View clinical trials related to Length of Stay.
Filter by:This retrospective study aims to compare discharge criteria and their impact on the length of stay using two neonatal intensive care units from two countries. The possible discharge criteria include temperature control, apnea observation, periodic respiration, least weight limit, and parents' readiness. The data were collected retrospectively in each study site.
The goal of this randomized, controlled, open-label trial is to test the use of secondary prioritization software (Optimum®) in the pediatric emergency department (PED). The aim of this study is to determine: 1. whether the use of this secondary prioritization software (Optimum®) reduces the patients' median length of stay (LOS) in the PED 2. how this software is accepted by the staff. The PED staff will be asked to manage the patients according to the Optimum® software indications (intervention) or according to the standard dashboard (control).
In the COVID-19 healthcare crisis, one possible treatment therapy that has generated the most discussion is that of proning, or the position in which the patient lays face down as opposed to face up for a period of time. As the pandemic continues, this method has been more widely adopted to increase oxygen saturation in patients in respiratory distress. While proning research is both ongoing and extensive in the ICU population of COVID-19 patients, minimal research has been conducted with acute care patients. The researchers aim to address this gap with this study. The researchers used a systematic approach to educate patients and staff about patient self-proning, implementing self-proning every 2 hours, and monitoring escalation of oxygen levels, as well as length of stay in the acute care unit. The researchers hypothesized an improvement in oxygen saturation levels as evidenced by no escalation of respiratory care (i.e. higher levels of oxygen needed, transfer to higher level of care), resulting in shorter lengths of stay for the intervention population.
The purpose of this study is to evaluate the impact of an AI admission prediction tool on the number of preventable hospital admissions, emergency department (ED) length of stay, when the predictions are displayed only to a dedicated ED triage team. Also, to evaluate user perceptions of the AI tool among the triage team users and medical officer of the day users. Additionally, to evaluate any impact of the AI tool on the number of interventions performed by the triage team, and to evaluate the impact of the tool on time-to-admission after an admission order is placed.
Esophageal atresia is a rare but severe malformation, and it requires early surgery. Coloesophagoplasty is surgical repair of the esophageal with an isoperistaltic transverse colon graft. In the postoperative period after coloesophagoplasty children require careful monitoring of fluid balance, because clinically significant fluid overload can lead to dysfunction of various organs and systems.
In our study, we aim to predict palliative care patients earlier, to reduce hospitalization periods and to prevent intensive care unit occupation by palliative care patients.
As humans age, there is a gradual loss of skeletal muscle mass and strength, termed sarcopenia. The underlying causes of sarcopenia are yet not fully elucidated but are thought to be multifactorial and include increased levels of systemic pro-inflammatory mediators, a decrease in anabolic hormones and changes in the neuromuscular system. Furthermore, physical inactivity, chronic diseases, immobilisation and hospitalisation are known to play an important part in the development of sarcopenia. The prevalence of sarcopenia ranges from 20-30% (aged >70yrs) within the general community. However, the prevalence of sarcopenia in geriatric patients after an acute hospital admission is substantially higher, estimated at ≈50%. Furthermore, successive events of hospitalisation have been suggested to contribute to the development of sarcopenia, as even short periods (4-5 days) of skeletal muscle disuse are known to induce muscle atrophy. Mean length of hospital stay in geriatric wards due to acute illness or hip-fracture is typically 7 to 11 days during which the level of physical activity is strongly reduced leading to an accelerated loss of muscle mass that many older patients never recover from. Notably, a substantial part of the deterioration in functional capacity could be avoided just by counteracting loss of muscle mass during hospitalization. As such, we need to identify sensitive biological, clinical and functional biomarkers predicting loss of muscle mass and function during hospitalization to identify patients at risk of developing sarcopenia. Additionally, it is crucial to investigate the association of these biomarkers with hospital length of stay, as hospitalisation has been suggested to contribute to the development of sarcopenia while longer hospital stays may increase patient risk of hospital-acquired infections and place an economic burden on society.
A comparison study was performed between laparoscopic appendectomy and open appendectomy in acute setting in tertiary hospital to access the outcome of postoperative pain and hospital stay. As the popularity of laparoscopic appendectomy has failed in major tertiary hospital due to huge amount of patient load in which open appendectomy was performed.This study was performed to prove that outcome of laparoscopic appendectomy are far better than open appendectomy and to increase the use of laparoscopic surgery in acute settings
Hemorrhoidectomy is the treatment of choice for grade 3 and 4th degree hemorrhoids. Various surgical technique has been used to improve the outcome of the procedures performed in respect to operative time ,post operative pain and hospital stay. This study compares the conventional closed technique with harmonic scalpel technique which is a device regulated with ultrasonic waves to perform the procedure with minimal postoperative complication as well as decreasing the prolong stay in hospital.
P-POSSUM score had a predictive power of >80% to predict the length of stay of kidney transplant recipients