192 resultados para Insurance rates.


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Background. From the mid-1980s to mid-1990s, the WHO MONICA Project monitored coronary events and classic risk factors for coronary heart disease (CHD) in 38 populations from 21 countries. We assessed the extent to which changes in these risk factors explain the variation in the trends in coronary-event rates, across the populations. Methods. In men and women aged 35-64 years, non-fatal myocardial infarction and coronary deaths were registered continuously to assess trends in rates of coronary events. We carried out population surveys to estimate trends in risk factors. Trends in event rates were regressed on trends in risk score and in individual risk factors. Findings. Smoking rates decreased in most male populations but trends were mixed in women; mean blood pressures and cholesterol concentrations decreased, body-mass index increased, and overall risk scores and coronary-event rates decreased. The model of trends in 10-year coronary-event rates against risk scores and single risk factors showed a poor fit, but this was improved with a 4-year time lag for coronary events. The explanatory power of the analyses was limited by imprecision of the estimates and homogeneity of trends in the study populations. Interpretation. Changes in the classic risk factors seem to partly explain the variation in population trends in CHD. Residual variance is attributable to difficulties in measurement and analysis, including time lag, and to factors that were not included, such as medical interventions. The results support prevention policies based on the classic risk factors but suggest potential for prevention beyond these.

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The potential that laser based particle accelerators offer to solve sizing and cost issues arising with conventional proton therapy has generated great interest in the understanding and development of laser ion acceleration, and in investigating the radiobiological effects induced by laser accelerated ions. Laser-driven ions are produced in bursts of ultra-short duration resulting in ultra-high dose rates, and an investigation at Queen's University Belfast was carried out to investigate this virtually unexplored regime of cell rdaiobiology. This employed the TARANIS terawatt laser producing protons in the MeV range for proton irradiation, with dose rates exceeding 10 Gys on a single exposure. A clonogenic assay was implemented to analyse the biological effect of proton irradiation on V79 cells, which, when compared to data obtained with the same cell line irradiated with conventionally accelerated protons, was found to show no significant difference. A Relative Biological effectiveness of 1.4±0.2 at 10 % Survival Fraction was estimated from a comparison with a 225 kVp X-ray source. © 2013 SPIE.

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Background: There is a need to review factors related to health service utilisation by the increasing number of cancer survivors in order to inform care planning and the organisation and delivery of services.

Methods: Studies were identified via systematic searches of Medline, PsycINFO, CINAHL, Social Science Citation Index and the SEER-MEDICARE library. Methodological quality was assessed using STROBE; and the Andersen Behavioural Model was used as a framework to structure, organise and analyse the results of the review.

Results: Younger, white cancer survivors were most likely to receive follow-up screening, preventive care, visit their physician, utilise professional mental health services and least likely to be hospitalised. Utilisation rates of other health professionals such as physiotherapists were low. Only studies of health service use conducted in the USA investigated the role of type of health insurance and ethnicity. There appeared to be disparate service use among US samples in terms of ethnicity and socio-demographic status, regardless of type of health insurance provisions- this may be explained by underlying differences in health-seeking behaviours. Overall, use of follow-up care appeared to be lower than expected and barriers existed for particular groups of cancer survivors.

Conclusions: Studies focussed on the use of a specific type of service rather than adopting a whole-system approach and future health services research should address this shortcoming. Overall, there is a need to improve access to care for all cancer survivors. Studies were predominantly US-based focussing mainly on breast or colorectal cancer. Thus, the generalisability of findings to other health-care systems and cancer sites is unclear. The Andersen Behavioural Model provided an appropriate framework for studying and understanding health service use among cancer survivors. The active involvement of physicians and use of personalised care plans are required in order to ensure that post-treatment needs and recommendations for care are met.

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Evidence is presented from three estuarine tide gauges located in the
Sundarban area of southwest Bangladesh of relative sea level rise
substantially in excess of the generally accepted rates from altimetry, as
well as previous tide-gauge analyses. It is proposed that the difference
arises from the use of relative mean sea level (RMSL) to characterise the
present and future coastal flood hazard, since RMSL can be misleading in
estuaries in which tidal range is changing. Three tide gauges, one located in
the uninhabited mangrove forested area (Sundarban) of southwest
Bangladesh, the others in the densely populated polder zone north of the
present Sundarban, show rates of increase in RMSL ranging from 2.8 mm
a-1 to 8.8 mm a-1. However, these trends in RMSL disguise the fact that high
water levels in the polder zone have been increasing at an average rate of
15.9 mm a-1 and a maximum of 17.2 mm a-1. In an area experiencing tidal
range amplification, RMSL will always underestimate the rise in high water
levels; consequently, as an alternative to RMSL, the use of trends in high
water maxima or ‘Effective Sea Level Rise’ (ESLR) is adopted as a more
strategic parameter to characterise the flooding hazard potential. The rate
of increase in ESLR is shown to be due to a combination of deltaic
subsidence, including sediment compaction, and eustatic sea level rise, but
principally as a result of increased tidal range in estuary channels recently
constricted by embankments. These increases in ESLR have been partially
offset by decreases in fresh water discharge in those estuaries connected
to the Ganges. The recognition of increases of the effective sea level in the
Bangladesh Sundarban, which are substantially greater than increases in
mean sea level, is of the utmost importance to flood management in this
low-lying and densely populated area.

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Background: The incidence of nonmelanomatous skin cancer (NMSC) is substantially higher among renal transplant recipients (RTRs) than in the general population. With a growing RTR population, a robust method for monitoring skin cancer rates in this population is required.
Methods: A modeling approach was used to estimate the trends in NMSC rates that adjusted for changes in the RTR population (sex and age), calendar time, the duration of posttransplant follow-up, and background population NMSC incidence rates. RTR databases in both Northern Ireland (NI) and the Republic of Ireland (ROI) were linked to their respective cancer registries for diagnosis of NMSC, mainly squamous cell carcinoma (SCC) and basal cell carcinoma (BCC).
Results: RTRs in the ROI had three times the incidence (P<0.001) of NMSC compared with NI. There was a decline (P<0.001) in NMSC 10-year cumulative incidence rate in RTRs over the period 1994–2009, which was driven by reductions in both SCC and BCC incidence rates. Nevertheless, there was an increase in the incidence of NMSC with time since transplantation. The observed graft survival was higher in ROI than NI (P<0.05) from 1994–2004. The overall patient survival of RTRs was similar in NI and ROI.
Conclusion: Appropriate modeling of incidence trends in NMSC among RTRs is a valuable surveillance exercise for assessing the impact of change in clinical practices over time on the incidence rates of skin cancer in RTRs. It can form the basis of further research into unexplained regional variations in NMSC incidence.

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Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.

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Trajectory surface hopping (TSH) is one of the most widely used quantum-classical algorithms for nonadiabatic molecular dynamics. Despite its empirical effectiveness and popularity, a rigorous derivation of TSH as the classical limit of a combined quantum electron-nuclear dynamics is still missing. In this work, we aim to elucidate the theoretical basis for the widely used hopping rules. Naturally, we concentrate thereby on the formal aspects of the TSH. Using a Gaussian wave packet limit, we derive the transition rates governing the hopping process at a simple avoided level crossing. In this derivation, which gives insight into the physics underlying the hopping process, some essential features of the standard TSH algorithm are retrieved, namely (i) non-zero electronic transition rate ("hopping probability") at avoided crossings; (ii) rescaling of the nuclear velocities to conserve total energy; (iii) electronic transition rates linear in the nonadiabatic coupling vectors. The well-known Landau-Zener model is then used for illustration. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4770280]

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he double-detonation explosion scenario of Type Ia supernovae (SNe Ia) has gained increased support from the SN Ia community as a viable progenitor model, making it a promising candidate alongside the well-known single degenerate and double degenerate scenarios. We present delay times of double-detonation SNe, in which a sub-Chandrasekhar mass carbon–oxygen white dwarf (WD) accretes non-dynamically from a helium-rich companion. One of the main uncertainties in quantifying SN rates from double detonations is the (assumed) retention efficiency of He-rich matter. Therefore, we implement a new prescription for the treatment of accretion/accumulation of He-rich matter on WDs. In addition, we test how the results change depending on which criteria are assumed to lead to a detonation in the helium shell. In comparing the results to our standard case (Ruiter et al.), we find that regardless of the adopted He accretion prescription, the SN rates are reduced by only ∼25 per cent if low-mass He shells (≲0.05 M⊙) are sufficient to trigger the detonations. If more massive (0.1 M⊙) shells are needed, the rates decrease by 85 per cent and the delay time distribution is significantly changed in the new accretion model – only SNe with prompt (<500 Myr) delay times are produced. Since theoretical arguments favour low-mass He shells for normal double-detonation SNe, we conclude that the rates from double detonations are likely to be high, and should not critically depend on the adopted prescription for accretion of He.

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The influence of oscillatory versus unidirectional flow on the growth and nitrate-uptake rates of juvenile kelp, Laminaria digitata, was determined seasonally in experimental treatments that simulated as closely as possible natural environmental conditions. In winter, regardless of flow condition (oscillatory and unidirectional) or water velocity, no influence of water motion was observed on the growth rate of L. digitata. In summer, when ambient nitrate concentrations were low, increased water motion enhanced macroalgal growth, which is assumed to be related to an increase in the rate of supply of nutrients to the blade surface. Nitrate-uptake rates were significantly influenced by water motion and season. Lowest nitrate-uptake rates were observed for velocities <5 cm · s−1 and nitrate-uptake rates increased by 20%–50% under oscillatory motion compared to unidirectional flow at the same average speed. These data further suggested that the diffusion boundary layer played a significant role in influencing nitrate-uptake rates. However, while increased nitrate-uptake in oscillatory flow was clear, this was not reflected in growth rates and further work is required to understand the disconnection of nitrate-uptake and growth by L. digitata in oscillatory flow. The data obtained support those from related field-based studies, which suggest that in summer, when insufficient nitrogen is available in the water to saturate metabolic demand, the growth rate of kelps will be influenced by water motion restricting mass transfer of nitrogen.

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In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

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Reducible diffusions (RDs) are nonlinear transformations of analytically solvable Basic Diffusions (BDs). Hence, by construction RDs are analytically tractable and flexible diffusion processes. Existing literature on RDs has mostly focused on time-homogeneous transformations, which to a significant extent fail to explore the full potential of RDs from both theoretical and practical points of view. In this paper, we propose flexible and economically justifiable time variations to the transformations of RDs. Concentrating on the Constant Elasticity Variance (CEV) RDs, we consider nonlinear dynamics for our time-varying transformations with both deterministic and stochastic designs. Such time variations can greatly enhance the flexibility of RDs while maintaining sufficient tractability of the resulting models. In the meantime, our modeling approach enjoys the benefits of classical inferential techniques such as the Maximum Likelihood (ML). Our application to the UK and the US short-term interest rates suggests that from an empirical point of view time-varying transformations are highly relevant and statistically significant. We expect that the proposed models can describe more truthfully the dynamic time-varying behavior of economic and financial variables and potentially improve out-of-sample forecasts significantly.

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In recent years, the issue of life expectancy has become of utmost importance to pension providers, insurance companies, and government bodies in the developed world. Significant and consistent improvements in mortality rates and hence life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data to anticipate future life expectancy and hence quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age, and cohort and forecast these trends into the future by using standard statistical methods. These approaches rely on the assumption that structural breaks in the trend do not exist or do not have a significant impact on the mortality forecasts. Recent literature has started to question this assumption. In this paper, we carry out a comprehensive investigation of the presence or of structural breaks in a selection of leading mortality models. We find that structural breaks are present in the majority of cases. In particular, we find that allowing for structural break, where present, improves the forecast result significantly.

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The area of mortality modelling has received significant attention over the last 20 years owing to the need to quantify and forecast improving mortality rates. This need is driven primarily by the concern of governments, professionals, insurance and actuarial professionals and individuals to be able to fund their old age. In particular, to quantify the costs of increasing longevity we need suitable model of mortality rates that capture the dynamics of the data and forecast them with sufficient accuracy to make them useful. In this paper we test several of those models by considering the fitting quality and in particular, testing the residuals of those models for normality properties. In a wide ranging study considering 30 countries we find that almost exclusively the residuals do not demonstrate normality. Further, in Hurst tests of the residuals we find evidence that structure remains that is not captured by the models.

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Pseudomonas aeruginosa is an important cause of pulmonary infection in cystic fibrosis (CF). Its correct identification ensures effective patient management and infection control strategies. However, little is known about how often CF sputum isolates are falsely identified as P. aeruginosa. We used P. aeruginosa-specific duplex real-time PCR assays to determine if 2,267 P. aeruginosa sputum isolates from 561 CF patients were correctly identified by 17 Australian clinical microbiology laboratories. Misidentified isolates underwent further phenotypic tests, amplified rRNA gene restriction analysis, and partial 16S rRNA gene sequence analysis. Participating laboratories were surveyed on how they identified P. aeruginosa from CF sputum. Overall, 2,214 (97.7%) isolates from 531 (94.7%) CF patients were correctly identified as P. aeruginosa. Further testing with the API 20NE kit correctly identified only 34 (59%) of the misidentified isolates. Twelve (40%) patients had previously grown the misidentified species in their sputum. Achromobacter xylosoxidans (n = 21), Stenotrophomonas maltophilia (n = 15), and Inquilinus limosus (n = 4) were the species most commonly misidentified as P. aeruginosa. Overall, there were very low rates of P. aeruginosa misidentification among isolates from a broad cross section of Australian CF patients. Additional improvements are possible by undertaking a culture history review, noting colonial morphology, and performing stringent oxidase, DNase, and colistin susceptibility testing for all presumptive P. aeruginosa isolates. Isolates exhibiting atypical phenotypic features should be evaluated further by additional phenotypic or genotypic identification techniques.