OBJECTIVE: To analyze the allocation and utilization efficiency of hospital beds in Sichuan Province, China, and to provide a scientific basis for improving the rational allocation and efficient utilization.
METHODS: The supply and demand balance method, health resource agglomeration degree (HRAD), bed efficiency index and bed utilization model were used to evaluate the allocation and utilization efficiency of hospital beds in Sichuan Province from 2017 to 2021.
RESULTS: The number of hospital beds per 1000 population in Sichuan Province increased from 4.97 in 2017 to 5.94 in 2021. The overall supply and demand ratio of hospital beds in Sichuan Province is between 0.85 and 1.01, and the supply and demand situation is a basically balanced situation. The HRAD of hospital beds in Ya\'an, Aba, Ganzi and Liangshan is <1, indicating that the equity of hospital beds by geography in these regions is low. The difference between HRAD and population agglomeration degree (PAD) in 9 regions, including Deyang, Aba, Ganzi and Liangshan, is <0, indicating that there are insufficient hospital beds in these areas relative to the agglomerated population. The bed efficiency index of hospital beds in 17 regions, including Chengdu, Zigong, Aba and Ganzi, are all <1, which means that hospital beds are operating with low efficiency. The bed utilization model of Panzhihua is efficiency type, that of Zigong, Deyang and Ziyang is pressure bed type, and that of Nanchong and Ya\'an is idle type.
CONCLUSIONS: The hospital bed allocation in Sichuan Province is relatively good, and the supply and demand situation is in a basically balanced situation. The hospital bed allocation in Aba, Ganzi and Liangshan is insufficient by geography and population. The overall operational efficiency of hospital beds is low, and there are more idle and pressure bed utilization models.

OBJECTIVE: To analyze the coupling and coordination level of medical education and health resource allocation in China, and to provide scientific basis for promoting the high-quality development of medical education and the efficient allocation of health resources.
METHODS: Based on the panel data from 2011 to 2021, the coupling coordination degree model was used to measure the coupling coordination index of medical education and health resources in China. The spatial auto-correlation model was used to analyze the development status and distribution characteristics of the coupling coordination degree of the two systems. The kernel density estimation method was used to analyze the dynamic evolution trend of the coupling coordination of the two systems. The QR quantile regression model was used to explore the key factors affecting the coupling coordination degree of the two systems.
RESULTS: During the observation period, the coupling coordination degree of the two systems increased from 0.393 to 0.465, with a growth rate of 18.3%. The coupling coordination degree between regions gradually decreased in the eastern-central and eastern-western regions, and there were still large differences between the central and western regions. The coupling coordination degree of the two systems in the region was significantly different in the eastern and western regions, and the central region was relatively similar. There is a positive spatial correlation between the provinces, and 25.81% of the provinces have transitions. Finally, the number of points in the first and third quadrants is higher than that in the second and fourth quadrants. In the process of dynamic distribution, the degree of polarization of the coupling coordination degree curve of the two systems is gradually weakened. Per capita GDP, residents \' income difference and population size are the positive and significant factors driving the coupling and coordinated development of the two systems.
CONCLUSIONS: The coupling and coordination degree of the two systems of medical education and health resource allocation showed a stable upward trend during the observation period, and the global spatial positive correlation also gradually increased, showing the spatial agglomeration characteristics of \' high-high agglomeration \' and \' low-low agglomeration \'. The spatial difference of coupling coordination degree shows a shrinking trend and develops towards equalization. The coupling coordination degree of the two systems is affected by social, economic and demographic factors to varying degrees. Therefore, it is necessary to innovate the coordinated development mechanism of the two systems, promote the two-way flow of medical education and health resource allocation in talents, technology and other elements, and then promote the coupling and coordinated development of the two systems.

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BACKGROUND: Patient complaints are a perennial challenge faced by health care institutions globally, requiring extensive time and effort from health care workers. Despite these efforts, patient dissatisfaction remains high. Recent studies on the use of large language models (LLMs) such as the GPT models developed by OpenAI in the health care sector have shown great promise, with the ability to provide more detailed and empathetic responses as compared to physicians. LLMs could potentially be used in responding to patient complaints to improve patient satisfaction and complaint response time.
OBJECTIVE: This study aims to evaluate the performance of LLMs in addressing patient complaints received by a tertiary health care institution, with the goal of enhancing patient satisfaction.
METHODS: Anonymized patient complaint emails and associated responses from the patient relations department were obtained. ChatGPT-4.0 (OpenAI, Inc) was provided with the same complaint email and tasked to generate a response. The complaints and the respective responses were uploaded onto a web-based questionnaire. Respondents were asked to rate both responses on a 10-point Likert scale for 4 items: appropriateness, completeness, empathy, and satisfaction. Participants were also asked to choose a preferred response at the end of each scenario.
RESULTS: There was a total of 188 respondents, of which 115 (61.2%) were health care workers. A majority of the respondents, including both health care and non-health care workers, preferred replies from ChatGPT (n=164, 87.2% to n=183, 97.3%). GPT-4.0 responses were rated higher in all 4 assessed items with all median scores of 8 (IQR 7-9) compared to human responses (appropriateness 5, IQR 3-7; empathy 4, IQR 3-6; quality 5, IQR 3-6; satisfaction 5, IQR 3-6; P<.001) and had higher average word counts as compared to human responses (238 vs 76 words). Regression analyses showed that a higher word count was a statistically significant predictor of higher score in all 4 items, with every 1-word increment resulting in an increase in scores of between 0.015 and 0.019 (all P<.001). However, on subgroup analysis by authorship, this only held true for responses written by patient relations department staff and not those generated by ChatGPT which received consistently high scores irrespective of response length.
CONCLUSIONS: This study provides significant evidence supporting the effectiveness of LLMs in resolution of patient complaints. ChatGPT demonstrated superiority in terms of response appropriateness, empathy, quality, and overall satisfaction when compared against actual human responses to patient complaints. Future research can be done to measure the degree of improvement that artificial intelligence generated responses can bring in terms of time savings, cost-effectiveness, patient satisfaction, and stress reduction for the health care system.

BACKGROUND: Primary health care is a key element in the structuring and coordination of health systems, contributing to overall coverage and performance. PHC financing is therefore central in this context, with variations in sufficiency and regularity depending on the \"political dimension\" of health systems. Research that systematically examines the political factors and arrangements influencing PHC financing is justified from a global and multidisciplinary perspective. The scoping review proposed here aims to systematically map the evidence on this topic in the current literature, identifying groups, institutions, priorities and gaps in the research.
METHODS: A scoping review will be conducted following the method proposed by Arksey and O\'Malley to answer the following question: What is known from the literature about political factors and arrangements and their influence on and repercussions for primary health care financing and resource allocation models? The review will include peer-reviewed papers in Portuguese, English or Spanish published between 1978 and 2023. Searches will be performed of the following databases: Medline (PubMed), Embase, BVS Salud, Web of Science, Scopus and Science Direct. The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Inclusion and exclusion criteria will be used for literature screening and mapping. Screening and data charting will be conducted by a team of four reviewers.
BACKGROUND: This protocol is registered on the Open Science Framework (OSF) platform, available at https://doi.org/10.17605/OSF.IO/Q9W3P.

Microorganisms are shown to actively partition their intracellular resources, such as proteins, for growth optimization. Recent experiments have begun to reveal molecular components unpinning the partition; however, quantitatively, it remains unclear how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here, we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that the cellular ability of resource partition lies in an ultrasensitive, negative feedback-controlling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism that mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations and is also efficient for biomass production over time. This work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

Although the original purpose of this article was to provide a comprehensive review of services provided for autistic children among Indigenous communities in Texas, USA, the authors\' encounter with a significant paucity in availability of data and relevant reports on Indigenous services for ASD spurred the choice of a perspective article instead as it allows a more critical view into the pitfalls surrounding the state of autism services. The meager documentation availability presents a dilemma for both researchers and Indigenous communities since it often leads to misrepresentations of data, and limits understanding of existing support systems. This perspective article addresses these issues and serves to highlight the complexity of collecting data among Indigenous populations across the United States. Specifically, it emphasizes the challenges faced in Texas, shedding light on the various barriers such as variations in cultural identity, government trust, cultural awareness, and disability identity that impede data-collection efforts in providing effective services to Indigenous populations. We advocate for a radical transformation in understanding how to approach and report the prevalence of possible ASD autism among Indigenous children to provide effective and tailored services. Ultimately, this transformation aims to secure the necessary data to provide services that effectively complement the existing support systems within individual Indigenous communities to enable their fullest and most equitable participation in society. The discussion calls for a comprehensive roadmap to achieve the goal of increasing Indigenous data collection and availability while the conclusion outlines a suggested roadmap to achieve the goals of increasing data generation and available services to Indigenous communities, and ultimately, improving services for Indigenous children with ASD in Texas and their families.

Chain elongating bacteria are a unique guild of strictly anaerobic bacteria that have garnered interest for sustainable chemical manufacturing from carbon-rich wet and gaseous waste streams. They produce C6-C8 medium-chain fatty acids which are valuable platform chemicals that can be used directly, or derivatized to service a wide range of chemical industries. However, the application of chain elongating bacteria for synthesizing products beyond C6-C8 medium-chain fatty acids has not been evaluated. In this study, we assess the feasibility of expanding the product spectrum of chain elongating bacteria to C9-C12 fatty acids, along with the synthesis of C6 fatty alcohols, dicarboxylic acids, diols, and methyl ketones. We propose several metabolic engineering strategies to accomplish these conversions in chain elongating bacteria and utilize constraint-based metabolic modelling to predict pathway stoichiometries, assess thermodynamic feasibility, and estimate ATP and product yields. We also evaluate how producing alternative products impacts the growth rate of chain elongating bacteria via resource allocation modelling, revealing a trade-off between product carbon length and class versus cell growth rate. Together, these results highlight the potential for using chain elongating bacteria as a platform for diverse oleochemical biomanufacturing and offer a starting point for guiding future metabolic engineering efforts aimed at expanding their product range.

UNASSIGNED: To evaluate the current status and equity of older adult resource allocation in the 31 provinces (autonomous regions and municipalities) of mainland China, and to offer recommendations for the optimization of these allocations.
UNASSIGNED: Four key indicators, namely, the number of older adult institutions, employees, professionals, and beds in mainland China in the year 2020, were used and analyzed using various methods and tools, including agglomeration analysis, the Gini coefficient, and the Lorenz Curve. These methods were applied to evaluate the equity of older adult resource allocation across the different provinces (autonomous regions and municipalities) and regions of China, using two dimensions, namely, the geographical area and the older adult population.
UNASSIGNED: Overall, the number of older adult resource allocations was found to be increasing in China, while the number of employees with educational levels of junior college or above was relatively low and the population structure was aging. In terms of the equity of older adult resource allocation, the results showed that this was good according to the dimensions of the older adult population but was on the low side based on the dimension of geographical area, and the Gini coefficient of the western region, in particular, was in an alarming state. Different provinces (autonomous regions and municipalities) were found to have an uneven allocation of resources for older adults, with large differences, with some areas having a serious under-allocation of resources, while others showed resource over-allocation.
UNASSIGNED: While China\'s allocation of older adult resources is relatively equitable, there is nevertheless a need to take into account recent changes in the older adult population and strengthen the construction of a reasonably structured, high-quality team of professionals and technicians, as well as consider factors such as geographical area and the older adult population, and rationally allocate older adult resources in the eastern, middle, and western regions, to achieve a balanced allocation in terms of equity and efficiency and enhance social capital, to better satisfy the demands for older adult services in older adults at multiple levels.