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.
Abstract Objective: The aim of this study is to evaluate the level of the anatomical knowledge of undergraduate students in Nursing collage/Baghdad university.Methodology:The sample was collected by symmetrical probability. Research sample includes (197)students represent four classes which is distributed as following: fifty students represent first class, fifty students represent the second class, forty nine students represent the third class,&fourty eight students represent the fourth class. Results:The study concludes that the anatomical knowledge level for collage students is intermediate .The m
The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.
Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.
The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple
... Show MoreDeaf and dumb peoples are suffering difficulties most of the time in communicating with society. They use sign language to communicate with each other and with normal people. But Normal people find it more difficult to understand the sign language and gestures made by deaf and dumb people. Therefore, many techniques have been employed to tackle this problem by converting the sign language to a text or a voice and vice versa. In recent years, research has progressed steadily in regard to the use of computers to recognize and translate the sign language. This paper reviews significant projects in the field beginning with important steps of sign language translation. These projects can b
الاحداث السياسية في العراق بعد 2003 وأثر الانتماء والوعي في التشكيل العراقي المعاصر
One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first
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