Do Physicians’ Online Activities Impact Outpatient Visits? An Examination of Online Health Communities

The medical service on online health communities (OHCs) has created an additional touch point whereby physicians can interact with patients and extends physicians’ service from hospitals to the online environment. As the supplement and improvement of physicians’ diagnosis and treatment services, online consultation services can make full use of physicians’ spare time. Despite heated debates about the pros and cons of the online services to the traditional services in the hospitals, little empirical work has been conducted to examine it. We seek to understand and measure the impacts of physicians’ various activities online on their outpatient visits in the hospitals. By collecting a panel dataset from an OHC and a hospital in China, we find that participation in the OHCs leads to an increase in outpatient visits. We provide insights for physicians about how to increase patient visits in the emerging era of the Internet medical

Applying Technology Acceptance Model to Explore the Determinants of Mobile Health Service: From the Perspective of Public User

With the rapid usage rate of mobile phone and advances in healthcare technology, as well as current concerns arise over public’s health, mobile health are attracting the attention of more and more people. Although previous studies on the adoption of mobile services are quite extensive, few focus on public users’ adoption of mobile health service (MHS). In this study, we examine the determinants of user adoption of MHS based on Technology acceptance model (TAM). The findings confirm that perceived usefulness positively affect users’ attitude toward MHS, perceived service availability significantly impact on perceived ease of use and perceived usefulness, perceived usefulness and attitude directly enhance intention

Developing urban design as public policy in China : a case study in Shenzhen

This research explores how China has been developing urban design as public policy in the context of rapid urbanization and radical Socialist market reform. This is not a well developed area in urban research in China, however Western literature provides a good comparative basis through which to develop a more sophisticated system of design control. In pursuing the research objective, a Chinese city - Shenzhen has been chosen as a case study. It is the national exemplar and represents the best Chinese practices. Inspired by international aspirations for good practice in design control, the Shenzhen case study allows exploration of the political and economic influences on design outcomes, reveals the instruments used by planners to promote good design, uncovers the shifting concept of urban design, and assesses the impacts of the permitting process on project design. Some 11 commercial office projects have been selected to provide empirical evidence. They range from masterplanned projects in central locations to individual developments in off-centre locations, from conventional developments to projects involving appeals and illegal constructions, from recently completed projects to the ones still in the planning process. The event-sequence and structure-agency models derived from real-estate research have been used to analyse design processes. To collect the data, a 'snowball approach' mixed with participant-observation, documentary review, interview and design evaluation are utilised. This research reveals that Shenzhen has achieved progressive improvements in developing urban design as public policy. However urban design's public values are only partially embedded in Shenzhen's urban planning system, due to rapid urbanization processes, the significant change of development scale, top-down hierarchy of political control, lack of discrimination among tenants and the partial application of the generic urban design principles in the planning and design process. Shenzhen is facing many challenges when compared with the best international practice in design review. In detail, the city has a strong design vision for its future, but this is not developed with the local communities, and only reflects an elite vision that is both short-term and oriented towards business. The political support, the use of land powers, and discretionary zoning control have provided a solid basis for Shenzhen to pursue higher quality urban design, but a more regulated system is needed to limit political intervention and provide a better research base for planning decision making. Planners are slowly developing urban design principles to address the quality of the public realm, but they need a deeper understanding of the generic design principles and sustainable design. Shenzhen's established planning permission process has been a successful mechanism for design intervention, but it needs to address weaknesses in public participation and in dealing with monitoring, enforcement and appeal. It is argued that Shenzhen is representative of most large Chinese cities, but small or medium size cities and the cities with conservation issues may have slightly different experiences. Future challenges are discussed and practical suggestions are made to better develop urban design as public policy in Shenzhen and more generally in China.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An Empirical Study of Customer Satisfaction and Loyalty on Health Websites

Numerous health websites are developing rapidly in China and the competition is fierce between these websites. In order to win the competition, the websites operators need to satisfy their customers to attain more market shares. But few attention has been paid to factors affecting customer satisfaction and loyalty on these websites. As a result, the paper aims to empirically explore the factors affecting customer satisfaction and loyalty on health websites based on perceived service quality (responsiveness, empathy and reliability), perceived risk (financial risk and time risk) and trust, and then to propose some targeted measures. A survey was conducted to collect data by means of questionnaires, and a total of 231 usable responses were gathered. Then the hypothesis model was tested using the Structural Equation Modeling(SEM). Results revealed that responsiveness, empathy, time risk and trust had significant impacts on customer satisfaction, whereas reliability and financial risk showed no effects on customer satisfaction. In addition, customer satisfaction and trust significantly influenced customer loyalty. The implications and limitations were discussed

The Why of Abandonment: Effects of Team Diversity and Leadership Type on the Disbandment and Stagnation of Online Medical Teams

Medical teams (MTs) online could provide more comprehensive and rapid services to patients through the collaboration among physicians. Numerous doctors have participated, but parts of MTs disband or stagnate after a period, so this pressing issue is in need of relief through exploring the reasons. Effects of team diversity, leadership types and their interaction on the team disbandment and stagnation were studied. This study comprehensively examined a sample of 1,071 MTs online, the total MTs on January 10, 2018, and we crawled the data from a leading OHC in China. Logistic regression was utilized. Results revealed team state would be influenced by team diversity and its interaction with leadership type, so the combination pairwise of the leadership and team diversity could reduce the abandonment possibility. Implications in theory and practice about the dealing with the abandonment crisis in online health community, and limitations are discussed

Developing urban design as public policy in China : a case study in Shenzhen

This research explores how China has been developing urban design as public policy in the context of rapid urbanization and radical Socialist market reform. This is not a well developed area in urban research in China, however Western literature provides a good comparative basis through which to develop a more sophisticated system of design control. In pursuing the research objective, a Chinese city - Shenzhen has been chosen as a case study. It is the national exemplar and represents the best Chinese practices. Inspired by international aspirations for good practice in design control, the Shenzhen case study allows exploration of the political and economic influences on design outcomes, reveals the instruments used by planners to promote good design, uncovers the shifting concept of urban design, and assesses the impacts of the permitting process on project design. Some 11 commercial office projects have been selected to provide empirical evidence. They range from masterplanned projects in central locations to individual developments in off-centre locations, from conventional developments to projects involving appeals and illegal constructions, from recently completed projects to the ones still in the planning process. The event-sequence and structure-agency models derived from real-estate research have been used to analyse design processes. To collect the data, a 'snowball approach' mixed with participant-observation, documentary review, interview and design evaluation are utilised. This research reveals that Shenzhen has achieved progressive improvements in developing urban design as public policy. However urban design's public values are only partially embedded in Shenzhen's urban planning system, due to rapid urbanization processes, the significant change of development scale, top-down hierarchy of political control, lack of discrimination among tenants and the partial application of the generic urban design principles in the planning and design process. Shenzhen is facing many challenges when compared with the best international practice in design review. In detail, the city has a strong design vision for its future, but this is not developed with the local communities, and only reflects an elite vision that is both short-term and oriented towards business. The political support, the use of land powers, and discretionary zoning control have provided a solid basis for Shenzhen to pursue higher quality urban design, but a more regulated system is needed to limit political intervention and provide a better research base for planning decision making. Planners are slowly developing urban design principles to address the quality of the public realm, but they need a deeper understanding of the generic design principles and sustainable design. Shenzhen's established planning permission process has been a successful mechanism for design intervention, but it needs to address weaknesses in public participation and in dealing with monitoring, enforcement and appeal. It is argued that Shenzhen is representative of most large Chinese cities, but small or medium size cities and the cities with conservation issues may have slightly different experiences. Future challenges are discussed and practical suggestions are made to better develop urban design as public policy in Shenzhen and more generally in China

Machine learning-based prediction models for patients no-show in online outpatient appointments

With the development of information and communication technologies, all public tertiary hospitals in China began to use online outpatient appointment systems. However, the phenomenon of patient no-shows in online outpatient appointments is becoming more serious. The objective of this study is to design a prediction model for patient no-shows, thereby assisting hospitals in making relevant decisions, and reducing the probability of patient no-show behavior. We used 382,004 original online outpatient appointment records, and divided the data set into a training set (N1 = 286,503), and a validation set (N2 = 95,501). We used machine learning algorithms such as logistic regression, k-nearest neighbor (KNN), boosting, decision tree (DT), random forest (RF) and bagging to design prediction models for patient no-show in online outpatient appointments. The patient no-show rate of online outpatient appointment was 11.1% (N = 42,224). From the validation set, bagging had the highest area under the ROC curve and AUC value, which was 0.990, followed by random forest and boosting models, which were 0.987 and 0.976, respectively. In contrast, compared with the previous prediction models, the area under ROC and AUC values of the logistic regression, decision tree, and k-nearest neighbors were lower at 0.597, 0.499 and 0.843, respectively. This study demonstrates the possibility of using data from multiple sources to predict patient no-shows. The prediction model results can provide decision basis for hospitals to reduce medical resource waste, develop effective outpatient appointment policies, and optimize operations

On Tightness of the Tsaknakis-Spirakis Algorithm for Approximate Nash Equilibrium

Finding the minimum approximate ratio for Nash equilibrium of bi-matrix games has derived a series of studies, started with 3/4, followed by 1/2, 0.38 and 0.36, finally the best approximate ratio of 0.3393 by Tsaknakis and Spirakis (TS algorithm for short). Efforts to improve the results remain not successful in the past 14 years. This work makes the first progress to show that the bound of 0.3393 is indeed tight for the TS algorithm. Next, we characterize all possible tight game instances for the TS algorithm. It allows us to conduct extensive experiments to study the nature of the TS algorithm and to compare it with other algorithms. We find that this lower bound is not smoothed for the TS algorithm in that any perturbation on the initial point may deviate away from this tight bound approximate solution. Other approximate algorithms such as Fictitious Play and Regret Matching also find better approximate solutions. However, the new distributed algorithm for approximate Nash equilibrium by Czumaj et al. performs consistently at the same bound of 0.3393. This proves our lower bound instances generated against the TS algorithm can serve as a benchmark in design and analysis of approximate Nash equilibrium algorithms

On the Re-Solving Heuristic for (Binary) Contextual Bandits with Knapsacks

In the problem of (binary) contextual bandits with knapsacks (CBwK), the agent receives an i.i.d. context in each of the $T$ rounds and chooses an action, resulting in a random reward and a random consumption of resources that are related to an i.i.d. external factor. The agent's goal is to maximize the accumulated reward under the initial resource constraints. In this work, we combine the re-solving heuristic, which proved successful in revenue management, with distribution estimation techniques to solve this problem. We consider two different information feedback models, with full and partial information, which vary in the difficulty of getting a sample of the external factor. Under both information feedback settings, we achieve two-way results: (1) For general problems, we show that our algorithm gets an $\widetilde O(T^{\alpha_u} + T^{\alpha_v} + T^{1/2})$ regret against the fluid benchmark. Here, $\alpha_u$ and $\alpha_v$ reflect the complexity of the context and external factor distributions, respectively. This result is comparable to existing results. (2) When the fluid problem is linear programming with a unique and non-degenerate optimal solution, our algorithm leads to an $\widetilde O(1)$ regret. To the best of our knowledge, this is the first $\widetilde O(1)$ regret result in the CBwK problem regardless of information feedback models. We further use numerical experiments to verify our results.Comment: 43 pages, 2 figures, 1 tabl