Factors influencing the continuity of evidence-based practice in perioperative airway management for elderly patients with fractures:A qualitative study

BACKGROUND More and more evidence-based practices are emerging,but researchers mostly focus on short-term effects,resulting in evidence-based practices not being applied in the clinic in the long term.In this study,we took the evidence-based practice of perioperative airway management in elderly fracture patients as an example and adopted a descriptive phenomenological approach to understand the influencing factors of its sustainability to provide a reference basis for promoting the continuity of evidence-based practice in the clinic.AIM To explore factors influencing the persistence of evidence-based practice in perioperative airway management in elderly patients with fractures.METHODS This study was qualitative research.Nine nurses who implemented evidencebased practice in the orthopedic ward of a tertiary comprehensive hospital in Shanghai from September 2023 to October 2023 were selected using purposive sampling as research subjects.Semi-structured interviews were conducted with them,and the data were analyzed using the Colaizzi phenomenological analysis method based on the three dimensions and ten factors of the NHS sustainability model.RESULTS Three main themes and ten subthemes were identified:Process aspects(benefits to patients,benefits to nurses,lack of follow-up,complex processes);staff aspects(insufficient human resources,inadequate training and education,lack of leadership support);and organizational environment aspects(inadequate infrastructure,poor patient compliance,poor doctor cooperation).CONCLUSION Human resources,training and education,leadership support,infrastructure,and patient-physician collaboration are important factors influencing the sustainability of evidence-based practice for perioperative airway management in older patients with fractures.

Research on the Application of Evidence-Based Quality Control Circle to Improve the Implementation Rate of Airway Management Measures in Adult Critically Ill Patients

Objective: To explore the effect of evidence-based quality control circle (QCC) in improving the implementation rate of airway management measures in adult critically ill patients. Methods: Based on the Joanna Briggs Institute (JBI) evidence-based health care model, the best evidence of airway management in adult critically ill patients was obtained and applied to the clinic. Results: The total implementation rate of airway management measures in adult critically ill patients increased from 23.62% before the implementation of quality control circle to 88.82%, and the pulmonary infection rate in critically ill patients decreased from 42.31% to 21.74%, with statistical significance between the two groups (P 0.05). Conclusion: Evidence-based quality control circle activities can standardize the practice standards of airway management in critically ill patients, reduce the occurrence of patients’ airway related complications, and improve clinical outcomes.

Intelligent Evidence-Based Management for Data Collection and Decision-Making Using Algorithmic Randomness and Active Learning

We describe here a comprehensive framework for intelligent information management (IIM) of data collection and decision-making actions for reliable and robust event processing and recognition. This is driven by algorithmic information theory (AIT), in general, and algorithmic randomness and Kolmogorov complexity (KC), in particular. The processing and recognition tasks addressed include data discrimination and multilayer open set data categorization, change detection, data aggregation, clustering and data segmentation, data selection and link analysis, data cleaning and data revision, and prediction and identification of critical states. The unifying theme throughout the paper is that of “compression entails comprehension”, which is realized using the interrelated concepts of randomness vs. regularity and Kolmogorov complexity. The constructive and all encompassing active learning (AL) methodology, which mediates and supports the above theme, is context-driven and takes advantage of statistical learning, in general, and semi-supervised learning and transduction, in particular. Active learning employs explore and exploit actions characteristic of closed-loop control for evidence accumulation in order to revise its prediction models and to reduce uncertainty. The set-based similarity scores, driven by algorithmic randomness and Kolmogorov complexity, employ strangeness / typicality and p-values. We propose the application of the IIM framework to critical states prediction for complex physical systems;in particular, the prediction of cyclone genesis and intensification.

An Evidence-Based Management Approach to HIV/AIDS in Nigeria

Objectives: This paper seeks to examine the history of HIV/AIDS in Nigeria while presenting a clear picture of some of the issues that exist in service delivery. Lastly, this paper explores how an evidence-based management approach offers an effective set of tools to HIV/AIDS organizations. Methods: Content analysis and a qualitative desk review of the literature. Results: Findings from this paper reveal that through the use of evidence-based management, preconceived notions can be challenged so as to yield a diversity of thought and a more people-centered approach to public health delivery. This paper also shows that in the Nigerian setting, an evidence-based management framework can be a transformative tool in ensuring that key populations can receive critical care and treatment in the long run despite the uncertainty that might exist when it comes to funding and resources. Conclusions: Evidence-based management is a rigorous framework that can be used for understanding how a multitude of factors can position an organization to achieve its theory of change, which in turn can lead to sustainable impact in the long run. Incorporating the use of evidence in everyday organizational behavior involves not only looking at the manner in which data is aggregated, but also how it is disseminated. In order to ensure that the evidence is not manipulated, nonprofit organizations are often viewed as being best suited for collecting evidence since they are not heavily plagued by systemic corruption and political tides, compared to their government counterparts.

The Effect of Evidence-based Management on Occupational Protection of Nurses Who Perform Chemotherapy

Objective:The study was to explore the effect of evidence-based management in occupational protection for nurses who perform chemotherapy.Methods:40 chemotherapy nurses were selected,20 of them were included in the experimental group for evidence-based management,and the other 20 were included in the control group for routine management.Results:Compared with the control group,there were significantly fewer adverse nursing events in the experimental group,and P<0.05.Conclusion:The effect of evidence-based management in occupational protection of nurses who perform chemotherapy is significant.

Application and Promotion of Whole-Process Capacity Management Model for CHF Patients Led by Specialist Nurses in “Heart Failure Center Alliance Unit”

Objective: To implement the whole-process capacity management model led by specialist nurses, improve the capacity management behavior of medical staff, and build a standardized, standardized and operable CHF capacity management system. Methods: According to the evidence pyramid principle and search strategy, 2 evidence-based nursing backbone completed literature search in both Chinese and English, and finally included 7 literatures. Results: Around the three key links of capacity assessment, monitoring and management, stakeholders were invited to evaluate each evidence according to the FAME principle, that is, the feasibility, suitability, effectiveness and clinical significance of evidence. Finally, 11 best evidences were obtained and 5 clinical review indicators of the cost project were transformed. This study formulated the competence management plan for CHF patients based on the current situation, established competence load evaluation criteria for CHF patients, and determined the target “dry weight” value for CHF patients. Conclusion: The whole-course volume management model of CHF patients guided by specialist nurses should be established and applied and promoted in the “heart failure Center Alliance unit”, so as to improve the capacity management ability of medical staff for CHF patients, enhance the self-management ability of CHF patients, improve the capacity management behavior and health outcomes, and effectively reduce the hospitalization rate and mortality rate of CHF patients in the region.

Intelligent Fault-tolerant Management of Electromechanical Equipment

In this paper, a method of intelligent fault tolerant management on electromechanical equipment is presented. It is based on condition monitoring of equipment and realized by condition prediction and condition control. An example is introduced and analyzed in this paper.

Overview of the Importance of Intelligent Approaches on Machinery Faults Diagnosis and Prediction Based on Prognostic and Health Management/Condition-Based Maintenance

Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance( CBM) and prognostic and health management( PHM) are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems( CMMS) store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It's too necessary to uncover useful knowledge from the huge amount of data.It's vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM.

Review of Fault Types, Impacts, and Management Solutions in Smart Grid Systems

Fault management study in smart grid systems (SGSs) is important to ensure the stability of the system. Also, it is important to know the major types of power failures for the effective operation of the SGS. This paper reviews diverse types of faults that might appear in the SGS and gives a survey about the impact of renewable energy resources (RERs) on the behavior of the system. Moreover, this paper offers different fault detection and localization techniques that can be used for SGSs. Furthermore, a potential fault management case study is proposed in this paper. The SGS model in this paper is investigated using both of the Matlab/Simulink and the Real Time Digital Simulation (RTDS) to compute the fault management study. Simulation results show the fast response to a power failure in the system which improves the stability of the SGS.

Development of Fault Management Dispatcher Training Simulator for TDAS in Korea

A fault management dispatcher training simulator for large-scale Distribution Automation System (TDAS) is developed to train operators in distribution control center. This simulator is composed of independent simulation server and operator consoles and can be used for network analysis, network operation, fault management and evaluation. TDAS DB is duplicated online to the simulation server keeping the data security. The system can model distribution network penetrated with distributed generations (DG) using the real data from the TDAS DB. Network fault scenarios are automatically generated by calculating fault current and generating fault indicators. Also, manual entry of cry wolf alarm is available. Moreover, operation solution for scenario of fault isolation and service restoration is generated automatically so that trainee can check their operation result. Operator actions during training session are saved and can be played back as well as displayed on one-line diagram pictures.

The Design of Management Software for Network Device Faults

Effective network management software ensures networks to run credibly. In this paper we discuss the design and implementation of network device fault management based on Pure Java. It includes designs of general functions, server functions, client functions and a database table. The software can make it convenient to monitoring a network device, and improve network efficiency.

Hepatocellular carcinoma: From clinical practice to evidence-based treatment protocols

Hepatocellular carcinoma(HCC) is one of the major malignant diseases in many healthcare systems. The growing number of new cases diagnosed each year is nearly equal to the number of deaths from this cancer. Worldwide, HCC is a leading cause of cancerrelated deaths, as it is the fifth most common cancer and the third most important cause of cancer related death in men. Among various risk factors the two are prevailing: viral hepatitis, namely chronic hepatitis C virus is a well-established risk factor contributing to the rising incidence of HCC. The epidemic of obesity and the metabolic syndrome, not only in the United States but also in Asia, tend to become the leading cause of the long-term rise in the HCC incidence. Today, the diagnosis of HCC is established within the national surveillance programs in developed countries while the diagnosis of symptomatic, advanced stage disease still remains the characteristic of underdeveloped countries. Although many different staging systems have been developed and evaluated the BarcelonaClinic Liver Cancer staging system has emerged as the most useful to guide HCC treatment. Treatment allocation should be decided by a multidisciplinary board involving hepatologists, pathologists, radiologists, liver surgeons and oncologists guided by personalized-based medicine. This approach is important not only to balance between different oncologic treatments strategies but also due to the complexity of the disease(chronic liver disease and the cancer) and due to the large number of potentially efficient therapies. Careful patient selection and a tailored treatment modality for every patient, either potentially curative(surgical treatment and tumor ablation) or palliative(transarterial therapy, radioembolization and medical treatment, i.e., sorafenib) is mandatory to achieve the best treatment outcome.

The implementation and evaluation of HIV symptom management guidelines: A preliminary study in China

Objective:The overarching objective of this study was to examine the effectiveness of HIV symptom management guidelines in China in reducing the incidence and severity of symptoms and improving patients'quality of life.Methods:We conducted a controlled,pre-and post-implementation design in the HIV/AIDS inpatient unit in Shanghai.Patients recruited from November 2014 to February 2015 were in the intervention group and those from October 2013 to February 2014 were in the control group.There were 74 patients in each group.Participants in the intervention group received interventions based on the HIV symptom management guidelines.Overall symptom severity,depression,and quality of life were measured in two groups at baseline,week 4,and week 8.Results:Totally 126 patients completed the research,65 in the intervention group and 61 in the control group.The total symptom severity scores showed a statistically significant difference between groups across time(P<0.05).It showed that frequencies of fatigue(36.9%vs.44.3%),fever(6.2%vs.11.5%),loss in weight(9.2%vs.16.4%),mouth ulcers(12.3%vs.16.4%),headaches(9.2%vs.19.7%)and depression(F=1.09,P>0.05)in the intervention group were lower than those in the control group in week 8 without statistical significance.The multilevel growth mixture model indicated a greater increase in the total score of quality of life for the group treated according to the symptom management guidelines(P=0.04).Conclusion:The evidence-based HIV symptom management guidelines can improve a patient's quality of life and relieve negative symptoms.The guidelines can be applied in a similar context to other HIV/AIDS units or clinics.

Risk Management of Key Issues of FPSO

Risk analysis of key systems have become a growing topic late of because of the development of offshore structures. Equipment failures of offioading system and fire accidents were analyzed based on the floating production, storage and offioading （FPSO） features. Fault tree analysis （FTA）, and failure modes and effects analysis （FMEA） methods were examined based on information already researched on modules of relex reliability studio （RRS）. Equipment failures were also analyzed qualitatively by establishing a fault tree and Boolean structure function based on the shortage of failure cases, statistical data, and risk control measures examined. Failure modes of fire accident were classified according to the different areas of fire occurrences during the FMEA process, using risk priority number （RPN） methods to evaluate their severity rank. The qualitative analysis of FTA gave the basic insight of forming the failure modes of FPSO offioading, and the fire FMEA gave the priorities and suggested processes. The research has practical importance for the security analysis problems of FPSO.

Fault Aware Dynamic Resource Manager for Fault Recognition and Avoidance in Cloud

Fault tolerance(FT)schemes are intended to work on a minimized and static amount of physical resources.When a host failure occurs,the conventional FT frequently proceeds with the execution on the accessible working hosts.This methodology saves the execution state and applications to complete without disruption.However,the dynamicity of open cloud assets is not seen when taking scheduling choices.Existing optimization techniques are intended in dealing with resource scheduling.This method will be utilized for distributing the approaching tasks to the VMs.However,the dynamic scheduling for this procedure doesn’t accomplish the objective of adaptation of internal failure.The scheme prefers jobs in the activity list with the most elevated execution time on resources that can execute in a shorter timeframe,but it suffers with higher makespan;poor resource usage and unbalance load concerns.To overcome the above mentioned issue,Fault Aware Dynamic Resource Manager(FADRM)is proposed that enhances the mechanism to Multi-stage Resilience Manager at an application-level FT arrangement.Proposed FADRM method gives FT a Multi-stage Resilience Manager(MRM)in the client and application layers,and simultaneously decreases the over-head and degradations.It additionally provides safety to the application execution considering the clients,application and framework necessities.Based on experimental evaluations,Proposed Fault Aware Dynamic Resource Manager(FADRM)method 157.5 MakeSpan(MS)time,0.38 Fault Rate(FR),0.25 Failure Delay(FD)and improves 5.5 Performance Improvement Ratio(PIR)for 25,50,75 and 100 tasks and 475 MakeSpan(MS)time,0.40 Fault Rate(FR),1.30 Failure Delay(FD)and improves 6.75 improves Performance Improvement Ratio(PER)for 100,200,300 and 500 Tasks compare than existing methodologies.

Design of a Prognostics and Health Management System for Electromechanical Equipment Through Time Stress Analysis

Time stress includes all kinds of environment and operating stress such as shock, vibration, temperature and electric current that the electromechanical system suffers in the manufacture, transport and operating process. In this paper, the conception of time stress and prognostics and health management （ PHM） system are introduced. Then, in order to improve the false alarm recognition and fault prediction capabilities of the electromechanical equipment, a novel PHM architecture for electromechanical equipment is put forward based on a built-in test （BIT） system design technology and time stress analysis method. Finally, the structure, the design and implementing method and the functions of each module of this PHM system are described in detail.

Study on Service Level Management in Integrated Satellite Information Network

Integrated Satellite Information Network (ISIN) includes those nodes in space and those on ground. It is the way to realize the fusion of satellite communication and traditional network technology. A satellite network management system based on Multiplex Network Management Protocol (MNMP) has accomplished traditional management, such as configuration, performance and fault management. An architecture of Service Level Management (SLM) in ISIN is proposed, and a service topology management and Service Level Agreement (SLA) are deeply researched. At last, service security and fault management are briefly discussed, and a simulation system is accomplished.

Safety-assured,real-time neural active fault management for resilient microgrids integration

Federated-learning-based active fault management(AFM)is devised to achieve real-time safety assurance for microgrids and the main grid during faults.AFM was originally formulated as a distributed optimization problem.Here,federated learning is used to train each microgrid’s network with training data achieved from distributed optimization.The main contribution of this work is to replace the optimization-based AFM control algorithm with a learning-based AFM control algorithm.The replacement transfers computation from online to offline.With this replacement,the control algorithm can meet real-time requirements for a system with dozens of microgrids.By contrast,distributed-optimization-based fault management can output reference values fast enough for a system with several microgrids.More microgrids,however,lead to more computation time with optimization-based method.Distributed-optimization-based fault management would fail real-time requirements for a system with dozens of microgrids.Controller hardware-in-the-loop real-time simulations demonstrate that learning-based AFM can output reference values within 10 ms irrespective of the number of microgrids.

Fault diagnosis and analysis of main sea water pump based on vibration monitoring in offshore oil field

The main sea water pump is the key equipment for the floating production storage and offloading （FPSO）. Affected by some factors such as hull deformation, sea water corrosion, rigid base and pipeline stress, the vibration value of main sea water pump in the horizontal direction is abnormally high and malfunctions usually happen. Therefore, it is essential to make fault diagnosis of main sea water pump, By conventional off-line monitoring and vibration amplitude spectrum analysis, the fault cycle is found and the alarm value and stop value of equipment are set, which is helpful to equipment maintenance and accident prevention.

Network Fault Diagnosis Using DSM

Difference similitude matrix (DSM) is effective in reducing information system with its higher reduction rate and higher validity. We use DSM method to analyze the fault data of computer networks and obtain the fault diagnosis rules. Through discretizing the relative value of fault data, we get the information system of the fault data. DSM method reduces the information system and gets the diagnosis rules. The simulation with the actual scenario shows that the fault diagnosis based on DSM can obtain few and effective rules. Key words computer networks - data reduction - fault management - difference-similitude matrix CLC number TP 393 Foundation item: Supported by the National Natural Science Foundation of China (90204008)Biography: Jiang Hao (1976-), male, Ph. D candidate, research direction: computer network, data mine.