Increased hospital pressure seven admitted to the hospital
Bed rest often leads to complications like pressure ulcers. We examined risk factors for hospital-acquired pressure ulcers, the use of preventive devices, and the effects of case-mix adjustments on between-ward comparisons. Increased hospital pressure seven admitted to the hospital. (United Carry)
We conducted 3 cross-sectional surveys of 2373 patients with no pressure ulcers at admission at a teaching hospital. We analyzed the presence of pressure ulcers, dates of admission and occurrence of ulcers, hospital ward, patient age and gender, appetite and nutritional status, surgery during the stay, hospitalization for fracture, comorbidities, and low-pressure devices. use (special mattresses, cushions, and pressure-relieving beds), and the Norton Pressure Ulcer Predictive Score (physical status, mental status, activity, mobility, and incontinence).
Two hundred forty-seven new pressure ulcers (5.7 per 1000 person-days) occurred. In multivariate analysis, pressure ulcer risk increased with age (risk gradient 1:4.5 across 5 categories; P< .001) and Norton score (risk gradient 30-fold across 5 categories; P< .001); Other risk factors (all relative risks, 1.5-1.8; P< .002) were fracture, surgical intervention, loss of appetite, and hospitalization for nasogastric tube or intravenous nutrition. Adjustment for case mix substantially altered differences between hospital wards. The use of preventive devices was associated with Norton scores, but not all high-risk patients benefited.(joni-info)
Three cross-sectional surveys of all hospitalized patients were conducted in October and December 1995 and February 1996 at the Geneva University Hospital, Geneva, Switzerland. The only public hospital in Geneva is this urban teaching hospital with 1100 beds. The survey included all patients aged 16 years or older who were admitted to the hospital on pre-selected days. Patients who were free of pressure ulcers at admission were eligible for the risk factors study.
Study variables and data collection
The primary outcome variable was the presence of pressure ulcers on any part of the body, grade 1 (nonblanchable erythema), 2 (partial skin loss), 3 (full-thickness skin loss), or 4 (deep tissue destruction).17 Date of admission, date of first ulcer appearance, and whether or not a pressure ulcer was present on admission were noted, so that incidence rates could be calculated. Another outcome was the use of low-pressure devices (special mattresses, cushions, and pressure-reducing beds) to prevent variable pressure ulcers.
Independent variables included the patient’s age and sex, ward type, history of surgery during hospitalization, hospitalization for fracture, presence of diabetes and other comorbidities, patient’s appetite quality and nutritional status, and Norton. The Pressure Ulcer Prediction Score (hereafter called) includes The Norton score),18 which is a composite of 5 variables (physical status, mental status, activity, mobility, and incontinence) is scored from 1 (worst) to 4 (best).
Data were obtained from written nursing records by trained data collectors, supplemented by interviews with nursing staff and patient examinations whenever necessary. Hospital admission and discharge dates were obtained from computerized hospital records. (articalplus)
We used time-to-failure methods to calculate the time at risk of ulcer development. Ulcer incidence rates calculated per 1000 person-days at risk. The risk period continued from admission until ulceration (in those who developed ulcers) or the date of diagnosis (in those who did not). Patients who tested on the day of their admission scheduled for half a day of follow-up. Ulcer incidence rates over time evaluated using the Kaplan-Meier method. And the log-rank test.19 Multivariate modeling performed in proportional hazards models. 20 To extrapolate from the study sample to the general hospital patient population. We weighted observations by the inverse of the length of stay. Since the length of stay is proportional to the probability of included in a cross-sectional survey. (So longer stays are over-represented in patient cross-sectional surveys).
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Seven admitted to the hospital
Patients admitted on weekends may have worse outcomes than on weekdays. Adjusting the practice of senior doctors to weekends may reduce the weekend effect.
To compare outcomes between weekday and weekend admissions with propensity score matching (PSM) to account for potential confounding variables, a pre-post controlled study setting was conducted in northern
Conducted in a 2,000-bed medical center. The Hospitalist Program was conceptualized in October 2009. As part of this, a hospitalist-managed acute general medicine unit had both attending physicians and nurse practitioners (NPs) admitting general medicine patients from the emergency department (ED). Results for the first three months were reported. Unlike traditional academic medical services, the hospitalist program did not have resident physicians to care for inpatients, except for the night shift, when there was coverage by a resident physician under the supervision of a hospitalist.
Study design and population
The study based on a longitudinal hospitalist performance. Research study approved by the Research Ethical Committee. National Taiwan University Hospital (NTUH, 201112161RIC). Patient data, before July 2011, collected from medical records. Since then, every admission to a hospitalist general medicine unit collected. Only data on laboratory results were missing because some tests were not mandatory for every patient at admission. To avoid comparison, laboratory data were only used. (Present Gift)
The primary outcome variables were hospital length of stay (LOS), proportion of intensive care unit (ICU) admissions, cardiopulmonary resuscitation (CPR) events, and in-hospital mortality.
The pre-intervention group consisted of a comparison patient group cared for through traditional internal medicine models, just prior to the implementation of the hospital system. From November 1, 2009, to December 31, 2009. Patients admitted to seven traditional general medicine wards (with a total of 239 beds) sampled from the ED. The patient’s medical records examined.
To examine the data, SPSS used (version 16.0, SPSS Inc., Chicago, IL, USA). Between-group differences compared using Fisher’s exact t-test for continuous. VariablesExplicit variables compared using Acute medical admissions. Unlike elective surgery or scheduled admissions, which occur on both weekdays and weekends. Because of inherent differences between weekday and weekend admissions, in terms of baseline characteristics, we used propensity score matching (PSM) with a 1:1 ratio to adjust for these differences.
Evaluation of the long-term effect of the intervention
A total of 3315 patients admitted to the hospitalist care ward from January 1, 2010, to December 31, 2012. By reference, there was no difference between the two groups. p = 0.122), ICU admission ratio (2.9% vs. 2.0%, p = 0.156), CPR (0.4% vs. 0.7%, p = 0.259) incidence, and in-hospital mortality rate (6.8% vs. 7.9%, p = 0.283). D shows rates of ICU admission, CPR event, and in-hospital mortality for the pre-intervention, post-intervention, and three-year cohorts, respectively. (On Hold)