The impact of centralized band purchasing of pharmaceuticals on innovation of Chinese pharmaceutical firms: an empirical study based on double difference models.

In 2018, China began to gradually promote the pilot policy of centralized band purchasing of medicines. Implementing this policy has resulted in a significant decrease in drug prices. However, there needs to be a clear consensus on the impact and mechanism of action on the innovation of pharmaceutical companies. Therefore. Taking the data of Chinese Shanghai and Shenzhen A-share pharmaceutical listed companies from 2016 to 2022 as a sample, this paper empirically investigates the impact of the centralized banded purchasing policy of drugs on the innovation of pharmaceutical enterprises by using a double difference model and further analyzes the mechanism of its action. The results show that implementing the centralized banded purchasing policy can promote pharmaceutical enterprises' innovation input and output, which is robust under the parallel trend and placebo tests. Further exploring the impact mechanism of the centralized band purchasing policy on pharmaceutical enterprises' innovation, it can be found that it promotes innovation inputs through three channels: government subsidies, enterprise profits, and operating income. In addition, the impact of centralized band purchasing on enterprise innovation is heterogeneous in terms of region, enterprise nature, and scale. Therefore, the positive effects of the centralized band purchasing policy on promoting innovation in pharmaceutical enterprises should be fully recognized, and enterprise heterogeneity should be taken into account when implementing the policy. This study provides empirical evidence on the implementation effect of the centralized banded purchasing policy and provides lessons for continuously optimizing the policy to promote the high-quality development of pharmaceutical enterprises.

Impact Analysis of COVID-19 Pandemic on Hospital Reviews on Dianping Website in Shanghai, China: Empirical Study.

BACKGROUND: In the era of the internet, individuals have increasingly accustomed themselves to gathering necessary information and expressing their opinions on public web-based platforms. The health care sector is no exception, as these comments, to a certain extent, influence people's health care decisions. During the onset of the COVID-19 pandemic, how the medical experience of Chinese patients and their evaluations of hospitals have changed remains to be studied. Therefore, we plan to collect patient medical visit data from the internet to reflect the current status of medical relationships under specific circumstances. OBJECTIVE: This study aims to explore the differences in patient comments across various stages (during, before, and after) of the COVID-19 pandemic, as well as among different types of hospitals (children's hospitals, maternity hospitals, and tumor hospitals). Additionally, by leveraging ChatGPT (OpenAI), the study categorizes the elements of negative hospital evaluations. An analysis is conducted on the acquired data, and potential solutions that could improve patient satisfaction are proposed. This study is intended to assist hospital managers in providing a better experience for patients who are seeking care amid an emergent public health crisis. METHODS: Selecting the top 50 comprehensive hospitals nationwide and the top specialized hospitals (children's hospitals, tumor hospitals, and maternity hospitals), we collected patient reviews from these hospitals on the Dianping website. Using ChatGPT, we classified the content of negative reviews. Additionally, we conducted statistical analysis using SPSS (IBM Corp) to examine the scoring and composition of negative evaluations. RESULTS: A total of 30,317 pieces of effective comment information were collected from January 1, 2018, to August 15, 2023, including 7696 pieces of negative comment information. Manual inspection results indicated that ChatGPT had an accuracy rate of 92.05%. The F1-score was 0.914. The analysis of this data revealed a significant correlation between the comments and ratings received by hospitals during the pandemic. Overall, there was a significant increase in average comment scores during the outbreak (P<.001). Furthermore, there were notable differences in the composition of negative comments among different types of hospitals (P<.001). Children's hospitals received sensitive feedback regarding waiting times and treatment effectiveness, while patients at maternity hospitals showed a greater concern for the attitude of health care providers. Patients at tumor hospitals expressed a desire for timely examinations and treatments, especially during the pandemic period. CONCLUSIONS: The COVID-19 pandemic had some association with patient comment scores. There were variations in the scores and content of comments among different types of specialized hospitals. Using ChatGPT to analyze patient comment content represents an innovative approach for statistically assessing factors contributing to patient dissatisfaction. The findings of this study could provide valuable insights for hospital administrators to foster more harmonious physician-patient relationships and enhance hospital performance during public health emergencies.

Impact of epidemic prevention policies on public vaccination willingness: empirical research in China.

Background: The sudden emergence of the COVID-19 pandemic in early 2020 posed an enormous threat to public health. Vaccination is currently recognized as the most cost-effective preventive and control measure against the COVID-19 pandemic worldwide and is the key to constructing a line of defense against the virus, while the epidemic prevention policies adopted by governments have an important impact on the protective behavior of the public. The purpose of this study is to analyze the mechanism by which the stringency of epidemic prevention policies affects public vaccination willingness and to explore the mediating effect of public risk perception. Methods: A cross-sectional survey was conducted among 387 adults from December 2022 to June 2023 in China. A multiple linear regression model was used to explore the impact of epidemic prevention policy stringency on public vaccination willingness, and a hierarchical regression model was used to test the mediating effect of public risk perception. Results: Our results showed that public vaccination willingness increased by approximately 45.5% for every one-unit increase in the stringency of the epidemic prevention policies, which shows that the stringency of epidemic prevention policies has a significant positive influence on public vaccination willingness. In addition, public risk perception increased by approximately 38.9% during the period of stringent government policies on epidemic prevention. For every one-unit increase in risk perception, public vaccination willingness increased by approximately 40.9%, and the relationship between the stringency of epidemic prevention policies and public vaccination willingness was partially mediated by risk perception. Conclusion: The stricter the epidemic prevention policies, the stronger the public vaccination willingness; risk perception plays a mediating effect between the stringency of epidemic prevention policies and public vaccination willingness. This finding is particularly important for exploring and analyzing the factors influencing public vaccination willingness and for improving public health.

Impact of linkage level on inferences from big data analyses in health and medical research: an empirical study.

BACKGROUND: Linkage errors that occur according to linkage levels can adversely affect the accuracy and reliability of analysis results. This study aimed to identify the differences in results according to personally identifiable information linkage level, sample size, and analysis methods through empirical analysis. METHODS: The difference between the results of linkage in directly identifiable information (DII) and indirectly identifiable information (III) linkage levels was set as III linkage based on name, date of birth, and sex and DII linkage based on resident registration number. The datasets linked at each level were named as databaseIII (DBIII) and databaseDII (DBDII), respectively. Considering the analysis results of the DII-linked dataset as the gold standard, descriptive statistics, group comparison, incidence estimation, treatment effect, and moderation effect analysis results were assessed. RESULTS: The linkage rates for DBDII and DBIII were 71.1% and 99.7%, respectively. Regarding descriptive statistics and group comparison analysis, the difference in effect in most cases was "none" to "very little." With respect to cervical cancer that had a relatively small sample size, analysis of DBIII resulted in an underestimation of the incidence in the control group and an overestimation of the incidence in the treatment group (hazard ratio [HR] = 2.62 [95% confidence interval (CI): 1.63-4.23] in DBIII vs. 1.80 [95% CI: 1.18-2.73] in DBDII). Regarding prostate cancer, there was a conflicting tendency with the treatment effect being over or underestimated according to the surveillance, epidemiology, and end results summary staging (HR = 2.27 [95% CI: 1.91-2.70] in DBIII vs. 1.92 [95% CI: 1.70-2.17] in DBDII for the localized stage; HR = 1.80 [95% CI: 1.37-2.36] in DBIII vs. 2.05 [95% CI: 1.67-2.52] in DBDII for the regional stage). CONCLUSIONS: To prevent distortion of the analyses results in health and medical research, it is important to check that the patient population and sample size by each factor of interest (FOI) are sufficient when different data are linked using DBDII. In cases involving a rare disease or with a small sample size for FOI, there is a high likelihood that a DII linkage is unavoidable.

The chain mediating effect of spiritual well-being and anticipatory grief between benefit finding and meaning in life of patients with advanced lung cancer: Empirical research quantitative.

AIM: This study aimed to explore the chain mediating effect of spiritual well-being and anticipatory grief between benefit finding and meaning in life of patients with advanced lung cancer. DESIGN: This was a cross-sectional study. METHODS: The research included 400 patients with advanced lung cancer who attended REDACTE from December 2022 to August 2023 as the research subjects. Data were collected using a questionnaire including socio-demographic and clinical characteristics, the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being scale (FACIT-Sp-12), the Benefit Finding Scale (BFS), the Preparatory Grief in Advanced Cancer Patients Scale (PGAC), and the Meaning of Life Questionnaire (MLQ). The structural equation model (SEM) was used to analyse the relationship between benefit finding, spiritual well-being, anticipatory grief and meaning in life. RESULTS: There was a significant correlation between benefit finding, spiritual well-being, anticipatory grief, and meaning in life. Benefit finding could have a direct positive impact on meaning in life of patients with advanced lung cancer, but it could also indirectly affect meaning in life of patients with advanced lung cancer through three pathways: the mediating effect of spiritual well-being, the mediating effect of anticipatory grief and the chain mediating effect of spiritual well-being and anticipatory grief. Nursing staff should develop an integrated program of interventions to enhance the meaning in life of patients with advanced lung cancer.

Assessing the Relationship Between Digital Trail Making Test Performance and IT Task Performance: Empirical Study.

BACKGROUND: Cognitive functional ability affects the accessibility of IT and is thus something that should be controlled for in user experience (UX) research. However, many cognitive function assessment batteries are long and complex, making them impractical for use in conventional experimental time frames. Therefore, there is a need for a short and reliable cognitive assessment that has discriminant validity for cognitive functions needed for general IT tasks. One potential candidate is the Trail Making Test (TMT). OBJECTIVE: This study investigated the usefulness of a digital TMT as a cognitive profiling tool in IT-related UX research by assessing its predictive validity on general IT task performance and exploring its discriminant validity according to discrete cognitive functions required to perform the IT task. METHODS: A digital TMT (parts A and B) named Axon was administered to 27 healthy participants, followed by administration of 5 IT tasks in the form of CAPTCHAs (Completely Automated Public Turing tests to Tell Computers and Humans Apart). The discrete cognitive functions required to perform each CAPTCHA were rated by trained evaluators. To further explain and cross-validate our results, the original TMT and 2 psychological assessments of visuomotor and short-term memory function were administered. RESULTS: Axon A and B were administrable in less than 5 minutes, and overall performance was significantly predictive of general IT task performance (F5,19=6.352; P=.001; Λ=0.374). This result was driven by performance on Axon B (F5,19=3.382; P=.02; Λ=0.529), particularly for IT tasks involving the combination of executive processing with visual object and pattern recognition. Furthermore, Axon was cross-validated with the original TMT (Pcorr=.001 and Pcorr=.017 for A and B, respectively) and visuomotor and short-term memory tasks. CONCLUSIONS: The results demonstrate that variance in IT task performance among an age-homogenous neurotypical population can be related to intersubject variance in cognitive function as assessed by Axon. Although Axon's predictive validity seemed stronger for tasks involving the combination of executive function with visual object and pattern recognition, these cognitive functions are arguably relevant to the majority of IT interfaces. Considering its short administration time and remote implementability, the Axon digital TMT demonstrates the potential to be a useful cognitive profiling tool for IT-based UX research.

A Primer for Increasing Competency in Forensic Psychiatry Research.

Empirical research is foundational to the discipline of forensic psychiatry. Candilis and Parker provide a cogent systematic review of the empirical literature on restoration of competence to stand trial using National Institutes of Health quality metrics. Components of the study methodology are highlighted, as they represent current best practices for conducting a systematic review. A discussion of strategies to increase empirical research uptake in forensic psychiatry is pursued alongside concrete examples of how the American Academy of Psychiatry and the Law Research Committee can help facilitate this goal.

The work relative value estimation assessment in China: an empirical research for common surgical procedures.

Objectives: China's National Health Service Items Standard (NHSIS) establishes a relative value system and plays an important role in pricing. However, there are few empirical evaluations of the objectivity of the NHSIS-estimated relative value. Methods: This paper presents a comparison between physician work relative value units (wRVUs) estimates for 70 common surgical procedures from NHSIS and those from the U.S. Medicare Physician Fee Schedule (MPFS). We defined the ratio of the wRVUs for sample procedures to the benchmark procedure (inguinal hernia repair) as a standardized relative value unit (SRVU), which was used to standardize the data for both schedules. We examined the variances in the ranking and quantification of SRVUs across specialties and procedures, as well as how SRVUs impact procedure reimbursement prices between the two schedules. Results: There was no systematic difference between MHSIS-estimated SRVUs and MPFS-estimated, but the dispersion of MPFS-estimated SRVU was greater than that of MHSIS-estimated, and the discrepancies increased with surgical risk and technical complexity. The discrepancies of SRVUs were significant in cardiothoracic procedures. Additionally, whether SRVUs were based on MPFS or MHSIS, there was a positive association between them and payment prices. However, in terms of the impact of SRVUs on payment pricing, the NHSIS system was lower than the MPFS system. Conclusion: China has made incremental progress in estimating the relative value of healthcare services, but there are shortcomings in valuation methods and their impact on pricing. The modular assessment method should be considered as a component to optimize reform.

Using symbiotic empirical ethics to explore the significance of relationships to clinical ethics: findings from the Reset Ethics research project.

BACKGROUND: At the beginning of the coronavirus (Covid-19) pandemic, many non-Covid healthcare services were suspended. In April 2020, the Department of Health in England mandated that non-Covid services should resume, alongside the continuing pandemic response. This 'resetting' of healthcare services created a unique context in which it became critical to consider how ethical considerations did (and should) underpin decisions about integrating infection control measures into routine healthcare practices. We draw on data collected as part of the 'NHS Reset Ethics' project, which explored the everyday ethical challenges of resetting England's NHS maternity and paediatrics services during the pandemic. METHODS: Healthcare professionals and members of the public participated in interviews and focus group discussions. The qualitative methods are reported in detail elsewhere. The focus of this article is our use of Frith's symbiotic empirical ethics methodology to work from our empirical findings towards the normative suggestion that clinical ethics should explicitly attend to the importance of relationships in clinical practice. This methodology uses a five-step approach to refine and develop ethical theory based on a naturalist account of ethics that sees practice and theory as symbiotically related. RESULTS: The Reset project data showed that changed working practices caused ethical challenges for healthcare professionals, and that infection prevention and control measures represented harmful barriers to the experience of receiving and offering care. For healthcare professionals, offering care as part of a relational interaction was an ethically important dimension of healthcare delivery. CONCLUSIONS: Our findings suggest that foregrounding the importance of relationships across a hospital community will better promote the ethically important multi-directional expression of caring between healthcare professionals, patients, and their families. We offer two suggestions for making progress towards such a relational approach. First, that there is a change of emphasis in clinical ethics practice to explicitly acknowledge the importance of the relationships (including with their healthcare team) within which the patient is held. Second, that organisational decision-making should take into account the moral significance afforded to caring relationships by healthcare professionals, and the role such relationships can play in the negotiation of ethical challenges.

Clinical research nurses perceive their role as being like the hub of a wheel without real power: Empirical qualitative research.

AIM: This study aimed to explore the experiences of being a clinical research nurse (CRN), in Sweden. DESIGN: A qualitative study analysing individual interview data. METHODS: Interviews with 10 participants were conducted in April 2017 and repeated with five participants in May 2022. A semi-structured interview guide was used to cover topics such as experiences of working in a new role and professional challenges related to the role. The transcribed interviews were analysed inductively using qualitative content analysis. RESULTS: The main theme revealed that the CRNs experienced their work role as being like a hub in a wheel, using an ethical compass, but without real power. The six themes identified showed that CRNs worked independently and relied on clinical experiences as nurses but needed more education. They not only had a sense of duty but also too large responsibilities. Furthermore, they viewed their work as valuable and important. However, they needed an accentuated ethical compass and were also affected by power relations that negatively impacted work. CONCLUSION: Working as a CRN means being in a central position and working independently, which requires diverse skills and competencies. CRNs, however, face and manage complex ethical and practical challenges without real power. They experience huge responsibilities but need education and acknowledgement, indicating a need for improvement. This is an important message to stakeholders and managers about the necessity of taking adequate action to support CRNs who are crucial resources in clinical research. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Eye tracking and audio sensors to evaluate surgeon's non-technical skills: An empirical study.

Non-Technical Skills (NTS) of medical teams are currently measured using subjective and resource-intensive ratings given by experts. This study explores if objective NTS assessment approaches with eye-tracking and audio sensors can measure teamwork and communication skills in surgery. Eight surgeons participated in a simulated two-phase surgical scenario developed to assess their NTS. Sensor-based audio, eye tracking and video data were collected and analyzed along with rating from the NOTSS scale. Different levels of communication were detected by the sensor data during the two phases of the simulated surgery. Sensor data detected leadership qualities among surgeons based on speech metrics, and eye tracking offered additional evidence about gaze patterns related to NTS. This objective approach to NTS measurement captured differences in communication in greater detail as opposed to a single collective rating obtained using current assessment tools.

Is the digital economy empowering high-quality tourism development? A theoretical and empirical research from China.

How digital economy (DE) empowers high-quality development of tourism (HQDT) has become a common concern among scholars. Given this, this study clarifies the theoretical connotation of DE enabling HQDT,and finds that: Micro, DE promotes efficiency improvements in tourism enterprises, with its economies of scale and Matthew effect reducing average costs, its economies of scope meeting diversified demand, and its long-tail effect improving supply-demand matching mechanism. Meso, DE can transform and upgrade tourism industry structure through industrial digitization and digital industrialization, and also form a new tourist industry form and value chain through cross-border integration. Macro, DE can stimulate innovation and flexibility of market players, increase new factor inputs in tourism, improve factor allocation efficiency, and advance macro regulation of the tourism market. Accordingly, the study conducts an empirical test based on panel data for 31 provinces in mainland China during 2011-2020. Results show that: ① DE positively influences HQDT, and the sub-dimensions all positively influence HQDT. ② DE has a heterogeneous impact on HQDT and shows spatial spillover effects. Finally, the study concludes with effective paths for DE promoting HQDT: "Promote digital infrastructure construction, accelerate tourism digital transformation, strengthen integration and innovation development, and overcome the challenges of tourism enterprises".

How do taxi drivers expose to fine particulate matter (PM2.5) in a Chinese megacity: a rapid assessment incorporating with satellite-derived information and urban mobility data.

BACKGROUND: Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability. METHODS: This study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers' exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers' activities. RESULTS: The taxi drivers' weekday and weekend 24-h PM2.5 exposure was 83.60 µg/m3 and 55.62 µg/m3 respectively, 3.4 and 2.2 times than the WHO's recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the "Inner Ring Road", while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the "Third Ring Road". CONCLUSION: These findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.

The power threat meaning framework 5 years on - A scoping review of the emergent empirical literature.

Since its release the Power Threat Meaning Framework (PTMF) has received considerable interest and uptake. However, there have not yet been any attempts to review the scope of this emergent literature. This scoping review aimed to identify and synthesize: (1) all empirical research which utilized the PTMF in their methodologies, (2) the characteristics of these studies, (3) the different ways in which these studies utilized the PTMF, and (4) the key findings of these studies. This review was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) scoping review extension (PRISMA-ScR). Following systematic searches of academic databases and grey literature, 17 studies meeting eligibility criteria were included. These papers were subject to critical appraisal, data charting, and narrative synthesis. This review identified four uses of the PTMF: (1) PTMF-informed data collection, (2) PTMF-informed data analysis, (3) Experiences of/views on the PTMF, and (4) PTMF-informed psychological practices. This evidence-base demonstrated the merits of utilizing the PTMF across a range of disciplines, settings, and populations. This heterogeneity also presents challenges for evidence synthesis. Implications for research (e.g. importance of the coherent and consistent approach to research) and practice/policy (e.g. professional training, collaboration, service-level barriers) are considered.

Digital transformation and supply chain efficiency improvement: An empirical study from a-share listed companies in China.

This article thoroughly examines the influence of digital transformation on the efficiency of corporate supply chains. As global economic integration accelerates and technological innovations deepen, digital transformation has become key to enhancing core corporate competitiveness. This research, utilizing data from A-share listed companies in China between 2007 and 2022, analyzes how companies improve supply chain efficiency through digital transformation. Furthermore, the study establishes a theoretical framework that demonstrates how digital transformation facilitates supply chain efficiency from the perspectives of internal governance and external competition. The research indicates that digital transformation plays a key role in significantly enhancing supply chain efficiency. Furthermore, the results of the mechanism analysis confirmed that digital transformation contributes to enhancing corporate supply chain efficiency by improving the level of corporate governance and the degree of market competition. The study also finds that the effect of digital transformation on supply chain efficiency varies with different corporate backgrounds, indicating its heterogeneous impact. Lastly, an analysis of economic consequences shows that the increased supply chain efficiency resulting from digital transformation can reduce future external transaction costs, strengthening the company's market position and financial performance. This research provides strategic guidance for firms to develop robust strategies amid the digital wave and offers strong policy recommendations for promoting digital supply chain management and enhancing market adaptability.

An empirical assessment of the influence of digital transformation on sports corporate sustainability.

The trend of digital transformation fosters enterprise change, helps cultivate enterprises' own competitive advantages and is crucial to the advancement of sports enterprises' sustainable development in the framework of the emerging digital economy as a national strategy. However, there have been few empirical studies on the microlevel of digital transformation and its impact on the sustainability of sports organizations. Therefore, the sustainable growth dynamic model is used to construct indicators of corporate sustainability by referencing 48 sports corporations listed on Shanghai and Shenzhen A-shares markets and the New Third Board in China from 2012 to 2021. The intrinsic relationship between digital transformation and the sustainable development of sports enterprises and the underlying mechanism of action are explored by constructing a panel fixed effects model, a chain mediating effects model, and a panel threshold model. The most important contribution is as follows: To provide a useful reference for analyzing enterprise digital transformation, a more complete indicator indicating the extent of corporate digital transformation is built. The micro viewpoint broadens our awareness of sustainable development in sports organizations and deepens our understanding of the interaction model between sustainable development and enterprise digital transformation. This study provides methodical evidence and insights for an accurate understanding of digital transformation for sustainable enterprise development, looking into the "black box" of the mechanism between digital transformation and sustainable business development. The results show that digital transformation significantly aids sports enterprises in their pursuit of long-term sustainability. Heterogeneity tests demonstrate the pivotal role of digital transformation in advancing the sustained growth of sports firms and high-tech sports enterprises situated in the eastern region of China. Regarding transmission mechanisms, the chain mediating effect of enterprises' digital transformation on improved technological innovation and TFP, which in turn promote long-term business growth, has yet to be validated. Further examination exposes that within the context of the correlation between digital transformation and the sustainability of corporations, there is a single threshold effect based on financing restrictions and operational costs and a double threshold effect based on operational efficiency.

Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape image analysis.

Semantic segmentation of cityscapes via deep learning is an essential and game-changing research topic that offers a more nuanced comprehension of urban landscapes. Deep learning techniques tackle urban complexity and diversity, which unlocks a broad range of applications. These include urban planning, transportation management, autonomous driving, and smart city efforts. Through rich context and insights, semantic segmentation helps decision-makers and stakeholders make educated decisions for sustainable and effective urban development. This study investigates an in-depth exploration of cityscape image segmentation using the U-Net deep learning model. The proposed U-Net architecture comprises an encoder and decoder structure. The encoder uses convolutional layers and down sampling to extract hierarchical information from input images. Each down sample step reduces spatial dimensions, and increases feature depth, aiding context acquisition. Batch normalization and dropout layers stabilize models and prevent overfitting during encoding. The decoder reconstructs higher-resolution feature maps using "UpSampling2D" layers. Through extensive experimentation and evaluation of the Cityscapes dataset, this study demonstrates the effectiveness of the U-Net model in achieving state-of-the-art results in image segmentation. The results clearly shown that, the proposed model has high accuracy, mean IOU and mean DICE compared to existing models.

Risk management and empirical study of the doctor-patient relationship: based on 1790 litigation cases of medical damage liability disputes in China.

BACKGROUND: Compensation for medical damage liability disputes (CMDLD) seriously hinders the healthy development of hospitals and undermines the harmony of the doctor-patient relationships (DPR). Risk management in the DPR has become an urgent issue of the day. The study aims to provide a comprehensive description of CMDLD in China and explore its influencing factors, and make corresponding recommendations for the management of risks in the DPR. METHODS: This study extracted data from the China Judgment Online - the official judicial search website with the most comprehensive coverage. Statistical analysis of 1,790 litigation cases of medical damage liability disputes (COMDLD) available from 2015 to 2021. RESULTS: COMDLD generally tended to increase with the year and was unevenly distributed by regions; the compensation rate was 52.46%, the median compensation was 134,900 yuan and the maximum was 2,234,666 yuan; the results of the single factor analysis showed that there were statistically significant differences between the compensation for different years, regions, treatment attributes, and trial procedures (P < 0.05); the correlation analysis showed that types of hospitals were significantly negatively associated with regions (R=-0.082, P < 0.05); trial procedures were significantly negatively correlated with years (R=-0.484, P < 0.001); compensat- ion was significantly positively correlated with years, regions, and treatment attributes (R = 0.098-0.294, P < 0.001) and negatively correlated with trial procedures (R=-0.090, P < 0.01); regression analysis showed that years, treatment attributes, and regions were the main factors affecting the CMDLD (P < 0.05). CONCLUSIONS: Years, regions, treatment attributes, and trial procedures affect the outcome of CMDLD. This paper further puts forward relevant suggestions and countermeasures for the governance of doctor-patient risks based on the empirical results. Including rational allocation of medical resources to narrow the differences between regions; promoting the expansion and sinking of high-quality resources to improve the level of medical services in hospitals at all levels; and developing a third-party negotiation mechanism for medical disputes to reduce the cost of medical litigation.

Is economic growth enough to propel rehabilitation expenditures? An empirical analysis of country panel data and policy implications.

PURPOSE: Rehabilitation is a set of services designed to increase functioning and improve wellbeing across the life course. Despite being a core part of Universal Health Coverage, rehabilitation services often receive limited public expenditure, especially in lower income countries. This leads to limited service availability and high out of pocket payments for populations in need of care. The purpose of this research was to assess the association between macroeconomic conditions and rehabilitation expenditures across low-, middle-, and high-income countries and to understand its implications for overall rehabilitation expenditure trajectory across countries. MATERIALS AND METHODS: We utilized a panel data set from the World Health Organization's Global Health Expenditure Database comprising the total rehabilitation expenditure for 88 countries from 2016 to 2018. Basic macroeconomic and population data served as control variables. Multiple regression models were implemented to measure the relationship between macroeconomic conditions and rehabilitation expenditures. We used four different model specifications to check the robustness of our estimates: pooled data models (or naïve model) without control, pooled data models with controls (or expanded naïve model), fixed effect models with all controls, and lag models with all controls. Log-log specifications using fixed effects and lag-dependent variable models were deemed the most appropriate and controlled for time-invariant differences. RESULTS: Our regression models indicate that, with a 1% increase in economic growth, rehabilitation expenditure would be associated with a 0.9% and 1.3% increase in expenditure. Given low baseline levels of existing rehabilitation expenditure, we anticipate that predicted increases in rehabilitation expenditure due to economic growth may be insufficient to meet the growing demand for rehabilitation services. Existing expenditures may also be vulnerable during periods of economic recession. CONCLUSION: This is the first known estimation of the association between rehabilitation expenditure and macroeconomic conditions. Our findings demonstrate that rehabilitation is sensitive to macroeconomic fluctuations and the path dependency of past expenditures. This would suggest the importance of increased financial prioritization of rehabilitation services and improved institutional strengthening to expand access to rehabilitation services for populations.