Objective To preliminarily assess the ameliorative effect of Mom’s Good Mood (MGM) on the prevalence of antenatal depression based on a pilot study, and to provide evidence for a scale-up study. Methods This study was conducted in Ma’anshan Maternal and Child Health Center as a pilot study of an implementation study conducted in China called the Perinatal Depression Screening and Management (PDSM) program. In 2019, 1 189 participants (gestational week ≤14+6 weeks) were included in the implementation group. Females were recruited in the first trimester and followed up in the second and third trimesters. At each time point, the participants’ depression status was screened by the Edinburgh postpartum depression scale (EPDS), and those who were screened as having depression were provided the MGM intervention. In 2020, 1 708 participants who underwent screening with the EPDS in either the first, second or third trimester at Ma’anshan Maternal and Child Health Center were included in the control group. Mann‒Whitney U test, Chi-square, and multivariate logistic regression analysis were used to compare the EPDS scores and depression prevalence between the control and implementation groups to assess the ameliorative effect of MGM (screening and intervention) on antenatal depression. Results In the first trimester, there were no statistically significant differences in EPDS scores or depression prevalence between the two groups (P>0.05). In the second and third trimesters, both the EPDS scores and depression prevalence of the implementation group were lower than those of the control group (P<0.05). After adjusting for confounders, logistic regression analysis showed that the risks of depression in the implementation group in both the second and third trimesters were lower than those in the control group (ORsecond trimester=0.55, 95%CI 0.37 to 0.81, P=0.003; ORthird trimester=0.51, 95%CI 0.35 to 0.74, P<0.001). Conclusion Implementation of the MGM based on the primary care system can effectively reduce the prevalence of antenatal depression, providing evidence for further scale up.
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.
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)
Internet of Things (IoT) technology plays an important role in smart healthcare. This paper discusses IoT solution for emergency medical devices in hospitals. Based on the cloud-edge-device architecture, different medical devices were connected; Streaming data were parsed, distributed, and computed at the edge nodes; Data were stored, analyzed and visualized in the cloud nodes. The IoT system has been working steadily for nearly 20 months since it run in the emergency department in January 2021. Through preliminary analysis with collected data, IoT performance testing and development of early warning model, the feasibility and reliability of the in-hospital emergency medical devices IoT was verified, which can collect data for a long time on a large scale and support the development and deployment of machine learning models. The paper ends with an outlook on medical device data exchange and wireless transmission in the IoT of emergency medical devices, the connection of emergency equipment inside and outside the hospital, and the next step of analyzing IoT data to develop emergency intelligent IoT applications.
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.
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.
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.
目的 为避免选择和发表偏倚,系统评价者应采用多种查询技术,并尽力获得未发表的研究.本文试图探讨,英特网检索对鉴定未发表和正在进行的临床试验是否有用.研究设计 利用七个Cochrane系统评价的查询策略回顾性地在英特网上检索未纳入的随机对照试验.方法 检索策略 以普通检索式"研究方法学 NEAR干预措施NERA 条件"、用AltaVista在英特网上搜索.测量指标包括搜索时间、英特网搜索已发表研究的回溯率、精确度(已发表和未发表的随机临床试验链接的网页比例)、英特网检索到的未纳入的未发表和正在进行的研究数.结果 用21小时查询了429个网页,找到14个链接到未发表的、正在进行的或最近完成的试验,至少有9个与4篇系统评价相关.英特网检索已发表研究文献的回溯率在0～43.6%,其链接已发表和未发表研究的精确度在0～20.2%.结论 未发表尤其是正在进行的试验的信息可在英特网上找到.潜在的问题是如何评价未经同行评审的电子出版物的质量.急需更强的搜索工具.建议用"Open Trial Initiative"定义英特网发表试验的语法,以加强试验登记的共同操作性.因此,专门的搜索引擎可找到更多有关正在进行和已完成的临床试验信息.
The intensive care unit (ICU) is a highly equipment-intensive area with a wide variety of medical devices, and the accuracy and timeliness of medical equipment data collection are highly demanded. The integration of the Internet of Things (IoT) into ICU medical devices is of great significance for enhancing the quality of medical care and nursing, as well as for the advancement of digital and intelligent ICUs. This study focuses on the construction of the IOT for ICU medical devices and proposes innovative solutions, including the overall architecture design, devices connection, data collection, data standardization, platform construction and application implementation. The overall architecture was designed according to the perception layer, network layer, platform layer and application layer; three modes of device connection and data acquisition were proposed; data standardization based on Integrating the Healthcare Enterprise-Patient Care Device (IHE-PCD) was proposed. This study was practically verified in the Chinese People’s Liberation Army General Hospital, a total of 122 devices in four ICU wards were connected to the IoT, storing 21.76 billion data items, with a data volume of 12.5 TB, which solved the problem of difficult systematic medical equipment data collection and data integration in ICUs. The remarkable results achieved proved the feasibility and reliability of this study. The research results of this paper provide a solution reference for the construction of hospital ICU IoT, offer more abundant data for medical big data analysis research, which can support the improvement of ICU medical services and promote the development of ICU to digitalization and intelligence.
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.