Objective
To find convenient methods for remote consultation of images of ocular fundus diseases.
Methods
A remote consultation system composed of internet was set up.The con sultation information,including images,words and figures,was published on intern et as web pages,so that the consultants would get the notice and the appointment by email.After reading the information on line,the consultants gave their opinions back to internet.
Results
The remote consultation system of images of ocular fundus diseases was setted up and managed successfully,and 23 patients had been diagnosed by this system.
Conclusion
The system which has clinical practicality is a simple,quick,effective and economic method for remote consultation of images of ocular fundus diseases.
(Chin J Ocul Fundus Dis, 2001,17:247-248)
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.
There are more than 6 800 urban public hospitals in China, which are the main subject of our country's medical service, but the process and efficiency need to be improved because of the siphon effect of resources and the limit of service scope. The use of internet thinking and technology will solve this problem effectively. Based on the fact, Deyang People's Hospital planned "internet+" system according to the requirement of the medical and health system reform, to solve the problems such as service efficiency, doctor-patient communication, multi-spot disciple, hierarchical medical system, delicacy management, etc. Through the concrete practice of elevating the efficiency of outpatient and emergency care services, it is recognized that the application of internet thinking and technology can not only accelerate the medical and health system reform, but also subvert the traditional medical pattern, integrate the regional medical resource, and enlarge the scope of medical services. It provides a sharp weapon to push forward the reform of urban public hospitals.
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.
Cohort study is the observational study with the highest strength of causality demonstration, which is often used to test the etiological hypothesis and determine the risk factors of diseases. However, it often takes a lot of manpower, material and financial resources to carry out a cohort study, and it is time-consuming. At the same time, due to the long follow-up time, it is difficult to maintain the compliance of the study population, which is prone to loss to follow-up bias. In recent years, driven by network technology, a new type of cohort study design, e-cohort study, has gradually emerged, which is based on the network to recruit participants, follow up and collect data. Taking advantage of the wide coverage and high flexibility of the network, it provides a new strategy for improving the recruitment speed, participant participation and compliance of cohort study. This article summarizes the development history, current status, key points of design and implementation, advantages and challenges of e-cohort study, so as to help researchers to fully understand and apply this study design to solve practical clinical problems.
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.
ObjectiveUse information technology to establish an “Internet+” chronic disease management model to provide patients with a full process, seamless, and convenient services. Explore a new model of “Internet+” chronic disease management and care services in the region. Methods Patients with chronic diseases treated in Mianyang Central Hospital from May 2018 to April 2019 were selected. The patients were randomly divided into intervention group and control group according to the single and even number at the end of hospitalization number. The control group adopted the traditional chronic disease management mode, and the intervention group adopted the “Internet+” chronic disease management mode based on the patients’ needs. And select the nursing experts who provide “Internet+” online nursing services. Compared with the effective management before and after the implementation of “Internet+” chronic disease management, the number of patients with chronic diseases, clinical outcome indicators, the number of health education readings, the number of Internet nursing services, and the sense of professional benefit of nurses and other indicators, etc. Results A total of 143 patients were included, including 78 in the control group and 65 in the intervention group. A total of 28 nursing experts were investigated. The effective management rate of patients with chronic diseases was 78.7%. The WeChat public account “Slow Disease Window” has read nearly 90 000 person-times, and the Internet Hospital “Nursing Professional Online” has nearly 2 000 online nursing services. After participating in “Internet+” chronic disease management, the disease activity and functional status of chronic disease patients were significantly improved (P<0.05). Nursing professionals have a strong sense of professional benefits (P<0.05). Conclusions With the development of “Internet+” chronic disease management, a new mode of chronic disease management was explored to promote the management of chronic disease more convenient and efficient, so that the health education work can be homogenized, the clinical outcome of the patients was effectively improved. At the same time the career planning of nursing staff can be broadened.
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 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.
