73 resultados para Insurance Costs.
Resumo:
The cost-effectiveness of novel interventions in the treatment of cancer is well researched; however, relatively little attention is paid to the cost of many aspects of routine care. Oesophageal cancer is the ninth most common cancer in the UK and sixth most common cause of cancer death. It usually presents late and has a poor prognosis. The hospital costs incurred by oesophageal cancer patients diagnosed in Northern Ireland in 2005 (n = 198) were determined by review of medical records. The average cost of hospital care per patient in the 12 months from presentation was £7847. Variations in total hospital costs by age at diagnosis, gender, cancer stage, histological type, mortality at 1 year, co-morbidity count and socio-economic status were analysed using multiple regression analyses. Higher costs were associated with earlier stages of cancer and cancer stage remained a significant predictor of costs after controlling for cancer type, patient age and mortality at 1 year. Thus, although early detection of cancer usually improves survival, this would mean increased costs in the first year. Deprivation achieved borderline significance with those from more deprived areas having lower resource consumption relative to the more affluent. © 2013 John Wiley & Sons Ltd.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
BACKGROUND: The number of patients with advanced chronic kidney disease opting for conservative management rather than dialysis is unknown but likely to be growing as increasingly frail patients with advanced renal disease present to renal services. Conservative kidney management includes ongoing medical input and support from a multidisciplinary team. There is limited evidence concerning patient and carer experience of this choice. This study will explore quality of life, symptoms, cognition, frailty, performance decision making, costs and impact on carers in people with advanced chronic kidney disease managed without dialysis and is funded by the National Institute of Health Research in the UK.
METHODS: In this prospective, multicentre, longitudinal study, patients will be recruited in the UK, by renal research nurses, once they have made the decision not to embark on dialysis. Carers will be asked to 'opt-in' with consent from patients. The approach includes longitudinal quantitative surveys of quality of life, symptoms, decision making and costs for patients and quality of life and costs for carers, with questionnaires administered quarterly over 12 months. Additionally, the decision making process will be explored via qualitative interviews with renal physicians/clinical nurse specialists.
DISCUSSION: The study is designed to capture patient and carer profiles when conservative kidney management is implemented, and understand trajectories of care-receiving and care-giving with the aim of optimising palliative care for this population. It will explore the interactions that lead to clinical care decisions and the impact of these decisions on informal carers with the intention of improving clinical outcomes for patients and the experiences of care givers.
Resumo:
Objectives The increasing prevalence of overweight and obesity worldwide continues to compromise population health and creates a wider societal cost in terms of productivity loss and premature mortality. Despite extensive international literature on the cost of overweight and obesity, findings are inconsistent between Europe and the USA, and particularly within Europe. Studies vary on issues of focus, specific costs and methods. This study aims to estimate the healthcare and productivity costs of overweight and obesity for the island of Ireland in 2009, using both top-down and bottom-up approaches.
Methods Costs were estimated across four categories: healthcare utilisation, drug costs, work absenteeism and premature mortality. Healthcare costs were estimated using Population Attributable Fractions (PAFs). PAFs were applied to national cost data for hospital care and drug prescribing. PAFs were also applied to social welfare and national mortality data to estimate productivity costs due to absenteeism and premature mortality.
Results The healthcare costs of overweight and obesity in 2009 were estimated at €437 million for the Republic of Ireland (ROI) and €127.41 million for NI. Productivity loss due to overweight and obesity was up to €865 million for ROI and €362 million for NI. The main drivers of healthcare costs are cardiovascular disease, type II diabetes, colon cancer, stroke and gallbladder disease. In terms of absenteeism, low back pain is the main driver in both jurisdictions, and for productivity loss due to premature mortality the primary driver of cost is coronary heart disease.
Conclusions The costs are substantial, and urgent public health action is required in Ireland to address the problem of increasing prevalence of overweight and obesity, which if left unchecked will lead to unsustainable cost escalation within the health service and unacceptable societal costs.