View clinical trials related to Emergencies.
Filter by:Aim 1: To demonstrate the feasibility by determining proportion of completed medication reconciliation, Central Nervous System active Potentially Inappropriate Medication (CNS PIM) use among patients with Alzheimer's Disease and Related Dementias (ADRD) and Mild Cognitive Impairment (MCI) in the emergency department (ED), and communication between ED clinical pharmacists and outpatient prescribers. Aim 2: To demonstrate the feasibility of collecting the primary and secondary outcomes for a subsequent study. The future primary outcome will be reduction in CNS PIMs 90 days after an ED visit. Secondary outcomes will include outpatient follow-up, repeat ED visits, and hospitalizations during the 90 days following an ED visit. Aim 3: To demonstrate the acceptability of the PRIDE intervention to outpatient clinicians using the Acceptability of Intervention Measure and qualitative analysis of responses.
The study titled " The Effect of Definitive Identification of Viral Etiology in Emergency Department Patients with Acute Respiratory Infection on Antibiotic Utilization (RADIATE)" aims to investigate the effectiveness of a rapid diagnostic approach in reducing unnecessary antibiotic use in the emergency department (ED) for patients presenting with acute respiratory illness (ARI) due to a virus. Using a prospective design, eligible participants are individuals who visit the ED with complaints related to acute respiratory illness. The study will employ a single-arm consecutive enrollment approach. The intervention involves the implementation of a rapid point-of-care multiplex polymerase chain reaction (PCR) test to promptly identify the viral cause of the infection. By utilizing a rapid diagnostic tool to identify viral etiology, the study aims to provide healthcare professionals in the ED with more accurate information to guide treatment decisions. Ultimately, the goal is to decrease the unnecessary use of antibiotics for ARI's due to a virus, which has several negative outcomes including promotion of antibiotic resistance, exacerbating ED length of stay and encouraging unnecessary additional diagnostic tests.
We try to evaluate whether the type of anesthesia used influences the occurrence of perioperative maternal complications as well as neonatal outcome on emergency (Red Code) Cesarean Section. This study occurred in a Level 3 Maternity Ward.
The purpose of the study is to determine whether SBCT is a useful tool for diagnosing the main form of failure respiratory acute and to define the SBCT limit associated with insufficiency respiratory in this population, the requirement for NIV or invasive ventilation. Furthermore, the correlation with the most common scores and indices used in the emergency room will be studied, such as: HACOR, MEW, REMS SCORE, ROS, CURB-65, qSOFA, SEVERITY INDEX OF PNEUMONIA, GWTG HF, LUNG ULTRASOUND SCORE, SINGLE BREATH COUNT
The goal of this feasibility study is to learn if Dutch ED providers are able to use transesophageal echocardiography during cardiac arrest. The main question it aims to answer is: • are the ED providers able to determine the area of maximal compression of the heart using TEE
The goal of this observational retrospective and prospective multicentric trial is to learn about the impact of bail-out stenting (BOS) after drug coated balloon (DCB) percutaneous coronary angioplasty (PCI) in de novo coronary stenosis.The main question to answer is: - if BOS PCI leads to an higher rate of 1-year target vessel failure that DCB-only PCI. Partecipants will recieve DCB PCI in de novo coronary stenosis. Treatments they'll be given should be: - DCB-only PCI - BOS PCI Reaserchers will compare DCB-only and BOS group to see if addictive stent implantation for DCB-PCI complication is relate to an higher rate of target vessel failure. Target vessel is the primary endpoint, defined as: - cardiovascular death - target vessel myocardial infarction - clinical driven target vessel revascularization - angiographic restenosis
Future predictive modeling in emergency medicine will likely combine the use of a wide range of data points such as continuous documentation, monitoring using wearables, imaging, biomarkers, and real-time administrative data from all health care providers involved. Subsequent extensive data sets could feed advanced deep learning and neural network algorithms to accurately predict the risk of specific health conditions. Moreover, predictive analytics steers towards the development of clinical pathways that are adaptive and continuously updated, and in which healthcare decision-making is supported by sophisticated algorithms to provide the best course of action effectively and safely. The potential for predictive analytics to revolutionize many aspects of healthcare seems clear in the horizon. Information on the use in emergency medicine is scarce. Aim of the study is to evaluate the performance of using routine-data to predict resource usage in emergency medicine using the commonly encountered symptom of acute neurologic deficit. As an outlook, this might serve as a prototype for other, similar projects using routine medical data for predictive analytics in emergency medicine.
Based on a survey conducted by the Nursing and Health Care Bureau of the Ministry of Health and Welfare in 2023, which investigated the recruitment and turnover rates of nursing personnel in 479 hospitals of different levels, the results revealed that the recruitment of nursing personnel was exceedingly challenging. The difficulty levels varied, with medical centers at 80%, regional hospitals at 67.9%, and district hospitals at 43.37%. Additionally, the turnover rates of nursing personnel were notably high, with medical centers at 10.21%, regional hospitals at 11.17%, and district hospitals at 14.52%. These rates all exceeded 10%, which means that, on average, one out of every ten nursing personnel resigned (Nursing and Health Care Bureau, Ministry of Health and Welfare, 2023). This study aims to investigate the relationship between job satisfaction and retention intention among emergency room nursing personnel in a regional teaching hospital in Yunlin County. In the fiscal year 2023, the unit experienced an alarming turnover rate of approximately 82% among newly hired personnel. Therefore, the study intends to conduct further research and exploration into the job satisfaction and retention intention of emergency room nursing personnel. The primary objectives of the research include examining the correlation between the demographic characteristics of emergency room nurses and their job satisfaction, the correlation between the demographic characteristics of emergency room nurses and their retention intention, and the correlation between job satisfaction and retention intention among emergency room nurses. The study's subjects are nurses or nursing staff employed in the emergency department. The research is conducted through the distribution of questionnaires, and all responses are collected anonymously. The questionnaire is structured into three main sections: the first section covers demographic characteristics, the second section addresses job satisfaction items, and the third section focuses on retention intention items. Upon collecting and encoding the data, the information will be compiled, and statistical analysis will be performed using Excel and SPSS version 25.0 statistical software to validate various research hypotheses. The expected outcome of the study is a positive relationship between job satisfaction and retention intention among emergency room nurses, indicating that job satisfaction influences retention intention.
The goal of this retrospective cohort study is to develop and validate a language model that can interpret the contents of emergency department electronic medical records and extract relevant information for research purposes in all adult patients who arrived at the participating emergency departments in a three-year period. The main question it aims to answer is: is the language model able to interpret the contents of emergency department electronic medical records and extract the requested information from them so that it can be used to make accurate analyses and predictions? The study is retrospective and data will be extracted automatically from the medical health records.
The older population is increasing, and one of the challenges is to prevent functional disability. Longer hospital stays are a recognized factor in dependency. Older subjects may present multiple complications, and therefore be frequently readmitted to hospital. Readmission to hospital is a costly and iatrogenic event in terms of independence, and must therefore be limited. The most vulnerable older patients therefore require specific care to avoid these iatrogenic complications, and various innovative structures have been developed, such as mobile geriatric teams, carrying out assessments in emergency departments, or geriatric post-emergency units with a shorter length of stay to reduce the iatrogenic impact of hospitalization.In November 2022, a temporary hospitalisation unit based on this model was opened at the CHU d'Angers with 11 beds. The aim of this study is to estimate the rate of early rehospitalisation (< 30 days) between December 2022 and September 2023, and the factors associated with it. Once identified, these factors will allow us to further select patient profiles that are suitable for care in these very short stay units.