The national policy on high-quality development of hospitals proposes to strengthen information technology support and actively promote the multi-disciplinary team (MDT) model. How to use the “Internet Plus” technology and operation mode to promote MDT communication and improve the efficiency of diagnosis and treatment in the digital and intelligent information age is a direction worthy of attention and research. This paper systematically reviews the current development status of MDT informatization construction at home and abroad. Based on the current challenges and opportunities, it makes prospects for the future development of MDT informatization construction from the aspects of strengthening the digital and intelligent support of MDT operation, connecting MDT “information silos”, and deepening the construction of MDT supervision and effect evaluation system, etc.
ObjectiveTo explore the development and application of a novel ventilator alarm management model in critically ill patients receiving invasive mechanical ventilation (MV) in the intensive care unit (ICU) using machine learning (ML) and Internet of Medical Things (IoMT). The study aims to identify alarms’ intervention requirements. MethodsA retrospective cohort study and ML analysis were conducted, including adult patients receiving invasive MV in the ICU at West China Hospital from February 10, 2024, to July 22, 2024. A total of 76 ventilator alarm-related parameters were collected through the IoMT system. Feature selection was performed using a stratified approach, and six ML algorithms were applied: Gaussian Naive Bayes, K-Nearest Neighbors, Linear Discriminant Analysis, Support Vector Machine, Categorical Boosting (CatBoost), and Logistic Regression. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC-ROC). ResultsA total of 107 patients and their associated ventilator alarm records were included. Thirteen highly relevant features were selected from the 76 parameters for model training through stratified feature selection. The CatBoost model demonstrated the best predictive performance, with an AUC-ROC of 0.984 7 and an accuracy of 0.912 3 in the training set. External validation of the CatBoost model yielded an AUC-ROC of 0.805 4. ConclusionThe CatBoost-based ML model successfully constructed in this study has high accuracy and reliability in predicting the ventilator alarms in ICU patients, providing an effective tool for ventilator alarm management. The CatBoost-based ML method exhibited remarkable efficacy in predicting the necessity of ventilator intervention in critically ill ICU patients. Further large-scale multicenter studies are recommended to validate its clinical application value and promote model optimization and implementation.
Objective To explore the construction and application of a new follow-up visit model in the context of Internet hospital consultation, aiming to create a novel follow-up visit model that integrates precise identification of follow-up patients, messages of follow-up reminders, online free follow-up visits, and promotional activities. Methods Satisfaction surveys were conducted among outpatient patients and doctors at Jintang County First People’s Hospital from July 2023 to June 2024. Patients and doctors were divided into two groups based on whether the online free follow-up visit program had been implemented: the pre-implementation group (July to December 2023) and the post-implementation group (January to June 2024). The satisfaction levels of patients and doctors before and after the implementation were compared and analyzed. Results A total of 17 831 patient visits and 801 doctor visits were included. Since its launch, WeChat messages had been pushed to all outpatient patients, and both WeChat and SMS messages had been pushed to patients in surgical departments. The average waiting time for outpatient visits in January-June 2024 was shortened by 2 minutes compared with the same period last year (January-June 2023). The hospital’s Case Mix Index increased by 3.7%, and the surgical volume increased by 7.5%. After the launch of the Internet hospital, both patient and doctor satisfaction improved. Conclusion The new follow-up visit model of the Internet hospital represents an important initiative in the digital transformation of hospitals and holds value and significance for promotion in more county-level medical institutions.
The paper summarizes three revolution trends of medical service mode in the age of 5th generation mobile networks (5G), including artificial intelligence & intelligent medical service, internet of things & internet hospital, and intelligent hospital. Artificial intelligence & intelligent medical service mainly covers artificial-intelligence-assisted diagnosis, artificial-intelligence medical decision-making, and artificial-intelligence-assisted new drug research & development. Internet of things & internet hospital mainly covers internet hospitals, internet care, cloud pharmacies, and medical imaging clouds. Intelligent hospitals mainly cover intelligent clinics, intelligent wards, and intelligent management. The revolution trends count on not only techniques such as 5G, but also the support and cooperation of the government and society. The risk of information and data leak needs attention.
Chronic kidney disease (CKD) has become a global public health problem because of its high prevalence, low awareness, poor prognosis, and high medical costs. Effective follow-up management can facilitate timely adjustment of the treatment of the CKD patients and delay the disease progression. The application of internet of things (IoT) technology in dynamic monitoring and telemedicine is helpful for the self-management of patients with chronic diseases, and can provide convenient, intelligent, and humanized medical and health services. In the future, with the rapid growth of demands of CKD management and innovations in information technology, new medical IoT industry will accelerate the intelligent development of CKD management. Multi-disciplinary and multi-industrial collaboration should be promoted to solve current challenges, such as evaluation of actual effectiveness, the system design and construction, and the accessibility of intelligent healthcare services, to ensure that IoT products can improve clinical outcomes, reduce medical expenditure, and lower disease burden.
ObjectiveTo systematically review the incidence of internet addiction disorder among college students in China.MethodsPubMed, EMbase, VIP, WanFang Data and CNKI databases were electronically searched to collect cross-sectional studies on incidence rate of college students’ internet addiction in China from inception to February 2020. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, then, meta-analysis was performed by Stata 16.0 software.ResultsA total of 65 cross-sectional studies involving 87 702 subjects were included. The results of meta-analysis showed that: the overall incidence of college students’ internet addiction in China was 10.7% (95%CI 9.6% to 11.8%). The incidence of internet addiction from 2011 to 2018 (11.7%, 95%CI 10.2% to 13.2%) was higher than that from 2005 to 2010 (9.6%, 95%CI 8.1% to 11.1%). The incidence in male students (14.6%, 95%CI 13.1% to 16.0%) was higher than that in female students (6.9%, 95%CI 5.9% to 7.8%). The incidence of urban students (12.2%, 95%CI 9.3% to 15.2%) was higher than that of rural students (9.0%, 95%CI 7.3% to 10.6%). The incidence of students who were not satisfied with their major (16.2%, 95%CI 5.5% to 26.8%) was higher than that of satisfied (5.0%, 95%CI 1.3% to 8.8%). The incidence of students with poor academic performance (29.4%, 95%CI 11.9% to 47%) was higher than of excellent academic performance (4.1%, 95%CI 1.9% to 6.4%).ConclusionsThe incidence rate of internet addiction among college students in China shows an obvious upward trend. There are differences in the incidence rates of internet addiction among college students in different regions. The incidence rates of internet addiction are different among different genders, degree of satisfaction with their majors and academic achievements.
Objective To explore the influencing factors of internet game addiction among middle school students. Methods Students from a certain district in Sichuan between September 2022 and March 2023 were included as participants. Basic information such as gender, age, whether the subjects were only children, place of residence, parental education, and subjective economic status were investigated. The nine-item Internet Gaming Disorder Scale-short form was used to investigate whether participants had internet game addiction, and the Berkman-Syme Social Network Index was used to evaluate the participants’ social level. Multiple linear regression analysis was used to conduct multivariate analysis to explore the influencing factors of internet game addiction. Results A total of 594 questionnaires were distributed, and 592 valid questionnaires were ultimately obtained. The detection rate of internet game addiction was 12.0%. Multiple linear regression analysis showed that gender (t=?8.281, P<0.001), age (t=3.211, P=0.001), subjective economic status in the region (t=2.025, P=0.043), and social level (t=?4.239, P<0.001) were the influencing factors of online game addiction. Due to the P value was close to the set test level (0.05), subjective economic status in the region was not considered an influencing factor of internet game addiction. Conclusion Teenagers with male gender, older age, and lower social skills are more likely to develop addiction to internet games.
At present, the rapid integration and development of internet technology and medical services have made internet diagnosis and treatment an important part of medical services, and it is also an inevitable development trend of future diagnosis and treatment services. In order to meet the needs of patients for more timely, accurate and convenient medical treatment, West China Hospital of Sichuan University has innovated the internet diagnosis and treatment mode, adopted the innovative mode of diversified online services, pre-treatment mode, expert team mode, specialized medical consortium platform and whole process management, optimized medical resources and structure, promoted regional medical association linkage, and improved patients’ medical experience. The West China Internet Hospital of Sichuan University takes the whole process ecological closed-loop of “medical+health” as the goal, has greatly improved the efficiency and quality of diagnosis and treatment, which is of great significance for the positioning and development of internet hospital. This article will share the construction experience of West China Internet Hospital of Sichuan University.
Basing on the internet education implemented during China’s fighting against the outbreak of coronavirus disease 2019, and combining with literature review and personal experience in internet teaching, the paper puts forward 10 suggestions from the perspective of problem-analysis, including policy guidance, enhancement of hardware and software capacities, teacher talent teams, diversity of education and teaching, standardization and normalization, integration of quality resources, examination system, supporting industry, exchange and cooperation, and network information security education, to further strengthen the construction and development of internet education in China.
ObjectiveTo summarize the experience of earthquake rescue with the help of wise information technology.MethodsThe Jiuzhaigou earthquake of magnitude 7.0 occurred at 21:19 on August 8th 2017. Three hours and 38 minutes after the earthquake, a triad model of remote consultation, mobile video consultation and mobile text consultation was established to assist the earthquake rescue based on the mobile on-line medical consultation application and telemedicine center in West China Hospital. Patients classification, primary diagnosis, psychological counseling, victims searching were done by this novel rescue model.ResultWithin 72 hours after the earthquake, there were 114 doctors taking part in the earthquake rescue, including 4 remote consultations (hospital to hospital), 7 video consultations (doctor to victim), 487 mobile text consultations (doctor to victim), and 32 cases of which were highly relative to earthquake rescue, including one case of positioning for victim-searching.ConclusionThe triad model of earhquake rescue which was first initiated by West China Hospital played an important role in assisting earthquake rescue and achieved good results.
