BACKGROUND: Medical research productivity is globally increasing, with a lagging progress in third-world countries due to significant challenges, including inadequate training and brain drain. Syria had been showing a slow upward trend until the war broke out and severely hindered academic growth and productivity. A deeper understanding of the factors influencing research productivity in this context are fundamental to guide educational policies and resource allocation. Previous cross-sectional studies that evaluated the perspectives of Syrian academics on the issue were limited by the small sample size of published healthcare workers, making it difficult to identify the factors that enabled them to pursue research.
METHODS: To address this challenge, we employed a case-control design. We isolated published early-career Syrian healthcare workers and compared their characteristics and perceptions to unpublished matched controls. Authors in the fields of medicine, dentistry, and pharmacy affiliated with any Syrian University were identified through an extensive search of PubMed and Google Scholar.These authors were invited to complete a questionnaire that covered participants\' research contributions, alongside their self-assessed knowledge, attitudes, and barriers towards research. The questionnaire was publicly published to recruit an equal sample of matching controls, with half consisting of unpublished researchers and the other half of participants without prior research contributions.
RESULTS: Six-hundred-sixteen participants were recruited. Their knowledge, attitudes, and perceived barriers explained 46% and 34% of the variability in research involvement and publication, respectively (P < 0.001). Getting involved in and publishing research studies associated with higher research-related knowledge and attitudes (P < 0.001). Respondents\' assessment of research-related barriers and their academic scores did not differ between cases and controls. Superior research-related knowledge and attitudes were associated with male gender, higher English competency, and better internet connectivity. Meanwhile, extracurricular training and mentors\' support were associated with more positive research-related attitudes and less perceived barriers.
CONCLUSIONS: Research productivity of medical professionals in Syria exhibits a positive correlation with their knowledge and favorable attitudes towards medical research. Noteworthy, the demographic variations are linked to disparities in research-related knowledge and motivation. In conclusion, these results suggest a potential avenue for enhancement through concentrated efforts on improving extracurricular training interventions and mentors\' support.

BACKGROUND: Named entity recognition (NER) is a fundamental task in natural language processing. However, it is typically preceded by named entity annotation, which poses several challenges, especially in the clinical domain. For instance, determining entity boundaries is one of the most common sources of disagreements between annotators due to questions such as whether modifiers or peripheral words should be annotated. If unresolved, these can induce inconsistency in the produced corpora, yet, on the other hand, strict guidelines or adjudication sessions can further prolong an already slow and convoluted process.
OBJECTIVE: The aim of this study is to address these challenges by evaluating 2 novel annotation methodologies, lenient span and point annotation, aiming to mitigate the difficulty of precisely determining entity boundaries.
METHODS: We evaluate their effects through an annotation case study on a Japanese medical case report data set. We compare annotation time, annotator agreement, and the quality of the produced labeling and assess the impact on the performance of an NER system trained on the annotated corpus.
RESULTS: We saw significant improvements in the labeling process efficiency, with up to a 25% reduction in overall annotation time and even a 10% improvement in annotator agreement compared to the traditional boundary-strict approach. However, even the best-achieved NER model presented some drop in performance compared to the traditional annotation methodology.
CONCLUSIONS: Our findings demonstrate a balance between annotation speed and model performance. Although disregarding boundary information affects model performance to some extent, this is counterbalanced by significant reductions in the annotator\'s workload and notable improvements in the speed of the annotation process. These benefits may prove valuable in various applications, offering an attractive compromise for developers and researchers.

This paper examines the effect of new medical technology (robotic surgery) on efficiency gains and productivity changes for surgical treatment in patients with prostate cancer from the perspective of a public health sector organization. In particular, we consider three interrelated surgical technologies within the English National Health System: robotic, laparoscopic and open radical prostatectomy. Robotic and laparoscopic techniques are minimally invasive procedures with similar clinical benefits. While the clinical benefits in adopting robotic surgery over laparoscopic intervention are unproven, it requires a high initial investment cost and carries high on-going maintenance costs. Using data from Hospital Episode Statistics for the period 2000-2018, we observe growing volumes of prostatectomies over time, mostly driven by an increase in robotic-assisted surgeries, and further analyze whether hospital providers that adopted a robot see improved measures of throughput. We then quantify changes in total factor and labor productivity arising from the use of this technology. We examine the impact of robotic adoption on efficiency gains employing a staggered difference-in-difference estimator and find evidence of a 50% reduction in length of stay (LoS), 49% decrease in post-LoS and 44% and 46% decrease in postoperative visits after 1 year and 2 years, respectively. Productivity analysis shows the growth in radical prostatectomy volume is sustained with a relatively stable number of urology surgeons. The robotic technique increases total production at the hospital level between 21% and 26%, coupled with a 29% improvement in labor productivity. These benefits lend some, but not overwhelming support for the large-scale hospital investments in such costly technology.

BACKGROUND: Various professional groups are involved in the daily work of the central operating room with the aim of providing the best possible treatment for each individual using modern medical technology (sociotechnical system) in a cost-effective manner. Ensuring perioperative patient safety is of particular importance. At the same time, the efficient use of the central operating room is essential for the economic success of a hospital. Preoperative preparation is a complex process with many substeps that are often difficult to manage. Historically, the focus has been on retrospective learning from errors and incidents. More recent approaches take a systemic view. A central idea is to consider the mostly positive course of treatment and the adjustments to daily work that are currently required by the people involved (Safety-II). By taking greater account of how the many components of the system interact, processes can be better understood and specific measures derived. This strengthens the system\'s ability to adapt to changes and disturbances, thus ensuring that goals are achieved. The functional resonance analysis method (FRAM) is an internationally recognized method for modelling work as done compared to work as imagined. This paper presents the application of FRAM to preoperative preparation in a major regional hospital.
OBJECTIVE: Is FRAM suitable for improving process understanding in preoperative preparation?
METHODS: An interdisciplinary project team identified relevant functions of preoperative preparation through document analysis and walkthroughs. Based on this, more than 30 guided interviews were conducted with functionaries. The results were presented graphically and specific information, such as safety-related statements or reasons for the variability of functions, were also presented textually. In the next phase, statements were evaluated and compared with the target model and the job descriptions.
RESULTS: The FRAM revealed the process as a complex network of relationships. During the modelling process, a varying degree of centrality and variability of certain functions became apparent. From the observations, the project team selected those with high relevance for patient safety and for the efficiency of the overall process in order to prioritize starting points for deriving measures to increase resilience. These starting points relate either to single functions, such as surgical site marking or to multiple functions that are variable in their execution, such as delays due to nonsynchronized duty times.
CONCLUSIONS: The FRAM conducted provides valuable new insights into the functioning of complex sociotechnical systems that go far beyond classical linear methods. The awareness of operational processes gained and the resulting dynamic view of interactions within the system enable specific measures to be derived that promote resilient behavior and reduce critical variability, thus contributing to increased patient safety and efficiency.
UNASSIGNED: HINTERGRUND: Die präoperative Vorbereitung ist ein komplexer Prozess, der aus zahlreichen, oft schwer überschaubaren Teilschritten besteht. Dabei sind sowohl Patientensicherheit als auch Effizienz von großer Bedeutung. Bisher stand das retrospektive Lernen aus Fehlern und Zwischenfällen im Vordergrund. Neuere Ansätze verfolgen einen systemischen Ansatz. Sie fokussieren auf die Ursachen der überwiegend positiven klinischen Prozesse. Mit der Methode der funktionalen Resonanzanalyse (FRAM) wird die tatsächliche Arbeit im Vergleich zur geplanten Arbeit modelliert. Durch ein besseres Prozessverständnis sollen Maßnahmen abgeleitet werden, die die Fähigkeit des Systems stärken, seine Ziele auch bei Veränderungen und Störungen zu erreichen.
UNASSIGNED: Ist die FRAM geeignet, das Prozessverständnis in der präoperativen Vorbereitung zu verbessern?
METHODS: Das interdisziplinäre Projektteam identifizierte relevante Funktionen der präoperativen Vorbereitung durch Dokumentenanalysen und Begehungen. Darauf aufbauend wurden mehr als 30 leitfadengestützte Interviews mit Funktionsträgern durchgeführt. Die Ergebnisse wurden grafisch und spezifische Informationen zusätzlich textlich aufbereitet.
UNASSIGNED: Die FRAM stellt den betrachteten Prozess als komplexes Beziehungsgeflecht dar. Bei der Erstellung wurde ein unterschiedlicher Grad an Zentralität und Variabilität bestimmter Funktionen deutlich, der sich über die Vernetzung auf die Patientensicherheit und Effizienz auswirkt. Aufbauend auf dem verbesserten Prozessverständnis wurden gezielte Maßnahmen ergriffen.
UNASSIGNED: Die Durchführung einer FRAM erweitert das Verständnis der Funktionsweise komplexer soziotechnischer Systeme erheblich. Sie stellt damit ein wertvolles neues Instrument zur Identifikation von spezifischen Ansatzpunkten zur Erhöhung der Resilienz dar.

UNASSIGNED: This study explores the coupling and coordinated development of new urbanization and eco-efficiency and their interaction mechanisms from the perspective of efficiency, and it has significant implications for promoting high-quality development and surpassing in China\'s regional development.
UNASSIGNED: The study aims to investigate the spatiotemporal distribution pattern of new urbanization efficiency and eco-efficiency and its coupling and coordinated development relationship.
UNASSIGNED: Using panel data from 2010 to 2020 for nine cities in Fujian Province, this study employs the undesired super-efficiency SBM model to measure the efficiency of new urbanization and eco-efficiency. Additionally, a spatial panel Durbin model is constructed to analyze the interaction effect between the two efficiencies.
UNASSIGNED: During the study period, both new urbanization efficiency and eco-efficiency in Fujian Province showed a fluctuating upward trend, with higher efficiency in the southeast than the northwest, exhibiting significant spatial agglomeration effects. Despite high double efficiency coupling, coordinated development was low, evolving from near-disorder to barely coordinated. The high coupling and coordination areas were mainly concentrated in the southeast, with gaps between different regions gradually narrowing. There was positive interaction between dual efficiency in the same region, with new urbanization efficiency showing a positive spatial spillover effect on eco-efficiency. Conversely, the spatial spillover effect of eco-efficiency on new urbanization efficiency was not significant.

The case-cohort study design provides a cost-effective study design for a large cohort study with competing risk outcomes. The proportional subdistribution hazards model is widely used to estimate direct covariate effects on the cumulative incidence function for competing risk data. In biomedical studies, left truncation often occurs and brings extra challenges to the analysis. Existing inverse probability weighting methods for case-cohort studies with competing risk data not only have not addressed left truncation, but also are inefficient in regression parameter estimation for fully observed covariates. We propose an augmented inverse probability-weighted estimating equation for left-truncated competing risk data to address these limitations of the current literature. We further propose a more efficient estimator when extra information from the other causes is available. The proposed estimators are consistent and asymptotically normally distributed. Simulation studies show that the proposed estimator is unbiased and leads to estimation efficiency gain in the regression parameter estimation. We analyze the Atherosclerosis Risk in Communities study data using the proposed methods.

The utilization efficiency of land resources is an essential embodiment of economic development, social development, and ecological development and is a critical core to measure how to maximize the efficiency of land resources under limited conditions. The land is an important content and essential carrier of the research of tourism development level. This paper selects Panel Data from 2010 to 2019 to research the Guangxi regional tourism development. The entropy weight method and stochastic frontier production function (SFA) model were used to evaluate the development level of urban-rural tourism and the utilization efficiency of land resources in Guangxi. This paper uses the Panel Vector Autoregression (PVAR) model to analyze the internal relationship between urban-rural tourism development. The results show that: (1) Guangxi has a good level of tourism development and a high land use efficiency. (2) There is a reciprocal causation relationship between the regional tourism development level and land use efficiency in Guangxi, with significant levels of 0.005 and 0.034 respectively, indicating high credibility. This indicates that there is a mutual promotion and interaction between the two, which rely on and drive each other, promoting the joint sustainability of tourism development and land use efficiency. (3) . The tourism development level is greatly influenced by itself, with impact values all above 0.99. At the same time, land use also has a significant self-impact, with impact values all above 0.87. Their internal optimization system is solid and endogenous impetus is robust, which can drive their development. Establishing an effective strategy for developing and protecting land use is beneficial to promote the long-term effectiveness of sustainable tourism development, enhancing high-quality development of the tourism economy and improving people\'s living standards and quality.

Exploring the of regional tourism efficiency is of great significance in promoting high-quality development of regional tourism. However, there are not many studies that measure the quality development of tourism destinations from the perspective of inputs and output. Based on this, the data envelopment analysis model is used to measure the overall technical efficiency (TECRS), pure technical efficiency (TEVRS), and scale efficiency (SE) with the help of DEA-SOLVER software, taking the ten prefecture-level cities in Shaanxi Province as examples, to further analyze and evaluate the spatial differences of different tourism destinations and the reasons for the differences. The results of the study found that: the efficiency indicators explain the differences in the development quality of tourism destinations from different sides; the development quality of tourism destinations in Shaanxi as a whole is low, with excessive inputs and insufficient outputs; and the tourism destinations with relatively high development quality are distributed in the Guanzhong. On this basis, corresponding countermeasure suggestions are put forward to promote the improvement of governance efficiency of tourism destinations in Shaanxi Province, and then optimize the quality of development.

New Public Management-inspired reforms in the Norwegian hospital sector have introduced several features from the private sector into a predominantly public healthcare system. Since the late 1990s, several reforms have been carried out with the intention of improving the utilization of resources. There is, however, limited knowledge about the long-term, and sector-wide effects of these reforms. In this study, using a panel data set of all public hospital trusts spanning nine years, we provide an analysis of the efficiency of hospital trusts using data envelopment analysis (DEA), as well as a Malmquist productivity index. Thereafter we use the efficiency scores as the dependent variable in a second-stage panel data regression analysis. We show that during the period between 2011 and 2019, on average, efficiency has increased over time. Further, in the second-stage analysis, we show that New Public Management features related to incentivization are associated with the level of hospital efficiency. We find no association between degree of competition and efficiency.

The spatial spillover of urban innovation has increasingly become an important factor affecting urban total factor productivity (TFP) growth. Based on the panel data of 108 cities in the Yangtze River Economic Belt from 2004 to 2020, this paper illustrates the spatial-temporal evolution trend of urban innovation and manufacturing total factor productivity and uses the spatial Dubin model to study the direct and indirect effects of urban innovation on manufacturing total factor productivity. The main conclusions are as follows:(1)Spatial correlation and heterogeneity between urban innovation and manufacturing total factor productivity prove to be significant in the Yangtze River Economic Belt;(2)Urban innovation has a significant positive impact on manufacturing total factor productivity and has a positive spillover effect on surrounding cities; (3)The effect of urban innovation on manufacturing total factor productivity varies with time and region;(4) Mechanism analysis shows that talent agglomeration significantly promotes the positive impact of urban innovation on manufacturing total factor productivity, while the spillover effect is insignificant.