Regional Medical Resources Research Articles

Challenges and opportunities in the development of telesurgery

Telesurgery, which utilizes remote communication technology and surgical robots for operations, is an emerging method that breaks the constraints of space on surgical procedures and is an important development direction for future surgery. With a vast territory, telesurgery has the potential to become a candidate method to improve the uneven distribution of regional medical resources. In recent years, with the development and maturity of China's domestic surgical robot technology and communication technology, China has made rapid progress in the field of telesurgery, but is still in the primary stage of development, facing many challenges and also taking advantage of opportunities. The next 20 years will be a golden opportunity for the development of telesurgery worldwide, and it is a hopeful view that Chinese surgeons will seize the opportunity and face the challenges to lead the development of telesurgery.

Research on care preferences for the elderly and influencing factors in Zhejiang Province: A statistical and geographical approach.

The aging of the population is becoming an increasingly severe issue. How can we develop caring services for the elderly and promote healthy aging? Investigating care preferences is an essential step in addressing this issue. A self-designed questionnaire was employed to collect data online. The impact of personal circumstances on care preferences was ascertained using the chi-squared test and multivariate logistic regression. An optimal parameters-based geographical detector was introduced to examine the influence of spatially heterogeneous regional factors on care preferences. The online survey produced 1178 valid questionnaires. Home-based elderly care was the preference of 91.9% of respondents, followed by community-based care and medical-nursing care; institutional care was the least preferred alternative. Age, education, living style, and health states of the elderly significantly influenced the preferred care option. When compared to home-based elderly care, older respondents (odds ratio [OR] = 3.776) preferred institutional care, highly educated respondents preferred community-based care (higher education: OR = 5.206; secondary education: OR = 3.049) and medical-nursing care (higher education: OR = 4.484); the elderly living alone (OR = 0.101) excluded institutional care, and the elderly living with their children excluded non-family care method of institutional care (OR = 0.031) and medical-nursing care (OR = 0.391). Regional medical resources and old-age security significantly affect the preferences of the elderly (q-statistic [q] > 0.5); local economic development significantly affects community-based care (q > 0.6); the availability of financial subsidies significantly affects home-based care and medical-nursing care (q > 0.9); and the availability of institutional resources significantly affects the preference for institutional care (q > 0.8). We found that it is necessary to improve the level of medical care given by non-family members and care facilities, vigorously develop new methods of elderly care, promote humanistic care in non-family care settings, and increase available regional medical resources, financial subsidies, and social security. This study integrates economic and social perspectives to examine and analyze retirement willingness, thereby broadening the scope of social surveys and research methodologies, and offering valuable insights with potential directive implications.

Telehealth Use Across Time and Regional Medical Resources During the COVID-19 Pandemic: Evidence from China.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has created lots of difficulties for individuals to seek medical help offline. Telehealth is considered as a potential approach to solve this issue. During the COVID-19 pandemic, although the use of telehealth has increased in the short term, it still remains unknown whether the use of telehealth can maintain a high level of development in the long term. The purpose of this article is to investigate the impact of COVID-19 pandemic on telehealth use across time and regional medical resources. Materials and Methods: Our research used the Internet search index from Baidu Index Platform in 31 provinces of China as the proxy of telehealth use. A total of 2,119,486 times of searching behaviors from January 2018 to December 2021 are included in our dataset. Changing plots, the method of analysis of variance and empirical models are applied to reveal the relationship between COVID-19 pandemic and telehealth use. Results: Baidu Index counts increased (p < 0.01) at the beginning of COVID-19 pandemic (2020) but started to decline (p < 0.01) during the period of regular epidemic prevention and control (2021). Moreover, the counts of Baidu Index in regions with rich medical resources are higher than those in other regions in 2020. Comparing Baidu Index counts in 2020, the COVID-19 pandemic has higher positive effects on telehealth use during the period of 2021 in regions with average and poor medical resources. Conclusions: COVID-19 pandemic has a positive effect on telehealth use in 2020 but has a negative effect in 2021. During the epidemic, telehealth use differs in regions with rich, average, and poor medical resources. Our findings indicate that the use of telehealth should be promoted with different measures in regions with different medical resources, thereby contributing its healthy development in the long term.

Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China.

Previous Studies, such as the evaluation of the supply of and demand for regional medical resources and carrying capacity assessments, require further development. This paper aims to evaluate the carrying capacity and spatial distribution of medical resources in Shenzhen from the perspective of supply and demand, and to conduct a time-series variation of the coupling coordination degree from 1986 to 2019. The two-step floating catchment area method was employed to quantify the carrying capacity and coupling coordination degree method and spatial autocorrelation analysis were applied to analyze spatial distribution between supply and demand. The results were as follows. (1) The carrying capacity index in more than 50% of the districts was classified as low-grade. The percentage of regions with good grades was 8.27%. The regions with a high carrying capacity were distributed in the central and southeastern areas. (2) The coupling coordination continued to rise, increasing from 0.03397 in 1986 to 0.33627 in 2019. (3) The level of supply and demand for medical resources in Shenzhen increased from 1986 to 2019, and the highest degree of compatibility between the supply and the population size was largely concentrated in the western and eastern regions. This research can provide a theoretical reference for Shenzhen to rationally plan medical resources and improve the carrying capacity of medical resources.

Predicting the Travel Distance of Patients to Access Healthcare Using Deep Neural Networks.

Objective: Improving geographical access remains a key issue in determining the sufficiency of regional medical resources during health policy design. However, patient choices can be the result of the complex interactivity of various factors. The aim of this study is to propose a deep neural network approach to model the complex decision of patient choice in travel distance to access care, which is an important indicator for policymaking in allocating resources. Method: We used the 4-year nationwide insurance data of Taiwan and accumulated the possible features discussed in earlier literature. This study proposes the use of a convolutional neural network (CNN)-based framework to make predictions. The model performance was tested against other machine learning methods. The proposed framework was further interpreted using Integrated Gradients (IG) to analyze the feature weights. Results: We successfully demonstrated the effectiveness of using a CNN-based framework to predict the travel distance of patients, achieving an accuracy of 0.968, AUC of 0.969, sensitivity of 0.960, and specificity of 0.989. The CNN-based framework outperformed all other methods. In this research, the IG weights are potentially explainable; however, the relationship does not correspond to known indicators in public health. Conclusions: Our results demonstrate the feasibility of the deep learning-based travel distance prediction model. It has the potential to guide policymaking in resource allocation. Clinical and Translational Impact Statement— Deep learning technology is feasible in investigating the distance that patients would travel while accessing care. It is a tool that integrates complex interactive variables with highly imbalanced data distributions.

The design of regional medical cloud computing information platform based on deep learning

In order to solve the imbalance of medical resources in different regions, a regional medical cloud computing information platform based on reactive algorithm is constructed. First, an application-oriented elastic scaling algorithm based on long short-term memory network and back propagation neural network (BPNN) is proposed. Then, based on cloud computing, a medical cloud data mining platform using Hadoop ecosystem is proposed. Finally, Visual Studio is used to develop regional medical cloud computing information platform, and the performance of the platform is tested. The experimental results show that the improved neural network algorithm has a loss and MAPE (mean absolute percentage error) value of 930 and 0.00031, respectively in the actual workload prediction, which is better than the algorithm before optimization. Moreover, it has the best fitting effect with the actual curve in the prediction of response time. In the strategy scheduling experiment, the loss of the model is 1.40222, the MAPE value is 0.34021, and the convergence time is 23 s, which is better than the test results of the model based on linear regression and BPNN. The experimental results suggest that the regional medical cloud computing information platform can solve the problem of unfair regional medical resources in the medical field to a certain extent.

Exploration and prospect of 5G application in telemedicine

The combination of network and medical field gave birth to telemedicine.The implementation of telemedicine can improve the uneven distribution of regional medical resources, reduce the working pressure of medical staff, shorten the distance between medical staff and patients and medical staff, and improve the timeliness of monitoring, diagnosis and treatment.The continuous development of telemedicine relies on the continuous innovation of network communication technology, the latest 5(th) generation wireless systems (5G) is bringing significant changes to mobile communication and other related industries by virtue of its advantages of high data rate and low latency. This paper reviews the development of telemedicine, introduces the characteristics of 5G technology, combines the research results of 5G technology applied in the medical field at home and abroad, and prospects the development of this field in the future.

Risk of preventable hospitalization before and after diagnosis among rheumatoid arthritis patients compared to non-rheumatoid arthritis controls.

The purpose of the study is to investigate the risk of preventable hospitalization among patients with rheumatoid arthritis (RA). We identified 11,852 incident RA patients and 59,260 age-, sex-, and index year-matched controls from the Taiwan National Health Insurance Database. Index date was the RA diagnosis date for cases, which was assigned to their matched controls. The odds ratios (OR) of preventable hospitalizations between RA patients and controls were estimated using a mixed effect model adjusted for age, sex, patient characteristics, Elixhauser comorbidity index, medical utilization and regional medical resources. The overall annualized incidence of preventable hospitalization in RA patients and controls was 38.7 vs. 20.9 events per 1,000 person-years (adjusted OR, 1.61; 95% confidence interval [CI], 1.51-1.71). The adjusted OR of preventable hospitalization in RA patients compared to matched controls was 1.17 (1.00-1.37) one year prior to RA diagnosis and remained elevated after RA diagnosis. Adjusted ORs (95% CI) for specific preventable hospitalization categories were 1.93 (1.58-2.36) for chronic obstructive pulmonary disease, 1.64 (1.21-2.21) for asthma, 1.95 (1.78-2.13) for bacterial pneumonia, and 1.59 (1.44-1.75) for urinary tract infection. When assessing the trend of individual preventable hospitalizations before and after diagnosis, bacterial pneumonia and urinary tract infection hospitalizations had a significantly higher OR in RA patients one year before diagnosis and five years afterward (adjusted OR ranges 2.75 to 4.48 and 1.83 to 3.07 respectively, all P-values<0.05) CONCLUSION: RA is independently associated with a higher risk of preventable hospitalization specifically for chronic lung diseases and infections.

Contributions of the medical alliance of northwest Guangxi hospitals in the health anti-poverty campaign

To implement the task of health anti-poverty campaign, the medical alliance of northwest Guangxi hospitals made full use of its synergy strengths to achieve remarkable progress in constructing a telemedicine cooperation network, nurturing medical discipline of primary hospitals in the alliance, promoting regional medical resources sharing, and improving the humanities connection mechanism. To further develop health anti-poverty via medical alliances, relevant institutions are recommended to probe into such problems as telemedicine compensation mechanism, precision-based disciplinary support, breakdown of resource sharing barriers and profit distribution mechanisms. Key words: Health resources; Medical alliance; Telemedicine; Health anti-poverty campaign; Hierarchical medical system

Spatial analysis of the distribution, risk factors and access to medical resources of patients with hepatitis B in Shenzhen, China.

Considering the high morbidity of hepatitis B in China, many epidemiological studies based on classic medical statistical analysis have been started but lack spatial information. However, spatial information such as the spatial distribution, autocorrelation and risk factors of the disease is of great help in studying patients with hepatitis B. This study examined 2851 cases of hepatitis B that were hospitalized in Shenzhen in 2010 and studied the spatial distribution, risk factors and spatial access to health services using spatial interpolation, Pearson correlation analysis and the improved two-step floating catchment area method. The results showed that the spatial distribution of hepatitis B, along with risk factors as well as spatial access to the regional medical resources, was uneven and mainly concentrated in the south and southwest of Shenzhen in 2010. In addition, the distribution characteristics of hepatitis B revealed a positive correlation between four types of service establishments and risk factors for the disease. The Pearson correlation coefficients are 0.566, 0.515, 0.626, 0.538 corresponding to bath centres, beauty salons, massage parlours and pedicure parlours (p < 0.05). Additionally, the allocation of medical resources for hepatitis B is adequate, as most patients could be treated at nearby hospitals.

Discussions on delivery mode of medical consortia within the ongoing health reform

A review of the development milestones of medical consortia during the 20th century in China,probed into the practice and strategy of medical consortia delivery modes.Such modes are designed to build an integrated regional medical resources and functions,create the delivery service chain to cater to primary medical demands in urban and rural areas,and meet China's present conditions.Author of the paper proposed better supporting policies and measures based on improving the basic strategy of the medical consortium's delivery mode. Key words: Medical service; Consortium; Delivery; Mode; Strategy

Review of Disaster Medicine and Regional Medical Resources after the Chi-Chi (Taiwan) Earthquake

Review of Disaster Medicine and Regional Medical Resources after the Chi-Chi (Taiwan) Earthquake