The objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association between ADE incidence and resident and facility characteristics. We extracted data from 755 medical charts and conducted 33 staff surveys. There were 6.13 ADEs per 100 residents per month. More than half were fall‐related (51.1%), and half of those were due to hypotension. Regression analysis revealed significant associations between ADEs and opioid analgesics, psychotropic medications, warfarin, skilled care, consultant pharmacist accessibility, nurse‐physician collaboration, CNA vital sign assessment skills, number of physician visits, nurse workload, and use of electronic health records. Five resident characteristics (skilled care, dementia, use of opioids, warfarin, psychotropics) and variables from 5 domains of the facility work system (organization, task, environment, person, technology) had significant associations with ADE incidence. The SEIPS model successfully identified work system factors influencing ADEs in NHs.
The continued acceleration in the business environment has led to the need for organizations great attention to quality applied in organizations to meet the needs of customers and stay in the market for as long as possible.
Search launched from the underlying problem is the presence of concentrations of defects and waste plaguing the company and to achieve the goal of the study detects the level of quality applied in the factory vessels and reservoirs of the General Company for Heavy Engineering Equipment, As well as calculate wastage rates occurring in the production process and find a relationship between the level of quality and ratios defective in each type of waste, it has been used quantitative meas
... Show MoreIn this research the change in the distance of the two stars in two binary star systems (13.6+8)M8and (13+10)M8 was studied, through the calculations the value (rate of mass transfer) of the two phases of dynamical stages of mass which are mass loss and mass transfer has been extracted in its own way ,by extracting the value of the value of (the distance variation between the two stars) has been found only in the mass transfer stage by using mathematical model ,in mass loss stage and were calculated from the change and the difference between the values of each at different times of binary star system evolution ,it was found that the maximum values of and are in ma
... Show MoreRenal transplantation is a principal treatment option for end-stage kidney failure. Bone loss and fracture are serious complication of kidney transplantation, associated with morbidity and mortality. The pathogenesis of post transplantation bone loss is multifactorial and complex
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra
... Show MoreSuccessfully, theoretical equations were established to study the effect of solvent polarities on the electron current density, fill factor and efficiencies of Tris (8-hydroxy) quinoline aluminum (Alq3)/ ZnO solar cells. Three different solvents studied in this theoretical works, namely 1-propanol, ethanol and acetonitrile. The quantum model of transition energy in donor–acceptor system was used to derive a current formula. After that, it has been used to calculate the fill factor and the efficiency of the solar cell. The calculations indicated that the efficiency of the solar cell is influenced by the polarity of solvents. The best performance was for the solar cell based on acetonitrile as a solvent with electron current density of (5.0
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