272 resultados para HOSPITAL ADMISSIONS


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Background Formalised predialysis care has been shown to extend the wellness of individuals with advanced chronic kidney disease, slow disease progression and increase the uptake of home dialysis. Predialysis care, incorporating multidisciplinary input is also vital in delaying the onset of end-stage kidney disease and reducing hospital admissions; thereby decreasing financial demands on health budgets. Predialysis care should include comprehensive information provision and predialysis education. This empowers patients to choose self-care strategies and therapies.

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Radical circumstances (bushfires and natural disasters) flush out the mental illness in society. Whenever there’s a disaster, there’s a rush on hospital admissions for psychiatric problems. But on the whole, the illness is already there. Emergencies naturally make fodder for delusions and the emergency efforts, for mania. Obviously, there are direct mental health consequences – a small rise in post-traumatic stress disorder inevitably follows disaster. This correlates with the severity of the consequences of the disaster (loss of family, friends, animals and property). And there’s usually a big rethink, with about a third of those affected leaving the area permanently. But, for the most part, this isn’t driven by mental health issues, it results from the very real fears about whether living in a fire (or other disaster) zone is worth it.

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Objective To determine trends in the incidence of foot-related hospitalisation and amputation amongst persons with diabetes in Queensland (Australia) between 2005 and 2010 that coincided with changes in state-wide ambulatory diabetic foot-related complication management. Methods All data from cases admitted for the principal reason of diabetes foot-related hospitalisation or amputation in Queensland from 2005–2010 were obtained from the Queensland Hospital Admitted Patient Data Collection dataset. Incidence rates for foot-related hospitalisation (admissions, bed days used) and amputation (total, minor, major) cases amongst persons with diabetes were calculated per 1,000 person-years with diabetes (diabetes population) and per 100,000 person-years (general population). Age-sex standardised incidence and age-sex adjusted Poisson regression models were also calculated for the general population. Results There were 4,443 amputations, 24,917 hospital admissions and 260,085 bed days used for diabetes foot-related complications in Queensland. Incidence per 1,000 person-years with diabetes decreased from 2005 to 2010: 43.0% for hospital admissions (36.6 to 20.9), 40.1% bed days (391 to 234), 40.0% total amputations (6.47 to 3.88), 45.0% major amputations (2.18 to 1.20), 37.5% minor amputations (4.29 to 2.68) (p < 0.01 respectively). Age-sex standardised incidence per 100,000 person-years in the general population also decreased from 2005 to 2010: 23.3% hospital admissions (105.1 to 80.6), 19.5% bed days (1,122 to 903), 19.3% total amputations (18.57 to 14.99), 26.4% major amputations (6.26 to 4.61), 15.7% minor amputations (12.32 to 10.38) (p < 0.01 respectively). The age-sex adjusted incidence rates per calendar year decreased in the general population (rate ratio (95% CI)); hospital admissions 0.949 (0.942–0.956), bed days 0.964 (0.962–0.966), total amputations 0.962 (0.946–0.979), major amputations 0.945 (0.917–0.974), minor amputations 0.970 (0.950–0.991) (p < 0.05 respectively). Conclusions There were significant reductions in the incidence of foot-related hospitalisation and amputation amongst persons with diabetes in the population of Queensland over a recent six-year period.

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Background. The objective is to estimate the cost-effectiveness of an intervention that reduces hospital readmission among older people at high risk. A cost-effectiveness model to estimate the costs and health benefits of the intervention was implemented. Methodology/Principal Findings. The model used data from a randomised controlled trial conducted in an Australian tertiary metropolitan hospital. Participants were acute medical admissions aged >65 years with at least one risk factor for readmission: multiple comorbidities, impaired functionality, aged >75 years, 30 recent multiple admissions, poor social support, history of depression. The intervention was a comprehensive nursing and physiotherapy assessment and an individually tailored program of exercise strategies and nurse home visits with telephone follow-up; commencing in hospital and continuing following discharge for 24 weeks. The change to cost outcomes, including the costs of implementing the intervention and all subsequent use of health care services, and, the change to health benefits, represented by quality adjusted life years, were estimated for the intervention as compared to existing practice. The mean change to total costs and quality 38 adjusted life years for an average individual over 24 weeks participating in the intervention were: cost savings of $333 (95% Bayesian credible interval $-1,932:1,282) and 0.118 extra quality adjusted life years (95% Bayesian credible interval 0.1:0.136). The mean net41 monetary-benefit per individual for the intervention group compared to the usual care condition was $7,907 (95% Bayesian credible interval $5,959:$9,995) for the 24 week period. Conclusions/Significance. The estimation model that describes this intervention predicts cost savings and improved health outcomes. A decision to remain with existing practices causes unnecessary costs and reduced health. Decision makers should consider adopting this 46 program for elderly hospitalised patients.

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Objective: To examine the effects of personal and community characteristics, specifically race and rurality, on lengths of state psychiatric hospital and community stays using maximum likelihood survival analysis with a special emphasis on change over a ten year period of time. Data Sources: We used the administrative data of the Virginia Department of Mental Health, Mental Retardation, and Substance Abuse Services (DMHMRSAS) from 1982-1991 and the Area Resources File (ARF). Given these two sources, we constructed a history file for each individual who entered the state psychiatric system over the ten year period. Histories included demographic, treatment, and community characteristics. Study Design: We used a longitudinal, population-based design with maximum likelihood estimation of survival models. We presented a random effects model with unobserved heterogeneity that was independent of observed covariates. The key dependent variables were lengths of inpatient stay and subsequent length of community stay. Explanatory variables measured personal, diagnostic, and community characteristics, as well as controls for calendar time. Data Collection: This study used secondary, administrative, and health planning data. Principal Findings: African-American clients leave the community more quickly than whites. After controlling for other characteristics, however, race does not affect hospital length of stay. Rurality does not affect length of community stays once other personal and community characteristics are controlled for. However, people from rural areas have longer hospital stays even after controlling for personal and community characteristics. The effects of time are significantly smaller than expected. Diagnostic composition effects and a decrease in the rate of first inpatient admissions explain part of this reduced impact of time. We also find strong evidence for the existence of unobserved heterogeneity in both types of stays and adjust for this in our final models. Conclusions: Our results show that information on client characteristics available from inpatient stay records is useful in predicting not only the length of inpatient stay but also the length of the subsequent community stay. This information can be used to target increased discharge planning for those at risk of more rapid readmission to inpatient care. Correlation across observed and unobserved factors affecting length of stay has significant effects on the measurement of relationships between individual factors and lengths of stay. Thus, it is important to control for both observed and unobserved factors in estimation.

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Objective. This study investigated cognitive functioning among older adults with physical debility not attributable to an acute injury or neurological condition who were receiving subacute inpatient physical rehabilitation. Design. A cohort investigation with assessments at admission and discharge. Setting. Three geriatric rehabilitation hospital wards. Participants. Consecutive rehabilitation admissions () following acute hospitalization (study criteria excluded orthopaedic, neurological, or amputation admissions). Intervention. Usual rehabilitation care. Measurements. The Functional Independence Measure (FIM) Cognitive and Motor items. Results. A total of 704 (86.5%) participants (mean age = 76.5 years) completed both assessments. Significant improvement in FIM Cognitive items (-score range 3.93–8.74, all ) and FIM Cognitive total score (-score = 9.12, ) occurred, in addition to improvement in FIM Motor performance. A moderate positive correlation existed between change in Motor and Cognitive scores (Spearman’s rho = 0.41). Generalized linear modelling indicated that better cognition at admission (coefficient = 0.398, ) and younger age (coefficient = −0.280, ) were predictive of improvement in Motor performance. Younger age (coefficient = −0.049, ) was predictive of improvement in FIM Cognitive score. Conclusions. Improvement in cognitive functioning was observed in addition to motor function improvement among this population. Causal links cannot be drawn without further research.

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Background Stroke incidence has fallen since 1950. Recent trends suggest that stroke incidence may be stabilizing or increasing. We investigated time trends in stroke occurrence and in-hospital morbidity and mortality in the Calgary Health Region. Methods All patients admitted to hospitals in the Calgary Health Region between 1994 and 2002 with a primary discharge diagnosis code (ICD-9 or ICD-10) of stroke were included. In-hospital strokes were also included. Stroke type, date of admission, age, gender,discharge disposition (died, discharged) and in-hospital complications (pneumonia, pulmonary embolism, deep venous thrombosis) were recorded. Poisson and simple linear regression was used to model time trends of occurrence by stroke type and age-group and to extrapolate future time trends. Results From 1994 to 2002, 11642 stroke events were observed. Of these, 9879 patients (84.8%) were discharged from hospital, 1763 (15.1%) died in hospital, and 591 (5.1%) developed in-hospital complications from pneumonia, pulmonary embolism or deep venous thrombosis. Both in-hospital mortality and complication rates were highest for hemorrhages. Over the period of study, the rate of stroke admission has remained stable. However, total numbers of stroke admission to hospital have faced a significant increase (p=0.012) due to the combination of increases in intracerebral hemorrhage (p=0.021) and ischemic stroke admissions (p=0.011). Sub-arachnoid hemorrhage rates have declined. In-hospital stroke mortality has experienced an overall decline due to a decrease in deaths from ischemic stroke, intracerebral hemorrhage and sub-arachnoid hemorrhage. Conclusions Although age-adjusted stroke occurrence rates were stable from 1994 to 2002, this is associated with both a sharp increase in the absolute number of stroke admissions and decline in proportional in-hospital mortality. Further research is needed into changes in stroke severity over time to understand the causes of declining in-hospital stroke mortality rates.

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Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

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Objective: To compare the effectiveness of the STRATIFY falls tool with nurses’ clinical judgments in predicting patient falls. Study Design and Setting: A prospective cohort study was conducted among the inpatients of an acute tertiary hospital. Participants were patients over 65 years of age admitted to any hospital unit. Sensitivity, specificity, and positive predictive value (PPV) and negative predictive values (NPV) of the instrument and nurses’ clinical judgments in predicting falls were calculated. Results: Seven hundred and eighty-eight patients were screened and followed up during the study period. The fall prevalence was 9.2%. Of the 335 patients classified as being ‘‘at risk’’ for falling using the STRATIFY tool, 59 (17.6%) did sustain a fall (sensitivity50.82, specificity50.61, PPV50.18, NPV50.97). Nurses judged that 501 patients were at risk of falling and, of these, 60 (12.0%) fell (sensitivity50.84, specificity50.38, PPV50.12, NPV50.96). The STRATIFY tool correctly identified significantly more patients as either fallers or nonfallers than the nurses (P50.027). Conclusion: Considering the poor specificity and high rates of false-positive results for both the STRATIFY tool and nurses’ clinical judgments, we conclude that neither of these approaches are useful for screening of falls in acute hospital settings.