8 resultados para hospital service

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Background Young children are known to be the most frequent hospital users compared to older children and young adults. Therefore, they are an important population from economic and policy perspectives of health care delivery. In Switzerland complete hospitalization discharge records for children [<5 years] of four consecutive years [2002–2005] were evaluated in order to analyze variation in patterns of hospital use. Methods Stationary and outpatient hospitalization rates on aggregated ZIP code level were calculated based on census data provided by the Swiss federal statistical office (BfS). Thirty-seven hospital service areas for children [HSAP] were created with the method of "small area analysis", reflecting user-based health markets. Descriptive statistics and general linear models were applied to analyze the data. Results The mean stationary hospitalization rate over four years was 66.1 discharges per 1000 children. Hospitalizations for respiratory problem are most dominant in young children (25.9%) and highest hospitalization rates are associated with geographical factors of urban areas and specific language regions. Statistical models yielded significant effect estimates for these factors and a significant association between ambulatory/outpatient and stationary hospitalization rates. Conclusion The utilization-based approach, using HSAP as spatial representation of user-based health markets, is a valid instrument and allows assessing the supply and demand of children's health care services. The study provides for the first time estimates for several factors associated with the large variation in the utilization and provision of paediatric health care resources in Switzerland.

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BACKGROUND Avoidable hospitalizations (AH) are hospital admissions for diseases and conditions that could have been prevented by appropriate ambulatory care. We examine regional variation of AH in Switzerland and the factors that determine AH. METHODS We used hospital service areas, and data from 2008-2010 hospital discharges in Switzerland to examine regional variation in AH. Age and sex standardized AH were the outcome variable, and year of admission, primary care physician density, medical specialist density, rurality, hospital bed density and type of hospital reimbursement system were explanatory variables in our multilevel poisson regression. RESULTS Regional differences in AH were as high as 12-fold. Poisson regression showed significant increase of all AH over time. There was a significantly lower rate of all AH in areas with more primary care physicians. Rates increased in areas with more specialists. Rates of all AH also increased where the proportion of residences in rural communities increased. Regional hospital capacity and type of hospital reimbursement did not have significant associations. Inconsistent patterns of significant determinants were found for disease specific analyses. CONCLUSION The identification of regions with high and low AH rates is a starting point for future studies on unwarranted medical procedures, and may help to reduce their incidence. AH have complex multifactorial origins and this study demonstrates that rurality and physician density are relevant determinants. The results are helpful to improve the performance of the outpatient sector with emphasis on local context. Rural and urban differences in health care delivery remain a cause of concern in Switzerland.

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BACKGROUND: In general cantons regulate and control the Swiss health service system; patient flows within and between cantons are thereby partially disregarded. This paper develops an alternative spatial model, based upon the construction of orthopedic hospital service areas (HSAOs), and introduces indices for the analysis of patient streams in order to identify areas, irrespective of canton, with diverse characteristics, importance, needs, or demands. METHODS: HSAOs were constructed using orthopedic discharge data. Patient streams between the HSAOs were analysed by calculating three indices: the localization index (% local residents discharged locally), the netindex (the ratio of discharges of nonlocal incoming residents to outgoing local residents), and the market share index (% of local resident discharges of all discharges in local hospitals). RESULTS: The 85 orthopedic HSAOs show a median localization index of 60.8%, a market share index of 75.1%, and 30% of HSAOs have a positive netindex. Insurance class of bed, admission type, and patient age are partially but significantly associated with those indicators. A trend to more centrally provided health services can be observed not only in large urban HSAOs such as Geneva, Bern, Basel, and Zurich, but also in HSAOs in mountain sport areas such as Sion, Davos, or St.Moritz. Furthermore, elderly and emergency patients are more frequently treated locally than younger people or those having elective procedures. CONCLUSION: The division of Switzerland into HSAOs provides an alternative spatial model for analysing and describing patient streams for health service utilization. Because this small area model allows more in-depth analysis of patient streams both within and between cantons, it may improve support and planning of resource allocation of in-patient care in the Swiss healthcare system.

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BACKGROUND: Climate- or holiday-related seasonality in hospital admission rates is well known for many diseases. However, little research has addressed the impact of tourism on seasonality in admission rates. We therefore investigated the influence of tourism on emergency admission rates in Switzerland, where winter and summer leisure sport activities in large mountain regions can generate orthopedic injuries. METHODS: Using small area analysis, orthopedic hospital service areas (HSAo) were evaluated for seasonality in emergency admission rates. Winter sport areas were defined using guest bed accommodation rate patterns of guest houses and hotels located above 1000 meters altitude that show clear winter and summer peak seasons. Emergency admissions (years 2000-2002, n = 135'460) of local and nonlocal HSAo residents were evaluated. HSAo were grouped according to their area type (regular or winter sport area) and monthly analyses of admission rates were performed. RESULTS: Of HSAo within the defined winter sport areas 70.8% show a seasonal, summer-winter peak hospital admission rate pattern and only 1 HSAo outside the defined winter sport areas shows such a pattern. Seasonal hospital admission rates in HSAo in winter sport areas can be up to 4 times higher in winter than the intermediate seasons, and they are almost entirely due to admissions of nonlocal residents. These nonlocal residents are in general -and especially in winter- younger than local residents, and nonlocal residents have a shorter length of stay in winter sport than in regular areas. The overall geographic distribution of nonlocal residents admitted for emergencies shows highest rates during the winter as well as the summer in the winter sport areas. CONCLUSION: Small area analysis using orthopedic hospital service areas is a reliable method for the evaluation of seasonality in hospital admission rates. In Switzerland, HSAo defined as winter sport areas show a clear seasonal fluctuation in admission rates of only nonlocal residents, whereas HSAo defined as regular, non-winter sport areas do not show such seasonality. We conclude that leisure sport, and especially ski/snowboard tourism demands great flexibility in hospital beds, staff and resource planning in these areas.

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The study systematically describes the frequency and geographic variability of major surgical interventions for musculoskeletal disorders in Switzerland. Age- and sex-standardized rates for joint replacements, arthroscopies, spine surgery and hip fracture repair were calculated for hospital service regions. Various statistical analyses were used to measure the extent of variation. The authors argue that the surgery of hip fractures can be used as index surgery in the context of analyzing variations in orthopedic surgery. Temporal trends imply that patient demand and supply factors related to clinical ambiguity and non-medical incentives of providers are far more important components leading to increased use than the sole effect of an aging population.

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OBJECTIVES: To validate the Probability of Repeated Admission (Pra) questionnaire, a widely used self-administered tool for predicting future healthcare use in older persons, in three European healthcare systems. DESIGN: Prospective study with 1-year follow-up. SETTING: Hamburg, Germany; London, United Kingdom; Canton of Solothurn, Switzerland. PARTICIPANTS: Nine thousand seven hundred thirteen independently living community-dwelling people aged 65 and older. MEASUREMENTS: Self-administered eight-item Pra questionnaire at baseline. Self-reported number of hospital admissions and physician visits during 1 year of follow-up. RESULTS: In the combined sample, areas under the receiver operating characteristic curves (AUCs) were 0.64 (95% confidence interval (CI)=0.62-0.66) for the prediction of one or more hospital admissions and 0.68 (95% CI=0.66-0.69) for the prediction of more than six physician visits during the following year. AUCs were similar between sites. In comparison, prediction models based on a person's age and sex alone exhibited poor predictive validity (AUC or= 0.5) were 2.3 times as likely (95% CI=2.1-2.6) as low-risk individuals to have a hospital admission, and 2.1 times as likely (95% CI=2.0-2.2) to have more than six physician visits. CONCLUSION: The Pra instrument exhibits good validity for predicting future health service use on a population level in different healthcare settings. Administrative data have shown similar predictive validity, but in practice, such data are often not available. The Pra is likely of high interest to governments and health insurance companies worldwide as a basis for programs aimed at health risk management in older persons.

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BACKGROUND: Epidemiological data for south Asian children in the United Kingdom are contradictory, showing a lower prevalence of wheeze, but a higher rate of medical consultations and admissions for asthma compared with white children. These studies have not distinguished different asthma phenotypes or controlled for varying environmental exposures. OBJECTIVE: To compare the prevalence of wheeze and related health-service use in south Asian and white pre-schoolchildren in the United Kingdom, taking into account wheeze phenotype (viral and multiple wheeze) and environmental exposures. METHODS: A postal questionnaire was completed by parents of a population-based sample of 4366 white and 1714 south Asian children aged 1-4 years in Leicestershire, UK. Children were classified as having viral wheeze or multiple trigger wheeze. RESULTS: The prevalence of current wheeze was 35.6% in white and 25.5% in south Asian 1-year-olds (P<0.001), and 21.9% and 20.9%, respectively, in children aged 2-4 years. Odds ratios (ORs) (95% confidence interval) for multiple wheeze and for viral wheeze, comparing south Asian with white children, were 2.21 (1.19-4.09) and 1.43 (0.77-2.65) in 2-4-year-olds after controlling for socio-economic conditions, environmental exposures and family history. In 1-year-olds, the respective ORs for multiple and viral wheeze were 0.66 (0.47-0.92) and 0.81 (0.64-1.03). Reported GP consultation rates for wheeze and hospital admissions were greater in south Asian children aged 2-4 years, even after adjustment for severity, but the use of inhaled corticosteroids was lower. CONCLUSIONS: South Asian 2-4-year-olds are more likely than white children to have multiple wheeze (a condition with many features of chronic atopic asthma), after taking into account ethnic differences in exposure to some environmental agents. Undertreatment with inhaled corticosteroids might partly explain their greater use of health services.

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IMPORTANCE Because effective interventions to reduce hospital readmissions are often expensive to implement, a score to predict potentially avoidable readmissions may help target the patients most likely to benefit. OBJECTIVE To derive and internally validate a prediction model for potentially avoidable 30-day hospital readmissions in medical patients using administrative and clinical data readily available prior to discharge. DESIGN Retrospective cohort study. SETTING Academic medical center in Boston, Massachusetts. PARTICIPANTS All patient discharges from any medical services between July 1, 2009, and June 30, 2010. MAIN OUTCOME MEASURES Potentially avoidable 30-day readmissions to 3 hospitals of the Partners HealthCare network were identified using a validated computerized algorithm based on administrative data (SQLape). A simple score was developed using multivariable logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort. RESULTS Among 10 731 eligible discharges, 2398 discharges (22.3%) were followed by a 30-day readmission, of which 879 (8.5% of all discharges) were identified as potentially avoidable. The prediction score identified 7 independent factors, referred to as the HOSPITAL score: h emoglobin at discharge, discharge from an o ncology service, s odium level at discharge, p rocedure during the index admission, i ndex t ype of admission, number of a dmissions during the last 12 months, and l ength of stay. In the validation set, 26.7% of the patients were classified as high risk, with an estimated potentially avoidable readmission risk of 18.0% (observed, 18.2%). The HOSPITAL score had fair discriminatory power (C statistic, 0.71) and had good calibration. CONCLUSIONS AND RELEVANCE This simple prediction model identifies before discharge the risk of potentially avoidable 30-day readmission in medical patients. This score has potential to easily identify patients who may need more intensive transitional care interventions.