936 resultados para Impatient Care Units


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OBJECTIVE: To examine variability in outcome and resource use between ICUs. Secondary aims: to assess whether outcome and resource use are related to ICU structure and process, to explore factors associated with efficient resource use. DESIGN AND SETTING: Cohort study, based on the SAPS 3 database in 275 ICUs worldwide. PATIENTS: 16,560 adults. MEASUREMENTS AND RESULTS: Outcome was defined by standardized mortality rate (SMR). Standardized resource use (SRU) was calculated based on length of stay in the ICU, adjusted for severity of acute illness. Each unit was assigned to one of four groups: "most efficient" (SMR and SRU < median); "least efficient" (SMR, SRU > median); "overachieving" (low SMR, high SRU), "underachieving" (high SMR, low SRU). Univariate analysis and stepwise logistic regression were used to test for factors separating "most" from "least efficient" units. Overall median SMR was 1.00 (IQR 0.77-1.28) and SRU 1.07 (0.76-1.58). There were 91 "most efficient", 91 "least efficient", 47 "overachieving", and 46 "underachieving" ICUs. Number of physicians, of full-time specialists, and of nurses per bed, clinical rounds, availability of physicians, presence of emergency department, and geographical region were significant in univariate analysis. In multivariate analysis only interprofessional rounds, emergency department, and geographical region entered the model as significant. CONCLUSIONS: Despite considerable variability in outcome and resource use only few factors of ICU structure and process were associated with efficient use of ICU. This suggests that other confounding factors play an important role.

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INTRODUCTION Community acquired pneumonia (CAP) is the most common infectious reason for admission to the Intensive Care Unit (ICU). The GenOSept study was designed to determine genetic influences on sepsis outcome. Phenotypic data was recorded using a robust clinical database allowing a contemporary analysis of the clinical characteristics, microbiology, outcomes and independent risk factors in patients with severe CAP admitted to ICUs across Europe. METHODS Kaplan-Meier analysis was used to determine mortality rates. A Cox Proportional Hazards (PH) model was used to identify variables independently associated with 28-day and six-month mortality. RESULTS Data from 1166 patients admitted to 102 centres across 17 countries was extracted. Median age was 64 years, 62% were male. Mortality rate at 28 days was 17%, rising to 27% at six months. Streptococcus pneumoniae was the commonest organism isolated (28% of cases) with no organism identified in 36%. Independent risk factors associated with an increased risk of death at six months included APACHE II score (hazard ratio, HR, 1.03; confidence interval, CI, 1.01-1.05), bilateral pulmonary infiltrates (HR1.44; CI 1.11-1.87) and ventilator support (HR 3.04; CI 1.64-5.62). Haematocrit, pH and urine volume on day one were all associated with a worse outcome. CONCLUSIONS The mortality rate in patients with severe CAP admitted to European ICUs was 27% at six months. Streptococcus pneumoniae was the commonest organism isolated. In many cases the infecting organism was not identified. Ventilator support, the presence of diffuse pulmonary infiltrates, lower haematocrit, urine volume and pH on admission were independent predictors of a worse outcome.

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INTRODUCTION Faecal peritonitis (FP) is a common cause of sepsis and admission to the intensive care unit (ICU). The Genetics of Sepsis and Septic Shock in Europe (GenOSept) project is investigating the influence of genetic variation on the host response and outcomes in a large cohort of patients with sepsis admitted to ICUs across Europe. Here we report an epidemiological survey of the subset of patients with FP. OBJECTIVES To define the clinical characteristics, outcomes and risk factors for mortality in patients with FP admitted to ICUs across Europe. METHODS Data was extracted from electronic case report forms. Phenotypic data was recorded using a detailed, quality-assured clinical database. The primary outcome measure was 6-month mortality. Patients were followed for 6 months. Kaplan-Meier analysis was used to determine mortality rates. Cox proportional hazards regression analysis was employed to identify independent risk factors for mortality. RESULTS Data for 977 FP patients admitted to 102 centres across 16 countries between 29 September 2005 and 5 January 2011 was extracted. The median age was 69.2 years (IQR 58.3-77.1), with a male preponderance (54.3%). The most common causes of FP were perforated diverticular disease (32.1%) and surgical anastomotic breakdown (31.1%). The ICU mortality rate at 28 days was 19.1%, increasing to 31.6% at 6 months. The cause of FP, pre-existing co-morbidities and time from estimated onset of symptoms to surgery did not impact on survival. The strongest independent risk factors associated with an increased rate of death at 6 months included age, higher APACHE II score, acute renal and cardiovascular dysfunction within 1 week of admission to ICU, hypothermia, lower haematocrit and bradycardia on day 1 of ICU stay. CONCLUSIONS In this large cohort of patients admitted to European ICUs with FP the 6 month mortality was 31.6%. The most consistent predictors of mortality across all time points were increased age, development of acute renal dysfunction during the first week of admission, lower haematocrit and hypothermia on day 1 of ICU admission.

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A number of medical and social developments have had an impact on the neonatal mortality over the past ten to 15 years in the United States. The purpose of this study was to examine one of these developments, Newborn Intensive Care Units (NICUs), and evaluate their impact on neonatal mortality in Houston, Texas.^ This study was unique in that it used as its data base matched birth and infant death records from two periods of time: 1958-1960 (before NICUs) and 1974-1976 (after NICUs). The neonatal mortality of single, live infants born to Houston resident mothers was compared for two groups: infants born in hospitals which developed NICUs and infants born in all other Houston hospitals. Neonatal mortality comparisons were made using the following birth-characteristic variables: birthweight, gestation, race, sex, maternal age, legitimacy, birth order and prenatal care.^ The results of the study showed that hospitals which developed NICUs had a higher percentage of their population with high risk characteristics. In spite of this, they had lower neonatal mortality rates in two categories: (1) white 3.5-5.5 pounds birthweight infants, (2) low birthweight infants whose mothers received no prenatal care. Black 3.5-5.5 pounds birthweight infants did equally well in either hospital group. While the differences between the two hospital groups for these categories were not statistically significant at the p < 0.05 level, data from the 1958-1960 period substantiate that a marked change occurred in the 3.5-5.5 pounds birthweight category for those infants born in hospitals which developed NICUs. Early data were not available for prenatal care. These findings support the conclusion that, in Houston, NICUs had some impact on neonatal mortality among moderately underweight infants. ^

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Objective: To assess whether crude league tables of mortality and league tables of risk adjusted mortality accurately reflect the performance of hospitals.

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" ... by Marc Freiman and Erwin Brown, Jr."--p. 1."

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Objective. To determine the population incidence and outcome of severe sepsis occurring in adult patients treated in Australian and New Zealand intensive care units (ICUs), and compare with recent retrospective estimates from the USA and UK. Design. Inception cohort study. Setting. Twenty-three closed multi-disciplinary ICUs of 21 hospitals (16 tertiary and 5 university affiliated) in Australia and New Zealand. Patients. A total of 5878 consecutive ICU admission episodes. Measurements and results. Main outcome measures were population-based incidence of severe sepsis, mortality at ICU discharge, mortality at 28 days after onset of severe sepsis, and mortality at hospital discharge. A total of 691 patients, 11.8 (95% confidence intervals 10.9-12.6) per 100 ICU admissions, were diagnosed with 752 episodes of severe sepsis. Site of infection was pulmonary in 50.3% of episodes and abdominal in 19.3% of episodes. The calculated incidence of severe sepsis in adults treated in Australian and New Zealand ICUs is 0.77 (0.76-0.79) per 1000 of population. 26.5% of patients with severe sepsis died in ICU, 32.4% died within 28 days of the diagnosis of severe sepsis and 37.5% died in hospital. Conclusion. In this prospective study, 11.8 patients per 100 ICU admissions were diagnosed with severe sepsis and the calculated annual incidence of severe sepsis in adult patients treated in Australian and New Zealand ICUs is 0.77 per 1000 of population. This figure for the population incidence falls in the lower range of recent estimates from retrospective studies in the U.S. and the U.K.

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Objective: To assess the outcomes for a group of elderly patients with mental illness following their discharge from a stand-alone psychiatric facility to seven extended care units (ECUs). Method: All patients (n = 60) who were relocated to the ECUs were assessed using a number of standardized clinical and general functioning instruments at 6 months and 6 weeks pre-move, and again at 6 weeks, 6 months and 18 months post-move. Results: By 18 months post-discharge, 13 of the 60 patients (21.7%) had died and seven others had been transferred to nursing homes. Those who died were older and had significantly higher levels of physical ill health when compared to those who did not die. Changes on measures of clinical and behavioural functioning in those who remained in the study did not reach statistical significance by 18 months post-move. However, participants did demonstrate improvements in quality of life with significantly higher scores on measures of social contact and community access. Conclusions: The mortality observed in the follow-up period is likely to be related to physical ill health and old age rather than the trauma associated with relocation. While overall functioning did not improve following relocation, patients had more independence and greater access to community-based activities.

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Purpose: To develop a model for the global performance measurement of intensive care units (ICUs) and to apply that model to compare the services for quality improvement. Materials and Methods: Analytic hierarchy process, a multiple-attribute decision-making technique, is used in this study to evolve such a model. The steps consisted of identifying the critical success factors for the best performance of an ICU, identifying subfactors that influence the critical factors, comparing them pairwise, deriving their relative importance and ratings, and calculating the cumulative performance according to the attributes of a given ICU. Every step in the model was derived by group discussions, brainstorming, and consensus among intensivists. Results: The model was applied to 3 ICUs, 1 each in Barbados, Trinidad, and India in tertiary care teaching hospitals of similar setting. The cumulative performance rating of the Barbados ICU was 1.17 when compared with that of Trinidad and Indian ICU, which were 0.82 and 0.75, respectively, showing that the Trinidad and Indian ICUs performed 70% and 64% with respect to Barbados ICU. The model also enabled identifying specific areas where the ICUs did not perform well, which helped to improvise those areas. Conclusions: Analytic hierarchy process is a very useful model to measure the global performance of an ICU. © 2005 Elsevier Inc. All rights reserved.

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Purpose - The purpose of this study is to develop a performance measurement model for service operations using the analytic hierarchy process approach. Design/methodology/approach - The study reviews current relevant literature on performance measurement and develops a model for performance measurement. The model is then applied to the intensive care units (ICUs) of three different hospitals in developing nations. Six focus group discussions were undertaken, involving experts from the specific area under investigation, in order to develop an understandable performance measurement model that was both quantitative and hierarchical. Findings - A combination of outcome, structure and process-based factors were used as a foundation for the model. The analyses of the links between them were used to reveal the relative importance of each and their associated sub factors. It was considered to be an effective quantitative tool by the stakeholders. Research limitations/implications - This research only applies the model to ICUs in healthcare services. Practical implications - Performance measurement is an important area within the operations management field. Although numerous models are routinely being deployed both in practice and research, there is always room for improvement. The present study proposes a hierarchical quantitative approach, which considers both subjective and objective performance criteria. Originality/value - This paper develops a hierarchical quantitative model for service performance measurement. It considers success factors with respect to outcomes, structure and processes with the involvement of the concerned stakeholders based upon the analytic hierarchy process approach. The unique model is applied to the ICUs of hospitals in order to demonstrate its effectiveness. The unique application provides a comparative international study of service performance measurement in ICUs of hospitals in three different countries. © Emerald Group Publishing Limited.

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The purpose of this study was to determine the emergency department (ED) length of stay (LOS) of patients admitted to inpatient telemetry and critical care units and to identify the factors that contribute to a prolonged ED LOS. It also examined whether there was a difference in ED LOS between clients evaluated by an ED physician, an Advanced Registered Nurse Practitioner (ARNP) or a Physician's Assistant (PA).^ A data collection tool was devised and used to record data obtained by retrospectively reviewing 110 charts of patients from this sample. The mean ED LOS was 286.75 minutes. Multiple factors were recorded as affecting the ED LOS of this sample, including: age, diagnosis, consultations, multiple radiographs, pending admission orders, nurse unable to call report/busy, relatives at bedside, observation or stabilization necessary, bed not ready and infusion in progress. No significant difference in ED LOS was noted between subjects initially evaluated by a physician, an ARNP or a PA. ^