Stacking-BERT model for Chinese medical procedure entity normalization.

Medical procedure entity normalization is an important task to realize medical information sharing at the semantic level; it faces main challenges such as variety and similarity in real-world practice. Although deep learning-based methods have been successfully applied to biomedical entity normalization, they often depend on traditional context-independent word embeddings, and there is minimal research on medical entity recognition in Chinese Regarding the entity normalization task as a sentence pair classification task, we applied a three-step framework to normalize Chinese medical procedure terms, and it consists of dataset construction, candidate concept generation and candidate concept ranking. For dataset construction, external knowledge base and easy data augmentation skills were used to increase the diversity of training samples. For candidate concept generation, we implemented the BM25 retrieval method based on integrating synonym knowledge of SNOMED CT and train data. For candidate concept ranking, we designed a stacking-BERT model, including the original BERT-based and Siamese-BERT ranking models, to capture the semantic information and choose the optimal mapping pairs by the stacking mechanism. In the training process, we also added the tricks of adversarial training to improve the learning ability of the model on small-scale training data. Based on the clinical entity normalization task dataset of the 5th China Health Information Processing Conference, our stacking-BERT model achieved an accuracy of 93.1%, which outperformed the single BERT models and other traditional deep learning models. In conclusion, this paper presents an effective method for Chinese medical procedure entity normalization and validation of different BERT-based models. In addition, we found that the tricks of adversarial training and data augmentation can effectively improve the effect of the deep learning model for small samples, which might provide some useful ideas for future research.

Usage and perceptions of telemedicine among health care professionals in China.

OBJECTIVE: To explore health care professionals' usage and perceptions of telemedicine, including their experience, evaluation and attitude towards telemedicine, and the factors affecting their satisfaction, using intention, and willingness to recommend telemedicine. METHODS: A nationwide and web-based survey was conducted. Statistical charts were used to describe the usage and perceptions of telemedicine by health care professionals. And the ordinal logistic regression was applied to analyze the influencing factors. RESULTS: A total of 1349 valid questionnaires were collected. In the survey, 74.0 % of Chinese health care professionals used telemedicine once a week. The average duration of participating in telemedicine services lasted mainly 11-30 min (64.0 %). More than half (52.5 %) of participants' hospitals adopted fee subsidy measures, followed by the award for excellent evaluation (36.4 %). The majority (92.5 %) believed that telemedicine could reduce patient referral rates. More than 95 % were satisfied with telemedicine, were willing to continue, and would recommend telemedicine for patients, respectively. The main problems existing were: incomplete system equipment, insufficient timeliness, high costs, inability to reimburse medical insurance, non-standardized medical records, inadequate publicity, cumbersome processes and long waiting time. Ordinal logistic regression showed that too short service duration (≤10 min) could significantly reduce medical professionals' overall satisfaction, using intention and willingness to recommend (P = 0.026, P = 0.017 and P = 0.040 respectively), while the convenience of the operating system had a significant positive impact (P = 0.005, P = 0.003 and P = 0.001 respectively). And cost subsidy incentive and the promotion of professional titles could significantly enhance their overall satisfaction(P = 0.006, P = 0.030), using intention (P = 0.011, P = 0.001), and willingness to recommend (P = 0.040, P = 0.004). CONCLUSIONS: The usage of telemedicine is relatively insufficient. Most health care professionals have fairly positive opinions toward telemedicine. The most mentioned issues and expectations for telemedicine can be roughly divided into four categories: infrastructure, service process, charge and cost, and popularity. It is possible to improve their evaluation by improving system convenience, enhancing service punctuality, avoiding excessively short service duration and adopting incentive measures.

Telemedicine Is Becoming an Increasingly Popular Way to Resolve the Unequal Distribution of Healthcare Resources: Evidence From China.

Background: Few studies focused on the general situation of telemedicine in China. Objectives: The purpose of this review is to investigate telemedicine in China, from the aspects of necessity, history, scale, and operation procedure, to improve the further development and implementation of telemedicine service. Methods: A literature search for peer-reviewed studies was conducted using the primary electronic databases. Additional documents from the official websites of Chinese government departments involved telemedicine was also collected. We extracted telemedicine related information focused on China from the final retrieved materials, and the general situation of telemedicine was drawn. Results: In China, telemedicine offers a feasible solution to the unequal allocation of healthcare resources, which makes telemedicine increasingly become an important alternative to close the gap between rural and urban in the capability and quality of medical services. China initiated telemedicine in the late 1980s. In 2018, China's telemedicine network has covered more than 3,000 hospitals across the country. As of 2019, almost all of the 31 provinces and municipalities in mainland have established regional telemedicine centers, and the market size of telemedicine reached about USD 2.68 billion. Based on the telemedicine network, remote rural patients can apply for healthcare services of top-tier urban hospitals through local county-level medical institutions. Conclusions: Through improving the capacity, quality, and efficiency of healthcare in underserved areas, and reducing the unequal distribution of medical resources, telemedicine can help solve the problems of the difficulty and high cost to access to medical services in China.

A Study of Mobile Medical App User Satisfaction Incorporating Theme Analysis and Review Sentiment Tendencies.

Mobile medicine plays a significant role in optimizing medical resource allocation, improving medical efficiency, etc. Identifying and analyzing user concern elements from active online reviews can help to improve service quality and enhance product competitiveness in a targeted manner. Based on the latent Dirichlet allocation (LDA) topic model, this study carries out a topic-clustering analysis of users' online comments and builds an evaluation index system of mobile medical users' satisfaction by using grounded theory. After that, the evaluation information of users is obtained through an emotional analysis of online comments. Then, in order to fully consider the uncertainty of decision makers' evaluations, rough number theory and the fuzzy comprehensive evaluation method are used to confirm the conclusions of experts and indicators and to evaluate the satisfaction of mobile medical users. The empirical results show that users are satisfied with the service quality and content quality of mobile medical apps, and less satisfied with the management and technology qualities. Therefore, this paper puts forward corresponding countermeasures from the aspects of strengthening safety supervision, strengthening scientific research, strengthening information audit, attaching importance to service quality management and strengthening doctors' sense of gain. This study uses text mining for index extraction and satisfaction analysis of online reviews to quantitatively evaluate user satisfaction with mobile medical apps, providing a reference for the improvement of mobile medical apps. However, there are still certain shortcomings in the current study, and subsequent studies can screen false reviews for a deeper study of online review information.

Self-Adaptive Telemedicine Specialist Recommendation Considering Specialist Activity and Patient Feedback.

Purpose: With the rapid development of medical informatization, information overload and asymmetry have become major obstacles that limit patients' ability to find appropriate telemedicine specialists. Although doctor recommendation methods have been proposed, they fail to address data sparsity and cold-start issues, and electronic medical records (EMRs), patient preferences, potential interest of service providers and the changes over time are largely under-explored. Therefore, this study develops a self-adaptive telemedicine specialist recommendation method that incorporates specialist activity and patient utility feedback from the perspective of privacy protection to fill the research gaps. Methods: First, text vectorization, view similarity and probabilistic topic model are used to construct the patient and specialist feature models based on patients' EMRs and specialists' long- and short-term knowledge backgrounds, respectively. Second, the recommended specialist candidate set and recommendation index are obtained based on the similarity between patient features. Then, the specialist long-term knowledge feature model is used to update the newly registered specialist recommendation index and the recommended specialist candidate set to overcome the data sparsity and cold-start issues, and the specialist short-term knowledge feature model is adopted to extend the recommended specialist candidate set at the semantic level. Finally, we introduce the specialists' activity and patients' perceived utility feedback mechanism to construct a closed-loop adjusted and optimized specialist recommendation method. Results: An empirical study was conducted integrating EMRs of telemedicine patients from the National Telemedicine Center of China and specialists' profiles and ratings from an online healthcare platform. The proposed method successfully recommended relevant and active telemedicine specialists to the target patient, and increased the recommended opportunities for newly registered specialists to some extent. Conclusions: The proposed method emphasizes the adaptability and acceptability of the recommended results while ensuring their accuracy and relevance. Specialists' activity and patients' perceived utility jointly contribute to the acceptability of recommended results, and the recommendation strategy achieves the organic fusion of the two. Several comparative experiments demonstrate the effectiveness and operability of the hybrid recommendation strategy under the premise of data sparsity and privacy protection, enabling effective matching of patients' demand and service providers' capabilities, and providing beneficial insights for data-driven telemedicine services.

Construction and Application of an Intelligent Response System for COVID-19 Voice Consultation in China: A Retrospective Study.

Background: The outbreak of novel coronavirus disease 2019 (COVID-19) has led to tremendous individuals visit medical institutions for healthcare services. Public gatherings and close contact in clinics and emergency departments may increase the exposure and cross-infection of COVID-19. Objectives: The purpose of this study was to develop and deploy an intelligent response system for COVID-19 voice consultation, to provide suggestions of response measures based on actual information of users, and screen COVID-19 suspected cases. Methods: Based on the requirements analysis of business, user, and function, the physical architecture, system architecture, and core algorithms are designed and implemented. The system operation process is designed according to guidance documents of the National Health Commission and the actual experience of prevention, diagnosis and treatment of COVID-19. Both qualitative (system construction) and quantitative (system application) data from the real-world healthcare service of the system were retrospectively collected and analyzed. Results: The system realizes the functions, such as remote deployment and operations, fast operation procedure adjustment, and multi-dimensional statistical report capability. The performance of the machine-learning model used to develop the system is better than others, with the lowest Character Error Rate (CER) 8.13%. As of September 24, 2020, the system has received 12,264 times incoming calls and provided a total of 11,788 COVID-19-related consultation services for the public. Approximately 85.2% of the users are from Henan Province and followed by Beijing (2.5%). Of all the incoming calls, China Mobile contributes the largest proportion (66%), while China Unicom and China Telecom are accounted for 23% and 11%. For the time that users access the system, there is a peak period in the morning (08:00-10:00) and afternoon (14:00-16:00), respectively. Conclusions: The intelligent response system has achieved appreciable practical implementation effects. Our findings reveal that the provision of inquiry services through an intelligent voice consultation system may play a role in optimizing the allocation of healthcare resources, improving the efficiency of medical services, saving medical expenses, and protecting vulnerable groups.

Spatio-temporal distribution characteristics of COVID-19 in China: a city-level modeling study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have been conducted to investigate the spatio-temporal distribution of COVID-19 on nationwide city-level in China. OBJECTIVE: To analyze and visualize the spatiotemporal distribution characteristics and clustering pattern of COVID-19 cases from 362 cities of 31 provinces, municipalities and autonomous regions in mainland China. METHODS: A spatiotemporal statistical analysis of COVID-19 cases was carried out by collecting the confirmed COVID-19 cases in mainland China from January 10, 2020 to October 5, 2020. Methods including statistical charts, hotspot analysis, spatial autocorrelation, and Poisson space-time scan statistic were conducted. RESULTS: The high incidence stage of China's COVID-19 epidemic was from January 17 to February 9, 2020 with daily increase rate greater than 7.5%. The hot spot analysis suggested that the cities including Wuhan, Huangshi, Ezhou, Xiaogan, Jingzhou, Huanggang, Xianning, and Xiantao, were the hot spots with statistical significance. Spatial autocorrelation analysis indicated a moderately correlated pattern of spatial clustering of COVID-19 cases across China in the early phase, with Moran's I statistic reaching maximum value on January 31, at 0.235 (Z = 12.344, P = 0.001), but the spatial correlation gradually decreased later and showed a discrete trend to a random distribution. Considering both space and time, 19 statistically significant clusters were identified. 63.16% of the clusters occurred from January to February. Larger clusters were located in central and southern China. The most likely cluster (RR = 845.01, P < 0.01) included 6 cities in Hubei province with Wuhan as the centre. Overall, the clusters with larger coverage were in the early stage of the epidemic, while it changed to only gather in a specific city in the later period. The pattern and scope of clusters changed and reduced over time in China. CONCLUSIONS: Spatio-temporal cluster detection plays a vital role in the exploration of epidemic evolution and early warning of disease outbreaks and recurrences. This study can provide scientific reference for the allocation of medical resources and monitoring potential rebound of the COVID-19 epidemic in China.

Molecular mechanism study of HGF/c-MET pathway activation and immune regulation for a tumor diagnosis model.

BACKGROUND: Hepatocyte growth factor (HGF) binds to the c-mesenchymal-epithelial transition (C-MET) receptor and activates downstream signaling pathways, playing an essential role in the development of various cancers. Given the role of this signaling pathway, the primary therapeutic direction focuses on identifying and designing HGF inhibitors, antagonists and other molecules to block the binding of HGF to C-MET, thereby limiting the abnormal state of other downstream genes. METHODS: This study focuses on the analysis of immune-related genes and corresponding immune functions that are significantly associated with the HGF/c-MET pathway using transcriptome data from 11 solid tumors. RESULTS: We systematically analyzed 11 different cancers, including expression correlation, immune infiltration, tumor diagnosis and survival prognosis from HGF/c-MET pathway and immune regulation, two biological mechanisms having received extensive attention in cancer analysis. CONCLUSION: We found that the HGF/c-MET pathway affected the tumor microenvironment mainly by interfering with expression levels of other genes. Immune infiltration is another critical factor involved in changes to the tumor microenvironment. The downstream immune-related genes activated by the HGF/c-MET pathway regulate immune-related pathways, which in turn affect the degree of infiltration of immune cells. Immune infiltration is significantly associated with cancer development and prognosis.

Application of Telemedicine Services Based on a Regional Telemedicine Platform in China From 2014 to 2020: Longitudinal Trend Analysis.

BACKGROUND: Telemedicine that combines information technology and health care augments the operational model of traditional medical services and brings new opportunities to the medical field. China promotes telemedicine with great efforts, and its practices in the deployment of telemedicine platforms and delivery of services have become important references for the research and development in this field. OBJECTIVE: Our work described in this paper focuses on a regional telemedicine platform that was built in 2014. We analyzed the system design scheme and remote consultations that were conducted via the system to understand the deployment and service delivery processes of a representative telemedicine platform in China. METHODS: We collected information on remote consultations conducted from 2015 to 2020 via the regional telemedicine platform that employs a centralized architectural system model. We used graphs and statistical methods to describe the changing trends of service volume of remote consultation, geographical and demographic distribution of patients, and waiting time and duration of consultations. The factors that affect consultation duration and patient referral were analyzed by multivariable linear regression models and binary logistic regression models, respectively. The attitudes toward telemedicine of 225 medical practitioners and 225 patients were collected using the snowball sampling method. RESULTS: The regional telemedicine platform covers all levels of medical institutions and hospitals in all 18 cities of Henan Province as well as some interprovince hospitals. From 2015 to 2020, 103,957 remote medical consultations were conducted via the platform with an annual increasing rate of 0.64%. A total of 86.64% (90,069/103,957) of medical institutions (as clients) that applied for remote consultations were tier 1 or 2 and from less-developed regions; 65.65% (68,243/103,945) of patients who applied for remote consultations were aged over 50 years. The numbers of consultations were high for departments focusing in the treatment of chronic diseases such as neurology, respiratory medicine, and oncology. The invited experts were mainly experienced doctors with senior professional titles. Year of consultation, tier of hospital, consultation department, and necessity of patient referral were the main factors affecting the duration of consultations. In surveys, we found that 60.4% (136/225) of medical practitioners and 53.8% (121/225) of patients had high satisfaction and believed that telemedicine is of vital importance for the treatment of illness. CONCLUSIONS: The development of telemedicine in China shows a growing trend and provides great benefits especially to medical institutions located in less developed regions and senior citizens who have less mobility. Cases of remote consultations are mainly for chronic diseases. At present, the importance and necessity of telemedicine are well recognized by both patients and medical practitioners. However, the waiting time needs to be further reduced to improve the efficiency of remote medical services.

Effectiveness of a Cloud-Based Telepathology System in China: Large-Sample Observational Study.

BACKGROUND: Whole-slide imaging allows the entire slide to be viewed in a manner that simulates microscopy; therefore, it is widely used in telepathology. However, managing the large digital files needed for whole-slide imaging is difficult. To solve this problem, we set up the Chinese National Cloud-Based Telepathology System (CNCTPS). CNCTPS has been running for more than 4 years and has accumulated a large amount of data. OBJECTIVE: The main purpose of this study was to comprehensively evaluate the effectiveness of the CNCTPS based on a large sample. The evaluation indicators included service volume, turnaround time, diagnosis accuracy, and economic benefits. METHODS: Details of 23,167 cases submitted to the CNCTPS from January 2016 to December 2019 were collected to analyze the service volume, turnaround time, and economic benefits. A total of 564 patients who visited the First Affiliated Hospital of Zhengzhou University and obtained final diagnoses were followed up to analyze the diagnostic accuracy of the CNCTPS. RESULTS: From 2016 to 2019, the service volume of the CNCTPS increased from 2335 to 9240, and the number of participating hospitals increased from 60 to 74. Consultation requests from county-level hospitals accounted for 86.57% (20,287/23,167). A total of 17,495 of 23,167 cases (75.52%) were confirmed, including 12,088 benign lesions, 5217 malignant lesions, and 190 borderline lesions. Of the cases, 3.85% (893/23,167) failed to be diagnosed for reasons such as poor slice quality and incomplete sampling. The median turnaround time was 16.93 hours and was shortened yearly (between 2018 and 2019: adjusted P=.01; other groups: adjusted P<.001); 82.88% cases were diagnosed in 48 hours. There was a discrepancy between the diagnosis and final diagnosis for 11 cases, including 4 false-positive cases and 7 false-negative cases. The sensitivity and specificity were 97.66% and 98.49%, respectively. The diagnostic accuracy of the system was 98.05%, with no statistical difference from the final diagnosis in the hospital (P=.55). By using this system, a total of US $300,000 was saved for patients every year. CONCLUSIONS: The novel cloud-based telepathology system has the potential to relieve the shortage of pathologists in primary hospitals. It can also simultaneously reduce medical costs for patients in China. It should, therefore, be further promoted to enhance the efficiency, quantity, and quality of telepathology diagnoses.

Design and comparison of scheduling strategy for teleconsultation.

BACKGROUND: Telemedicine is playing an increasingly more important role in disease diagnosis and treatment. The market of telemedicine application is continuously promoted, thus bringing some issues on telemedicine operations management. OBJECTIVE: We aimed to compare the teleconsultation scheduling performance of newly designed proactive strategy and existing static strategy and explore the decision-making under different conditions. METHODS: We developed a discrete-event simulation model based on practical investigation to describe the existing static scheduling strategy of teleconsultation. The static strategy model was verified by comparing it with the historical data. Then a new proactive strategy was proposed, whose average waiting time, variance of waiting time and completed numbers were compared with the static strategy. RESULTS: The analysis indicated that the proactive strategy performed better than static under the current resource allocation. Furthermore, we explored the impact on the system of both strategies varying arrival rate and experts' shift time. CONCLUSIONS: Under different shift times and arrival rates, the managers of telemedicine center should select different strategy. The experts' shift time had a significant impact on all system performance indicators. Therefore, if managers wanted to improve the system performance to a greater extent, they needed to reduce the shift time as much as possible.

Involvement of long non-coding RNAs in the progression of esophageal cancer.

Esophageal cancer (EC) is one of the most common malignant tumors of the digestive system with high incidence and mortality rate worldwide. Therefore, exploring the pathogenesis of EC and searching for new targeted therapies are the current research hotspot for EC treatment. Long non-coding RNAs (lncRNAs) are endogenous RNAs with more than 200 nucleotides, but without protein-coding function. In recent years, lncRNAs have gradually become the focuses in the field of non-coding RNA. Some lncRNAs have been proved to be closely related to the pathogenesis of EC. Many lncRNAs are abnormally expressed in EC and participate in many biological processes including cell proliferation, apoptosis, and metastasis by inhibiting or promoting target gene expression. LncRNAs can also regulate the progression of EC through epithelial-mesenchymal transformation (EMT), which is closely related to the occurrence, development, and prognosis of EC. In this article, we review and discuss the involvement of lncRNAs in the progression of EC.

A Security Awareness and Protection System for 5G Smart Healthcare Based on Zero-Trust Architecture.

The key features of 5G network (i.e., high bandwidth, low latency, and high concurrency) along with the capability of supporting big data platforms with high mobility make it valuable in coping with emerging medical needs, such as COVID-19 and future healthcare challenges. However, enforcing the security aspect of a 5G-based smart healthcare system that hosts critical data and services is becoming more urgent and critical. Passive security mechanisms (e.g., data encryption and isolation) used in legacy medical platforms cannot provide sufficient protection for a healthcare system that is deployed in a distributed manner and fail to meet the need for data/service sharing across "cloud-edge-terminal" in the 5G era. In this article, we propose a security awareness and protection system that leverages zero-trust architecture for a 5G-based smart medical platform. Driven by the four key dimensions of 5G smart healthcare including "subject" (i.e., users, terminals, and applications), "object" (i.e., data, platforms, and services), "behavior," and "environment," our system constructs trustable dynamic access control models and achieves real-time network security situational awareness, continuous identity authentication, analysis of access behavior, and fine-grained access control. The proposed security system is implemented and tested thoroughly at industrial-grade, which proves that it satisfies the needs of active defense and end-to-end security enforcement of data, users, and services involved in a 5G-based smart medical system.

Identification of risk genes related to myocardial infarction and the construction of early SVM diagnostic model.

BACKGROUND: Myocardial Infarction (MI) is a fatal cardiovascular system disease. At present, the diagnosis of MI patients is mainly based on the patient's clinical manifestations, dynamic changes in electrocardiogram (ECG), and changes in myocardial enzymes. ECG is insufficient to diagnose an acute coronary syndrome or acute myocardial infarction, since ST-segment deviation might be also present in other conditions, such as acute pericarditis and early repolarization patterns. Given the low specificity and effectiveness of the current diagnostic strategies, an accurate diagnostic approach based on the level of gene expression is urgently needed in the clinic. METHODS AND RESULTS: We compared the gene's expression between MI patients and normal samples. The RNAseq data were downloaded from the GEO database. Differentially expressed genes underwent a feature selection process, and the signatures were selected to train a machine-learning model. In this study, we identified the risk genes associated with MI as signatures and uses the SVM to establish a diagnostic model. The accuracy of the model on discovery data is 0.87, which significantly improves the diagnostic efficiency of early detection of MI patients (MIPs). Two independent datasets were applied to verify the diagnostic model. Our model can effectively distinguish the control group from the disease group. CONCLUSIONS: We used risk genes to construct a diagnostic model for MI diagnosis, which can effectively distinguish MIPs from normal samples in the both of the discovery data and validation data. In the validation data, we found that percutaneous coronary intervention could indeed reverse MI to a certain extent, and the gene expression level of patients treated with percutaneous coronary intervention (PCI) was closer to the normal state.

Implementation and Application of Telemedicine in China: Cross-Sectional Study.

BACKGROUND: Telemedicine has been used widely in China and has benefited a large number of patients, but little is known about the overall development of telemedicine. OBJECTIVE: The aim of this study was to perform a national survey to identify the overall implementation and application of telemedicine in Chinese tertiary hospitals and provide a scientific basis for the successful expansion of telemedicine in the future. METHODS: The method of probability proportionate to size sampling was adopted to collect data from 161 tertiary hospitals in 29 provinces, autonomous regions, and municipalities. Charts and statistical tests were applied to compare the development of telemedicine, including management, network, data storage, software and hardware equipment, and application of telemedicine. Ordinal logistic regression was used to analyze the relationship between these factors and telemedicine service effect. RESULTS: Approximately 93.8% (151/161) of the tertiary hospitals carried out telemedicine services in business-to-business mode. The most widely used type of telemedicine network was the virtual private network with a usage rate of 55.3% (89/161). Only a few tertiary hospitals did not establish data security and cybersecurity measures. Of the 161 hospitals that took part in the survey, 100 (62.1%) conducted remote videoconferencing supported by hardware instead of software. The top 5 telemedicine services implemented in the hospitals were teleconsultation, remote education, telediagnosis of medical images, tele-electrocardiography, and telepathology, with coverage rates of 86.3% (139/161), 57.1% (92/161), 49.7% (80/161), 37.9% (61/161), and 33.5% (54/161), respectively. The average annual service volume of teleconsultation reached 714 cases per hospital. Teleconsultation and telediagnosis were the core charging services. Multivariate analysis indicated that the adoption of direct-to-consumer mode (P=.003), support from scientific research funds (P=.01), charging for services (P<.001), number of medical professionals (P=.04), network type (P=.02), sharing data with other hospitals (P=.04), and expertise level (P=.03) were related to the effect of teleconsultation. Direct-to-consumer mode (P=.01), research funding (P=.01), charging for services (P=.01), establishment of professional management departments (P=.04), and 15 or more instances of remote education every month (P=.01) were found to significantly influence the effect of remote education. CONCLUSIONS: A variety of telemedicine services have been implemented in tertiary hospitals in China with a promising prospect, but the sustainability and further standardization of telemedicine in China are still far from accomplished.

Impact of the Internet on Medical Decisions of Chinese Adults: Longitudinal Data Analysis.

BACKGROUND: The internet has caused the explosive growth of medical information and has greatly improved the availability of medical knowledge. This makes the internet one of the main ways for residents to obtain medical information and knowledge before seeking medical treatment. However, little has been researched on how the internet affects medical decisions. OBJECTIVE: The purpose of this study was to explore the associations between internet behaviors and medical decisions among Chinese adults aged 18 or over, including whether to go to the hospital and which level of medical institution to choose. METHODS: With the adult residents (≥18 years old) in 12 regions including urban and rural areas taken as the research objects, the differences in medical choices of adults with various characteristics were analyzed, and generalized linear mixed models were adopted to analyze the longitudinal data of the China Health Nutrition Survey from 2006 to 2015. RESULTS: Adult groups with different ages, genders, education levels, regions, places of residence, severities of illness and injury, years of suffering from hypertension, and history of chronic diseases showed diverse medical decisions, and the differences were statistically significant (P<.05). After controlling for these potential confounding factors and taking self-care as the reference, the probability of Chinese adults who participated in online browsing activities selecting hospital care was 0.82 (95% CI 0.69-0.98; P=.03) times that of residents who did not participate in online browsing activities. In terms of medical institution choices, adults who participated in online browsing activities were 1.86 (95% CI 1.35-2.58; P<.001) times more likely to opt for municipal medical treatment than primary care. However, the effect of online browsing on the selection probability of county-level hospitals was not significant compared with primary hospitals (P=.59). Robust analysis verified that accessing the internet had a similar effect on Chinese adults' medical decisions. CONCLUSIONS: Chinese adults who use the internet are a little less likely to go to the hospital than self-care. The internet has broken down the barriers to obtain knowledge of common diseases and thus has a slight substitution effect of self-care on hospital care. Internet use may increase the probability of adults going to municipal hospitals. The rising tendency of visiting high-level medical institutions may be consequently exacerbated due to knowledge monopoly of severe and complicated diseases that is difficult to eliminate, and the increase in inconsistent and incomplete medical information online will blur the residents' cognitive boundary of common diseases and severe diseases. Exploring the substantive impact of the internet on medical decision making is of great significance for further rational planning and utilization of the internet, in order to guide patients to appropriate medical institution.

Epidemic features of coronavirus disease 2019 in Henan Province. / 河南省2019å† çŠ¶ç— æ¯’ç— ç–«æƒ æµè¡Œç‰¹å¾åˆ†æž.

OBJECTIVES: To analyze the regional epidemic features of coronavirus disease 2019 (COVID-19) in Henan Province, China. METHODS: According to the data of COVID-19 patients and the resident population at the end of 2018 in Henan Province, statistical description and analysis of epidemiological characteristics of COVID-19 in Henan Province were conducted, including the time distribution, population distribution, and regional distribution. RESULTS: The cumulative incidence of COVID-19 in Henan Province was 1.32/100 000, the cure rate was 98.03%, and the fatality rate was 1.73% by March 9, 2020. The incidence curve showed that the epidemic peak reached from January 24 to January 28. The high-incidence area was Xinyang, with a standardized cumulative incidence rate of 4.36/100 000. There were 580 female COVID-19 patients (45.60%), 688 males (54.09%) in Henan Province. The incidence of males was 1.41/100 000, while the incidence of females was 1.23/100 000. The age with the highest incidence of COVID-19 in Henan Province was 20-69 years old (88.68%). The incidence rate was highest in men aged 30-39 (2.51/ 100 000), while the lowest rate in women aged 0-9 (0.16/100 000). There were 1 225 local patients (96.31%), and the rural patients (45.73%) were slightly higher than the urban patients (44.02%) in Henan Province. A total of 63.60% patients had traveled or lived in Hubei or contacted with people who came from Hubei to Henan. The proportion of patients whose family members suffered from COVID-19 was 32.70%. Global spatial autocorrelation analysis suggested that there was a statistically significant positive correlation in the spatial distribution of COVID-19 patients in Henan Province (Moran's I=0.248, Z=2.955, P<0.01). CONCLUSIONS: There are differences in the morbidity and mortality of COVID-19 patients in different areas of Henan Province, with epidemic peak reaching from January 24 to January 28. Henan is dominated by local patients, male patients, and patients with contact history in Hubei. The space appears to be moderately clustered.

Research on Teleconsultation service quality based on multi-granularity linguistic information: the perspective of regional doctors.

BACKGROUND: Due to the increasing complexity in socioeconomic environments and the ambiguity in human cognition, decision makers prefer to give linguistic cognitive information with different granularities according to their own preferences. Consequently, to consider the uncertainty and preferences in the evaluation process, a method based on Multi-Granularity Linguistic Information (MGLI) for evaluating teleconsultation service quality is proposed, which provides a new research direction for scientific evaluation and improvement of teleconsultation service quality. METHODS: Firstly, this paper explored a service quality evaluation system from the perspective of regional doctors. And then considering the uncertainty and preferences of decision makers, MGLI was used to optimize the index system according to the similarity degree between the linguistic evaluation information and a given linguistic term set. Finally, the empirical research was conducted using Henan Province Telemedicine Center of China (HTCC) as an example to identify the direction for improving the service quality in teleconsultation. RESULTS: This study found that the number of consulting rooms, attitude of operators, consultation duration, charges, and attitude of experts are the key factors affecting the quality of teleconsultation service. CONCLUSIONS: Suggestions for improving the quality of teleconsultation service are put forward in terms of optimizing the allocation of consulting rooms, improving regional doctors' experience and standardizing charging standards, which provides a new direction for improving the quality of teleconsultation service.

The Application of Mobile Telehealth System to Facilitate Patient Information Presentation and Case Discussion.

Background: Most secondary transmission of COVID-19 is occurring in a hospital setting. To decrease person-to-person contact, health care providers have built many isolation wards. However, out-of-hospital professionals cannot access patient information, which has greatly reduced the efficiency of treatment; it is inconvenient for health care professionals to issue a case discussion with professionals from other wards. This article mainly introduces a mobile telehealth system (MTS) applied to facilitate patient information presentation and case discussion. Materials and Methods: The MTS searches patient information, which is stored in hospital intranet, and uses five modules to display patient information. By a request/response module and a real-time interaction module, we successfully conducted case discussions. In addition, we took measures in three areas to prevent patient information leakage. Results: The system uses mobile collaboration technology to present patient information and support case discussion. MTS was officially launched for 37 days, during which it has been used 3,061 times. Conclusions: The building of the MTS not only provides convenience and benefit for health care professionals, but also reduces person-to-person contact.