 7.305 for the case group of physicians with e-consults accessible (photo and text queries), while the mean was 9.465 for the control for physicians without e-consults. For the VV, its mean was 39.720 for the case group, while the mean was 84.565 for the control. For the DD, its mean on patient-generated tags was 2.103 for the case group, which is 0.413 lower than the control group. Conclusion: The availability of e-consults increases the concentration on physician expertise in the patient-generated tags. e-Consults reinforce the increment of the already-received physician expertise (reflected in tags), reducing the tag information diversity.

Can online health information sources really improve patient satisfaction?

Internet information has become the main way for individuals to obtain health information. The purpose of this paper is to explore the role online information sources play in health decision-making. Specifically, we investigated the relationship between online information sources and patient satisfaction, as well as their moderating effects as compared to those of other information sources. Using logistical regression analysis, we conducted the longitudinal data on 54,027 doctors and 952,877 online doctor reviews from 3,525 hospitals in 31 provinces to test a proposed research model. The results showed that patient satisfaction was generally lower for individuals who found a doctor through online information sources. Therefore, we suggest that patients consider the doctor quality, the doctor popularity, and patient involvement. In addition, we found that the doctor popularity had a negative moderating effect between online information sources and patient satisfaction, while patient involvement had a positive moderating effect between online information sources and patient satisfaction. The study provides strategic guidance and practical implications for policies, online healthcare community managers, and patients.

Impacts of physician promotion on the online healthcare community: Using a difference-in-difference approach.

In this study, we use a difference-in-difference approach to explore how physician promotion, the advancement of a physician's offline reputation, affects patient behavior toward physicians in online healthcare communities; this allows us to explore how patients interpret the signals created by physician promotion. The study sample was collected from over 140,000 physician online profiles after 25 months of continuous observation, with 280 physicians who were promoted at month 13 as the treatment group and a control group obtained by propensity score matching. Our results show that a physician's promotion causes more patients to choose that physician, makes patients willing to give more psychological rewards, and makes them tend to give that physician a higher online rating. This implies that patient behavior is susceptible to the signal of physician promotion because the quality of the physician is unlikely to have changed significantly in the short term. These findings extend prior research on reputation in online communities and have crucial implications for theory and practice.

Understanding the Inequality of Web Traffic and Engagement in Online Healthcare Communities.

The online healthcare community (OHC) is a kind of doctor-patient communication platform, in which doctors can share medical knowledge and provide various kinds of counsel for patients. However, if the OHC's web traffic is concentrated on a small number of doctors, or if only a few doctors are actively involved in the OHC's activities, this will not be conducive to the optimal development of the OHC. This study explores this issue of inequality and makes three main innovations. First, based on data on web traffic and engagement extracted from 139,037 doctors' web pages in one popular OHC, we point out how serious the inequality phenomenon is. Second, we confirm that the Matthew effect indeed exists in this context and leads to greater inequality. Third, we demonstrate that the inequality of psychological or material rewards causes the inequality of web traffic or engagement to become worse; hence, an appropriate reward mechanism should be designed to mitigate the Matthew effect rather than enhance it. Finally, we discuss the managerial implications of these results, as well as avenues for future studies.

Extracting Additional Influences From Physician Profiles With Topic Modeling: Impact on Ratings and Page Views in Online Healthcare Communities.

How physicians can get better ratings and more page views in online healthcare communities is an important issue. Based on 38,457 physicians' profiles from a popular online healthcare community in China, we used Latent Dirichlet Allocation model, which is a common topic model, to analyze the non-English text to obtain more doctor's latent characteristics. We found five of the most frequently mentioned topics. In addition to the first topic (doctor's academic rank and practice name), "research ability," "foreign experience," "committee position," and "clinical experience" were included as unstructured descriptions in the doctor's profile. Inferences about physician ratings and page views could be improved if these themes were set as characteristics of physicians. Specifically, in our findings, Physicians' mentions of their "research ability" and "foreign experience" had a significant positive impact on physician ratings. Surprisingly, physicians mentioning more "clinical experience" had a significant negative impact on physician ratings. Moreover, while descriptions about "foreign experience" and "committee position" had a significant positive impact on page views, physician mentions of "research ability" had a significant negative impact on page views. These results provide new insights into the ways in which online healthcare community managers or physicians create their personal online profiles.

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

BACKGROUND: Online health care services are 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 improvement of the online health care community (OHC). Although many studies have investigated the OHC, the impact of physicians' reputations and wage levels on consulting prices in the OHC has rarely been discussed in the literature. OBJECTIVE: This study was designed to explore the determinants of consulting prices in the OHC. We addressed the following questions: (1) Are the prices of online health consultation services affected by wage levels at the doctor's location? (2) How does a physician's online and offline reputation affect their consulting prices? METHODS: Employing a large-scale sample of 16,008 doctors in China, we first used descriptive statistics to investigate the determinants of consulting prices in their entirety. Hierarchical linear modeling was then used to investigate the determinants of consulting prices in the OHC. RESULTS: The empirical results led to the conclusion that if doctors have more elevated clinic titles, work in higher-level hospitals, have better online reputations, and/or have made more past sales, their consulting prices will be higher. Additionally, the wage level in the city in which the doctor is working determines their opportunity cost and therefore also affects consulting prices. CONCLUSIONS: The findings indicate that the characteristics of the doctor, the doctor's online reputation, and past sales affect the consulting price. In particular, the wage level in the city affects the price of the consultation. These findings highlight that the OHC is important because it can indeed break through geographical restrictions and give rural residents the opportunity to obtain medical service from doctors in big cities. However, doctors from cities often charge higher fees because of their higher opportunity cost. The results reveal that one of the most important functions of the OHC is to reduce the medical disparity between urban and rural areas; however, planners appear to ignore the possibility that rural residents with lower incomes may not be able to afford such high medical consultation costs. Therefore, the government should consider providing incentives to encourage urban doctors to provide discounts to rural residents or directly offer appropriate subsidies.

Exploring Types of Information Sources Used When Choosing Doctors: Observational Study in an Online Health Care Community.

BACKGROUND: Patients attempt to make appropriate decisions based on their own knowledge when choosing a doctor. In this process, the first question usually faced is that of how to obtain useful and relevant information. This study investigated the types of information sources that are used widely by patients in choosing a doctor and identified ways in which the preferred sources differ in various situations. OBJECTIVE: This study aims to address the following questions: (1) What is the proportion in which each of the various information sources is used? (2) How does the information source preferred by patients in choosing a doctor change when there is a difference in the difficulty of medical decision making, in the level of the hospital, or in a rural versus urban situation? (3) How do information sources used by patients differ when they choose doctors with different specialties? METHODS: This study overcomes a major limitation in the use of the survey technique by employing data from the Good Doctor website, which is now China's leading online health care community, data which are objective and can be obtained relatively easily and frequently. Multinomial logistic regression models were applied to examine whether the proportion of use of these information sources changes in different situations. We then used visual analysis to explore the question of which type of information source patients prefer to use when they seek medical assistance from doctors with different specialties. RESULTS: The 3 main information sources were online reviews (OR), family and friend recommendations (FR), and doctor recommendations (DR), with proportions of use of 32.93% (559,345/1,698,666), 23.68% (402,322/1,698,666), and 17.48% (296,912/1,698,666), respectively. Difficulty in medical decision making, the hospital level, and rural-urban differences were significantly associated with patients' preferred information sources for choosing doctors. Further, the sources of information that patients prefer to use were found to vary when they looked for doctors with different medical specialties. CONCLUSIONS: Patients are less likely to use online reviews when medical decisions are more difficult or when the provider is not a tertiary hospital, the former situation leading to a greater use of online reviews and the latter to a greater use of family and friend recommendations. In addition, patients in large cities are more likely to use information from online reviews than family and friend recommendations. Among different medical specialties, for those in which personal privacy is a concern, online reviews are the most common source. For those related to children, patients are more likely to refer to family and friend recommendations, and for those related to surgery, they value doctor recommendations more highly. Our results can not only contribute to aiding government efforts to further promote the dissemination of health care information but may also help health care industry managers develop better marketing strategies.

Understanding a Nonlinear Causal Relationship Between Rewards and Physicians' Contributions in Online Health Care Communities: Longitudinal Study.

BACKGROUND: The online health care community is not just a place for the public to share physician reviews or medical knowledge, but also a physician-patient communication platform. The medical resources of developing countries are relatively inadequate, and the online health care community is a potential solution to alleviate the phenomenon of long hospital queues and the lack of medical resources in rural areas. However, the success of the online health care community depends on online contributions by physicians. OBJECTIVE: The aim of this study is to examine the effect of incentive mechanisms on physician's online contribution behavior in the online health community. We addressed the following questions: (1) from which specialty area are physicians more likely to participate in online health care community activities, (2) what are the factors affecting physician online contributions, and (3) do incentive mechanisms, including psychological and material rewards, result in differences of physician online contributions? METHODS: We designed a longitudinal study involving a data sample in three waves. All data were collected from the Good Doctor website, which is the largest online health care community in China. We first used descriptive statistics to investigate the physician online contribution behavior in its entirety. Then multiple linear and quadratic regression models were applied to verify the causal relationship between rewards and physician online contribution. RESULTS: Our sample included 40,300 physicians from 3607 different hospitals, 10 different major specialty areas, and 31 different provinces or municipalities. Based on the multiple quadratic regression model, we found that the coefficients of the control variables, past physician online contributions, doctor review rating, clinic title, hospital level, and city level, were .415, .189, -.099, -.106, and -.143, respectively. For the psychological (or material) rewards, the standardized coefficient of the main effect was 0.261 (or 0.688) and the standardized coefficient of the quadratic effect was -0.015 (or -0.049). All estimates were statistically significant (P<.001). CONCLUSIONS: Physicians with more past physician online contribution, with higher review ratings, coming from lower level clinics, not coming from tertiary hospitals, and not coming from big cities were more willing to participate in online health care community activities. To promote physician online contribution, it is necessary to establish an appropriate incentive mechanism including psychological and material rewards. Finally, our findings suggest two guidelines for designing a useful incentive mechanism to facilitate physician online contribution. First, material reward is more useful than psychological reward. Second, as indicated by the concave-down-increasing causal relationship between rewards and physician online contribution, although an appropriate reward is effective in encouraging willingness on the part of physicians to contribute to the online health care community, the effect of additional rewards is limited.