Perceptions of Collaboration and Satisfaction with Collaboration Regarding Care Decision-Making in Intensive Care Units in Japan: A National Survey

Multi-professional collaboration is being promoted worldwide as a response to the need for sophisticated medical care and for catering to patients’ diverse needs. Patients in Intensive Care Units (ICUs) are seriously ill, and their families may be at risk depending on the patient’s situation. Considering these characteristics of patients and families, there is a strong need for multi-professional collaboration within ICUs. The purpose of this descriptive study was to examine recognition and other factors related to collaboration and satisfaction involving care decisions in Japanese ICUs. A mail survey about collaboration of activities and systems was sent to physicians, clinical engineers, and nurses working in ICUs in Japan, 387 consented to participate in this study. Results showed that satisfaction scores were generally high among the three aforementioned professions, but collaboration scores on deciding care for patients showed significant differences (p < 0.05). The total collaboration score was the highest among physicians (36.7 ± 6.7 points), followed by nurses (32.8 ± 7.4 points), and CEs (32.8 ± 7.4 points). The factors that commonly affected collaboration scores were the satisfaction score and the ability to collaborate with other professionals and set team medical care as a goal. Moreover, it is worth noting that the degree of difficulty in collaboration negatively affected this factor. On the other hand, other factors differed among the three professions, suggesting that the purpose and need for collaboration differ depending on the profession.

Clinical decision making on the use of physical restraint in intensive care units

Physical restraint is a common nursing intervention in intensive care units and nurses often use it to ensure patients'safety and to prevent unexpected accidents.However,existing literature indicated that the use of physical restraint is a complex one because of inadequate rationales,the negative physical and emotional effects on patients,but the lack of perceived alternatives.This paper is aimed to interpret the clinical decision-making theories related to the use of physical restraint in intensive care units in order to facilitate our understanding on the use of physical restraint and to evaluate the quality of decisions made by nurses.By reviewing the literature,intuition and heuristics are the main decision-making strategies related to the use of physical restraint in intensive care units because the rapid and reflexive nature of intuition and heuristics allow nurses to have a rapid response to urgent and emergent cases.However,it is problematic if nurses simply count their decision-making on experience rather than incorporate research evidence into clinical practice because of inadequate evidence to support the use of physical restraint.Besides that,such a rapid response may lead nurses to make decisions without adequate assessment and thinking and therefore biases and errors may be generated.Therefore,despite the importance of intuition and heuristics in decision-making in acute settings on the use of physical restraint,it is recommended that nurses should incorporate research evidence with their experience to make decisions and adequate assessment before implementing physical restraint is also necessary.

Optimal Selection of Hybrid Renewable Energy System Using Multi-Criteria Decision-Making Algorithms

Several models of multi-criteria decision-making(MCDM)have identified the optimal alternative electrical energy sources to supply certain load in an isolated region in Al-Minya City,Egypt.The load demand consists of water pumping system with a water desalination unit.Various options containing three different power sources:only DG,PV-B system,and hybrid PV-DG-B,two different sizes of reverse osmosis(RO)units;RO-250 and RO-500,two strategies of energy management;load following(LF)and cycle charging(CC),and two sizes of DG;5 and 10 kW were taken into account.Eight attributes,including operating cost,renewable fraction,initial cost,the cost of energy,excess energy,unmet load,breakeven grid extension distance,and the amount of CO_(2),were used during the evaluation process.To estimate these parameters,HOMER®software was employed to perform both the simulation and optimization process.Four different weight estimation methods were considered;no priority of criteria,based on a pairwise comparisons matrix of the criteria,CRITIC-method,and entropy-based method.The main findings(output results)confirmed that the optimal option for the case study was hybrid PV-DG-B with the following specification:5 kW DG,RO-500,and load following control strategy.Under this condition,the annual operating cost and initial costs were$5546 and$161022,respectively,whereas the cost of energy was 0.077$/kWh.The excess energy and unmet loads were 40998 and 2371 kWh,respectively.The breakeven grid extension distance and the amount of CO_(2) were 3.31 km and 5171 kg per year,respectively.Compared with DG only,the amount of CO_(2) has been sharply reduced by 113939 kg per year.

Aspect based sentiment analysis using multi-criteria decision-making and deep learning under COVID-19 pandemic in India

The COVID-19 pandemic has a significant impact on the global economy and health.While the pandemic continues to cause casualties in millions,many countries have gone under lockdown.During this period,people have to stay within walls and become more addicted towards social networks.They express their emotions and sympathy via these online platforms.Thus,popular social media(Twitter and Facebook)have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID-19-related issues.We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases.The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus.India-specific COVID-19 tweets have been annotated,for analysing the sentiment of common public.To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35%for Lockdown and 83.33%for Unlock data set.The suggested method outperforms many of the contemporary approaches(long shortterm memory,Bi-directional long short-term memory,Gated Recurrent Unit etc.).This study highlights the public sentiment on lockdown and stepwise unlocks,imposed by the Indian Government on various aspects during the Corona outburst.

Vigilance in Nurses Working in Intensive Care Units

Background and Aim: Vigilance is an essential element in intensive care nursing. This study was conducted to determine nursing vigilance in nurses working in the intensive care units of educational and medical centers in Ardabil, Iran. Methods: This was a cross-sectional descriptive-analytical study with 192 ICU nurses as the participants. The data were obtained through questionnaires regarding demographic characteristics and nursing vigilance. SPSS software version 24 was used for the statistical analysis. Results: The mean total vigilance score was 3.86 ± 0.23 of 5. The mean scores of the timely diagnosis of changes, pattern recognition, and clinical decision-making subscales were 4.07 ± 0.26, 04.04 ± 0.41, and 3.44 ± 0.25, respectively. No significant relationships were observed between the total or subscale vigilance scores and other demographic characteristics. Conclusion: We assessed ICU nurses’ vigilance behaviors and found that their mean vigilance score was higher than the expected average, indicating our participants had a high level of clinical vigilance. These results suggest a need for effective educational interventions to boost clinical decision-making skills in ICU nurses, especially younger nurses.

Data envelopment analysis procedure with two non-homogeneous DMU groups

The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.

Classifying and ranking DMUs in interval DEA

During efficiency evaluating by DEA, the inputs and outputs of DMUs may be intervals because of insufficient information or measure error. For this reason, interval DEA is proposed. To make the efficiency scores more discriminative, this paper builds an Interval Modified DEA (IMDEA) model based on MDEA. Furthermore, models of obtaining upper and lower bounds of the efficiency scores for each DMU are set up. Based on this, the DMUs are classified into three types. Next, a new order relation between intervals which can express the DM’s preference to the three types is proposed. As a result, a full and more convictive ranking is made on all the DMUs. Finally an example is given.

Development of a Decision Aid for Family Surrogate Decision Makers of Critically Ill Patients Requiring Renal Replacement Therapy in ICU:A User-Centered Design for Rapid Prototyping

Objectives Renal replacement therapy(RRT)is increasingly adopted for critically ill patients diagnosed with acute kidney injury,but the optimal time for initiation remains unclear and prognosis is uncertain,leading to medical complexity,ethical conflicts,and decision dilemmas in intensive care unit(ICU)settings.This study aimed to develop a decision aid(DA)for the family surrogate of critically ill patients to support their engagement in shared decision-making process with clinicians.Methods Development of DA employed a systematic process with user-centered design(UCD)principle,which included:(i)competitive analysis:searched,screened,and assessed the existing DAs to gather insights for design strategies,developmental techniques,and functionalities;(ii)user needs assessment:interviewed family surrogates in our hospital to explore target user group's decision-making experience and identify their unmet needs;(iii)evidence syntheses:integrate latest clinical evidence and pertinent information to inform the content development of DA.Results The competitive analysis included 16 relevant DAs,from which we derived valuable insights using existing resources.User decision needs were explored among a cohort of 15 family surrogates,revealing four thematic issues in decision-making,including stuck into dilemmas,sense of uncertainty,limited capacity,and delayed decision confirmation.A total of 27 articles were included for evidence syntheses.Relevant decision making knowledge on disease and treatment,as delineated in the literature sourced from decision support system or clinical guidelines,were formatted as the foundational knowledge base.Twenty-one items of evidence were extracted and integrated into the content panels of benefits and risks of RRT,possible outcomes,and reasons to choose.The DA was drafted into a web-based phototype using the elements of UCD.This platform could guide users in their preparation of decision-making through a sequential four-step process:identifying treatment options,weighing the benefits and risks,clarifying personal preferences and values,and formulating a schedule for formal shared decision-making with clinicians.Conclusions We developed a rapid prototype of DA tailored for family surrogate decision makers of critically ill patients in need of RRT in ICU setting.Future studies are needed to evaluate its usability,feasibility,and clinical effects of this intervention.

基于PI控制的内燃动车组柴油机恒功率控制技术

柴油机在非恒功率输出时,不仅燃料效率低,而且可能会产生较大的机械应力,导致机械部件的磨损和破坏。为确保内燃动车组柴油机高效运行,基于内燃动车组柴油发电机组恒功率输出的运行模式,文章提出了一种比例-积分控制方法,实现了负载侧牵引系统功率稳定跟随柴油发电机组的输出功率目标值,通过负载侧恒功率运行保障发电机组的恒功率稳定输出,从而提高柴油机燃油经济性。经过仿真及试验测试验证,采用此控制方法,负载功率稳态波动在±2%以内,实现了内燃动车组柴油机恒功率运行及负载功率对目标值的实时跟随。

数据包络分析方法在高校院系绩效评价中的应用

科学评价高等教育绩效对于优化高等教育资源配置、增强高校办学活力具有积极意义.应用数据包络分析方法(DEA),以M大学相关学院近3年的资源投入与产出数据为例,测算学院相对效率.并对DEA无效学院提出资源配置的改进建议.

DEA在政府社会管理职能绩效评估中的应用研究——以湖南省为例

政府社会管理职能绩效评估是政府社会管理与政府绩效评估面临的重点和难点问题。构建DEA绩效评估模型,对政府社会管理职能绩效进行实证评估,并对DEA在政府社会管理职能绩效评估中的应用方法和注意事项进行有益探讨。研究结果表明,DEA可以比较客观、简约、直观地评价政府社会管理职能的相对有效性,可以帮助政府部门准确掌握社会管理职能绩效水平,DEA在处理多指标输入和多指标输出的有效性评价方面具有明显的优势,特别适合政府社会管理职能这种复杂系统的绩效评估和改进。在运用DEA时,应注意DEA的使用条件和局限性,可依据评估目的进行适当的改进和拓展。

基于数据包络分析(DEA)的物流业可持续发展有效性评价

本文从物流业可持续发展研究现状出发,分析了数据包络分析方法用于物流业可持续发展评价的可行性,运用数据包络分析模型对中国31个省、市、自治区物流业可持续发展状况进行了实证分析。研究数据显示,所评价地区的物流业可持续发展整体有效率为32.258%,发展水平较低,而且西部与中、东部发展存在明显差距,这就需要加大物流业可持续发展投入力度,不断调整和优化投入结构,以实现物流业的可持续发展。结果表明,数据包络分析方法可以科学、合理地评价物流业可持续发展,为系统效率变化及其改进措施提供了新的方法和思路。

基于改进DEA模型的工业企业技术创新能力评价

针对传统数据包络分析(DEA)方法的C2R模型存在的无法对有效的决策单元加以区分以及输入和输出指标权重分配不合理问题,通过引入两个虚拟决策单元,建立了区分有效决策单元的改进DEA模型。利用该模型可以求得各决策单元的公共权向量,从而实现了对所有决策单元的区分和排序。通过将该模型应用于工业企业技术创新能力评价,验证了该模型可以区分传统C2R模型求得的有效决策单元,并使对决策单元的评价更为合理。

基于DEA方法的额外资源分配算法

研究基于DEA(数据包络分析)方法的资源分配问题.求解该类问题的难点在于:对于参与分配的决策单元来说,其分得的额外资源数不仅依赖于该决策单元的相对效率值,还依赖于它的规模大小,因此分配权重难以确定.根据输入、输出指标数的分布情况,建立了3种基本模型,分别是单输入单输出、多输入单输出、单输入多输出模型,给出了这3种模型的资源分配权重的确定算法.最后给出实例,并对给出的分配原则的合理性进行了分析讨论.

模糊条件下的决策单元相对有效性评价

研究了模糊条件下决策单元的相对有效性评价问题。首先分析了模糊性因素对决策单元相对有效性的影响;然后根据模糊规划取截集方法和DEA评价的经济含义,给出了模糊DEA模型的求解方法;最后定义了决策单元的模糊DEA有效性以及进行有效性排序的平均置信有效性。文末是一个模糊DEA应用的例子。

一种可用于生产效率评价的灰靶评估算法

本文在分析和比较了DEA和灰靶评估两种方法之后,给出一种可用于生产效率评价的灰靶评估算法。该算法由于运用了DEA方法中的“生产效率”概念,弥补了灰靶评估算法不能对不同的被评价单元进行效率评价的不足,从而拓宽了灰靶评估算法的应用背景。文章最后给出实例分析。

基于模糊DEA的心理战战法评估

根据心理战战法特点,建立了心理战战法模糊DEA评估模型。根据模糊规划取截集方法和DEA评价的经济含义,给出了模糊DEA模型的求解方法。文末是一个心理战战法评估的例子。

基于期望值方法的随机DEA综合模型及应用

对环境约束下包含不可控输入、非期望输出的DEA综合模型的相对有效性进行研究,给出决策单元有效的定义及定理。进一步提出了随机条件下决策单元的期望有效性指数概念和相对有效性评价的期望值方法,最后给出了计算实例。

一种基于DEA的额外卫生资源分配算法的运用

目的研究基于DEA(数据包络分析)方法的资源分配问题求解,并将模型运用于卫生资源分配。方法运用DEAP2.1软件,根据效率指标和实际投入计算11所市级妇幼保健院的额外卫生资源分配权重。结果额外资源分配权重不仅考虑该决策单元的相对效率值,还依赖于它的规模大小,根据输入、输出指标数的分布情况,运用单输入多输出模型,给出了资源分配权重的确定算法,最后给出实例。结论 DEA额外资源分配模型在确定分配权重时,避免了经验主义与平均主义的传统做法。利用该模型,管理者或决策者在进行额外分配资源时将更多地考虑到整个系统的效率,使得该分配对整个系统而言是最优的。

DEA扩展有效的鲁棒性

通过给出决策单元为DEA扩展有效的几个等价命题,来研究扩展有效决策单元的鲁棒性。得到了当输入增加或输出减少后,它仍然保持扩展有效性的一些充分必要条件,还给出了保持扩展有效的判断方法和数值实例,而该方法不需要求文献[3]中的最优基矩阵的逆矩阵,也不需要求解文献[5]中的线性方程组。