Suchergebnisse

INTRODUCTION: The recent global economic crisis is pushing governments worldwide to obtain a more explicit and urgent rationing of resources. The purpose of this study is to provide, through Data Envelopment Analysis (DEA), a methodological framework useful for investigating technical efficiency of hospital care.METHODS: To validate such framework, we compared 50 Italian public hospital trusts (AOs) to identify relative efficient using inputs and outputs from national databases. We also evaluated if, and how, efficiency is affected by various exogenous factors.RESULTS: On average, Italian AOs had an efficiency score of 77% (SD 0.12). Tobit regression model identified a positive association between efficiency and a lower case-mix index, being in the north of the country, in a region with fiscal autonomy, with a higher public and a lower private expenditure on health as % of GDP.CONCLUSIONS: DEA may provide useful and especially objective information regarding the technical efficiency of hospital care and support hospital management and policy makers decisions.

Severe asthma is a subtype of asthma that is difficult to treat and control. By conservative estimates, severe asthma affects approximately 5–10% of patients with asthma worldwide. Severe asthma impairs patients' health-related quality of life, and patients are at risk of life-threatening asthma attacks. Severe asthma also accounts for the majority of health care expenditures associated with asthma. Guidelines recommend that patients with severe asthma be referred to a specialist respiratory team for correct diagnosis and expert management. This is particularly important to ensure that they have access to newly available biologic treatments. However, many patients with severe asthma can suffer multiple asthma attacks and wait several years before they are referred for specialist care. As global patient advocates, we believe it is essential to raise awareness and understanding for patients, caregivers, health care professionals, and the public about the substantial impact of severe asthma and to create opportunities for improving patient care. Patients should be empowered to live a life free of symptoms and the adverse effects of traditional medications (e.g., oral corticosteroids), reducing hospital visits and emergency care, the loss of school and work days, and the constraints placed on their daily lives. Here we provide a Patient Charter for severe asthma, consisting of six core principles, to mobilize national governments, health care providers, payer policymakers, lung health industry partners, and patients/caregivers to address the unmet need and burden in severe asthma and ultimately work together to deliver meaningful improvements in care.

Context Animals' use of space and habitat selection emerges from their movement patterns, which are, in turn, determined by their behavioural or physiological states and extrinsic factors. Aim The aims of the present study were to investigate animal movement and incorporate the movement patterns into habitat selection analyses using Global Positioning System (GPS) location data from 16 black bears (Ursus americanus) in a fragmented area of Florida, USA. Methods Hidden Markov models (HMMs) were used to discern the movement patterns of the bears. These results were then used in step-selection functions (SSFs) to evaluate habitat selection patterns and the factors influencing these patterns. Key results HMMs revealed that black bear movement patterns are best described by three behavioural states: (1) resting (very short step-lengths and large turning angles); (2) encamped (moderate step-lengths and large turning angles); and (3) exploratory (long step-lengths and small turning angles). Bears selected for forested wetlands and marsh wetlands more than any other land cover type, and generally avoided urban areas in all seasons and when in encamped and exploratory behavioural states. Bears also chose to move to locations farther away from major roads. Conclusions Because habitat selection is influenced by how animals move within landscapes, it is essential to consider animals' movement patterns when making inferences about habitat selection. The present study achieves this goal by using HMMs to first discern black bear movement patterns and associated parameters, and by using these results in SSFs to investigate habitat selection patterns. Thus, the methodological framework developed in this study effectively incorporates state-specific movement patterns while making inferences regarding habitat selection. The unified methodological approach employed here will contribute to an improved understanding of animal ecology as well as informed management decisions. Implications Conservation plans focused on preserving forested wetlands would benefit bears by not only providing habitat for resting and foraging, but also by providing connectivity through fragmented landscapes. Additionally, the framework could be applied to species that follow annual cycles and may provide a tool for investigating how animals are using dispersal corridors.

Context
Animals' use of space and habitat selection emerges from their movement patterns, which are, in turn, determined by their behavioural or physiological states and extrinsic factors.

Aim
The aims of the present study were to investigate animal movement and incorporate the movement patterns into habitat selection analyses using Global Positioning System (GPS) location data from 16 black bears (Ursus americanus) in a fragmented area of Florida, USA.

Methods
Hidden Markov models (HMMs) were used to discern the movement patterns of the bears. These results were then used in step-selection functions (SSFs) to evaluate habitat selection patterns and the factors influencing these patterns.

Key results
HMMs revealed that black bear movement patterns are best described by three behavioural states: (1) resting (very short step-lengths and large turning angles); (2) encamped (moderate step-lengths and large turning angles); and (3) exploratory (long step-lengths and small turning angles). Bears selected for forested wetlands and marsh wetlands more than any other land cover type, and generally avoided urban areas in all seasons and when in encamped and exploratory behavioural states. Bears also chose to move to locations farther away from major roads.

Conclusions
Because habitat selection is influenced by how animals move within landscapes, it is essential to consider animals' movement patterns when making inferences about habitat selection. The present study achieves this goal by using HMMs to first discern black bear movement patterns and associated parameters, and by using these results in SSFs to investigate habitat selection patterns. Thus, the methodological framework developed in this study effectively incorporates state-specific movement patterns while making inferences regarding habitat selection. The unified methodological approach employed here will contribute to an improved understanding of animal ecology as well as informed management decisions.

Implications
Conservation plans focused on preserving forested wetlands would benefit bears by not only providing habitat for resting and foraging, but also by providing connectivity through fragmented landscapes. Additionally, the framework could be applied to species that follow annual cycles and may provide a tool for investigating how animals are using dispersal corridors.