公立医院与社会资本的合作之势在“何”行

在国家和地方的政策强力推动下,以社会资本进入医疗领域为核心的改革成为医改主要方向。对公立医院与社会资本合作的有效模式的积极探索对于主要的利益相关方将有明显的多赢效应。在实际合作过程中,需要从经营理念的转换、战略方向的把握、试点资格的审核和政策的支持等方面进行不断地磨合与探索。     

居民健康卡金融功能应用模式探讨

阐述了居民健康卡金融应用意义,分析了居民健康卡实现金融功能的相关技术基础,探讨了居民健康卡加载银行账户、银行卡绑定居民健康卡、居民健康卡动态绑定银行卡加储值卡等金融功能实现方法及相关应用。     

医院软实力建设的内涵与把握原则

??????? 随着医药卫生体制改革不断深化,加强医院软实力建设,对于实现医院可持续性发展具有积极的意义。现代医院软实力内涵主要体现在制度吸引力、文化感染力、团队凝聚力及品牌辐射力四个方面。医院软实力是医院硬实力的内在动力,是医院实现可持续发展的基础和重要保证。因此,在医院软实力建设过程中必须坚持系统性、科学性、超前性及实效性原则。     

护理人员个体因素对薪酬满意度影响的调查与分析

?????? 目的 通过对护理人员个体因素薪酬满意度的调查,了解护理人员个体因素对薪酬满意度的影响。 方法 应用方差分析和均值计算,判断护理人员个体因素的薪酬满意度及其影响。 结果 护理人员个体因素与薪酬满意度有显著差异（P﹤0.05）。年龄、工作年限、学历等因素对薪酬满意度的影响程度不同。 结论 护理人员对薪酬满意度整体满意度水平较低,年龄、工作年限、学历等因素是护理人员薪酬满意度的影响因素。     

影响上海市临床医师对基因技术与生命伦理认知的因素

通过上海市临床医师问卷调查,应用Logistic模型分析临床医师对基因技术与生命伦理认知的影响因素。结果显示,临床医师的性别、年龄、学历和职称等人口学因素主要影响对基因技术优势的认知,基因工作经历、伦理委员会任职经历、对伦理与相关法规的知晓度主要影响对基因技术风险的认知。建议加强基因伦理与相关法规教育,重视部属或市属综合性医院基因技术研究与应用的管理。     

六西格玛管理法对围手术期服务质量改进的影响研究

目的 设计了综合医院围手术期六西格玛管理模式,并进行了试验研究,以评价应用效果。 方法 采用干预性研究方法,设立干预组和对照组。制定和筛选出评价指标,根据前后统计结果,判断总体改善和指标的变化情况。 结果 干预组总体有明显的改善,对照组总体改善不明显;干预组评价指标横比、纵比均有明显的改进。结论 围手术期六西格玛管理模式的应用可明显改善医院医疗服务质量,对医疗服务行为有较大的良性影响,并有利于医院文化建设。     

门诊知名专家团队服务模式的实践与探索

为深化公立医院改革,北京同仁医院积极开展门诊知名专家团队服务模式试点工作,建立医院内部层级诊疗服务新模式。通过门诊就诊流程调整、服务模式变革,破解“挂号难”“号贩子”等相关问题,实现了医院内部门诊资源的优化利用,是医院内部分级诊疗的有益实践与探索,真正体现了医疗机构“以患者为中心”的服务理念,也为未来广泛推广分级诊疗模式奠定了坚实的基础。     

医疗纠纷案例处理方式的Meta分析

目的 综合分析协商、调解、诉讼等医疗纠纷处理方式的使用情况,以期为完善医疗纠纷处理机制提供参考。方法 搜索近年研究医疗纠纷的相关文献,运用Meta分析方法对医疗纠纷案例研究中的数据进行统计和处理,分析各种医疗纠纷处理方式的使用分布情况。结果 在引入医疗纠纷人民调解之前,文献研究中各种处理方式所占比例分别为：双方协商解决65%、卫生行政调解23%、诉讼19%。而在引入医疗纠纷人民调解之后,文献研究中各种处理方式所占比例分别为双方协商解决75%、医疗纠纷人民调解17%、卫生行政调解1%、诉讼6%。结论 医患双方协商解决仍为目前医疗纠纷的主要处理方式,随着医疗纠纷人民调解的逐步发展,多元化的医疗纠纷处理机制将日趋完善。     

医患沟通信息服务平台的构建

介绍了建立医患沟通信息服务平台的意义、平台系统的构成和主要功能、平台的科学性和创新性。该平台畅通了医患沟通渠道,拓宽了服务范畴,提升了服务水平,具有广阔的推广和发展前景。     

Autonomic resource management in virtualized data centers using fuzzy logic-based approaches

Data centers, as resource providers, are expected to deliver on performance guarantees while optimizing resource utilization to reduce cost. Virtualization techniques provide the opportunity of consolidating multiple separately managed containers of virtual resources on underutilized physical servers. A key challenge that comes with virtualization is the simultaneous on-demand provisioning of shared physical resources to virtual containers and the management of their capacities to meet service-quality targets at the least cost. This paper proposes a two-level resource management system to dynamically allocate resources to individual virtual containers. It uses local controllers at the virtual-container level and a global controller at the resource-pool level. An important advantage of this two-level control architecture is that it allows independent controller designs for separately optimizing the performance of applications and the use of resources. Autonomic resource allocation is realized through the interaction of the local and global controllers. A novelty of the local controller designs is their use of fuzzy logic-based approaches to efficiently and robustly deal with the complexity and uncertainties of dynamically changing workloads and resource usage. The global controller determines the resource allocation based on a proposed profit model, with the goal of maximizing the total profit of the data center. Experimental results obtained through a prototype implementation demonstrate that, for the scenarios under consideration, the proposed resource management system can significantly reduce resource consumption while still achieving application performance targets.

Identifying Lowest‐Emission Choices and Environmental Pareto Frontiers for Wastewater Treatment Wastewater Treatment Input‐Output Model based Linear Programming

This article proposes a linear programming model that is based on the wastewater treatment input‐output model (W²IO) to identify the lowest‐emission choice among alternative feasible options for wastewater treatment; this model can be considered as an application of the waste input‐output linear programming model (WIO‐LP) to wastewater issues. Using the data of the Tokyo metropolitan W²IO table, I apply this model to obtain the optimal wastewater treatment options under alternative scenarios. The Pareto frontiers of environmental loads are derived to show the trade‐off relationships among various types of environmental load and the effect of the introduction of high‐temperature incineration of dewatered sludge on the generation of environmental loads. The main conclusion of the study is that when all three types of environmental load (landfill level, global warming potential, and chemical oxygen demand) are considered, the introduction of high‐temperature incineration causes the widening of the Pareto frontier of environmental loads and also causes it to move closer to the origin.     

Minimizing invader impacts: striking the right balance between removal and restoration

Invasive species can cause severe damage in their introduced range; this damage often persists even after removal of the invader. In order to efficiently allocate a limited budget between invader removal and restoration of habitat from which the invader has been removed, it is vital to quantify the impacts of the invasion within an economic context. Here we develop optimal management strategies for biological invasions, which minimize both the direct economic costs of removal and restoration, and the ecological costs of present and future damage caused by the invasion. We demonstrate how this can be formulated as a linear programming problem, enabling the fast and efficient computation of optimal solutions. Using a simple example, we outline some general principles for the optimal control of an invader that damages its environment. Notably, we show that the most effective strategies often switch the priority of removal and restoration over time, and outline the conditions under which restoration is prioritized over removal. The proportion of total funds allocated to restoration will depend on the annual budget, the persistence of damage, and the relative costs of damage, removal and restoration.     

The influence of a positive correlation between clutch size and offspring fitness on the optimal offspring size

Summary The effect is modeled of a positive relationship between clutch size and offspring fitness on the optimal investment in offspring. In species which meet the assumptions of the model, the model predicts a positive correlation between maternal resource level and offspring size. If larger mothers are able to allocate more resources to offspring, then the model would also predict a positive correlation between maternal size and offspring size when the assumptions of the model are met. Thus, this model may help explain both among and within individual variation in offspring size. When offspring are produced in groups and the number of offspring killed per clutch is limited by predator satiation, offspring in larger clutches may experience a higher probability of survival. Such a life style may be found in animals such as sea turtles. Offspring size is positively correlated with maternal size in some members of this group.     

Investigating the potential use of aerial line transect surveys for estimating polar bear abundance in sea ice habitats: A case study for the Chukchi Sea

The expense of traditional capture‐recapture methods, interest in less invasive survey methods, and the circumpolar decline of polar bear (Ursus maritimus) habitat require evaluation of alternative methods for monitoring polar bear populations. Aerial line transect distance sampling (DS) surveys are thought to be a promising monitoring tool. However, low densities and few observations during a survey can result in low precision, and logistical constraints such as heavy ice and fuel and safety limitations may restrict survey coverage. We used simulations to investigate the accuracy and precision of, DS for estimating polar bear abundance in sea ice habitats, using the Chukchi Sea subpopulation as an example. Simulation parameters were informed from a recent pilot survey. Predictions from a resource selection model were used for stratification, and we compared two ratio estimators to account for areas that cannot be sampled. The ratio estimator using predictions of resource selection by polar bears allowed for extrapolation beyond sampled areas and provided results with low bias and CVs ranging from 21% to 36% when abundance was >1,000. These techniques could be applied to other DS surveys to allocate effort and potentially extrapolate estimates to include portions of the landscape that are logistically impossible to survey.     

Dynamics of internal carbon resources during masting behavior in trees

Several proximate factors of masting have been provided. Here, I focus on the role of internal factors, especially the relationship between internal carbon resources and modular structures in trees. I summarize various studies of carbon resource allocation for reproduction during masting events in terms of the proximate factors of masting and discuss the modular structure in which trees accumulate and consume carbon resources as well as the timing when internal carbon resources affect masting since trees have complex resource dynamics among organs. The resource budget model, which provides a simple mechanistic explanation of the masting mechanism, is supported by various study lines. This model assumes decreasing levels of stored photosynthate after flowering and fruiting. According to several studies, however, carbon reserves do not decrease after fruiting in species in which the modules autonomously allocate current photosynthate for fruiting. In addition, it is important to elucidate when carbon resources affect masting events because during their long developmental processes, trees pass through various stages until they produce maturing fruits to create successful masting events. To explore the mechanisms of masting in future studies, it would be important to figure out how and when candidate factors (including nutrients other than carbon) may influence the entire reproduction process, for example, using field manipulation experiments.     

A simple approach to optimal control of invasive species

The problem of invasive species and their control is one of the most pressing applied issues in ecology today. We developed simple approaches based on linear programming for determining the optimal removal strategies of different stage or age classes for control of invasive species that are still in a density-independent phase of growth. We illustrate the application of this method to the specific example of invasive Spartina alterniflora in Willapa Bay, WA. For all such systems, linear programming shows in general that the optimal strategy in any time step is to prioritize removal of a single age or stage class. The optimal strategy adjusts which class is the focus of control through time and can be much more cost effective than prioritizing removal of the same stage class each year.     

Fair Scheduling of General-Purpose Workloads on Workstation Clusters

In this paper we present a scheduling strategy for workstation clusters able to effectively and fairly schedule general-purpose workloads potentially made up by compute-bound, interactive, and I/O-intensive applications, that may each be sequential, client-server, or parallel. The scheduling strategy allocates resources to processes of the same parallel applications in such a way that they all get the same CPU share regardless of the level of resource contention on the respective machines, and relies on an extended stride scheduler to fairly allocate individual workstations. A simulation analysis carried out for a variety of workloads and operational conditions shows that our strategy (a) delivers good performance to all the applications classes composing general-purpose workloads, (b) fairly allocates resources among competing applications, and (c) outperforms alternative strategies.     

Integrated framework of system dynamics and meta-heuristic for multi-objective land use planning problem

Land use optimization as a resource allocation problem can be defined as the process of assigning different land uses to a region. Sustainable development also involves the exploitation of environmental resources, investment orientation, technology development, and industrial changes in a coordinated form. This paper studies the multi-objective sustainable land use planning problem and proposes an integrated framework, including simulation, forecasting, and optimization approaches for this problem. Land use optimization, a multifaceted process, requires complex decisions, including selection of land uses, forecasting land use allocation percentage, and assigning locations to land uses. The land use allocation percentage in the selected horizons is simulated and predicted by designing a System Dynamics (SD) model based on socio-economic variables. Furthermore, land use assignment is accomplished with a multi-objective integer programming model that is solved using augmented ε-constraint and non-dominated sorting genetic algorithm II (NSGA-II) methods. According to the results of the SD model, land use changes depend on population growth rate and labor productivity variables. Among the possible scenarios, a scenario focusing more on sustainable planning is chosen and the forecasting results of this scenario are used for optimal land use allocation. The computational results show that the augmented ε-constraint method cannot solve this problem even for medium sizes. The NSGA-II method not only solves the problem at large sizes over a reasonable time, but also generates good-quality solutions. NSGA-II showed better performance in metrics, including number of non-dominated Pareto solutions (NNPS), mean ideal distance (MID), and dispersion metric (DM). Integrated framework is implemented to allocate four types of land uses consisting of residential, commercial, industrial, and agricultural to a given region with 900 cells.