14 resultados para Lifetime Homes

em University of Queensland eSpace - Australia


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Objective: To identify determinants of PRN ( as needed) drug use in nursing homes. Decisions about the use of these medications are made expressly by nursing home staff when general medical practitioners (GPs) prescribe medications for PRN use. Method: Cross-sectional drug use data were collected during a 7-day window from 13 Australian nursing homes. Information was collected on the size, staffing-mix, number of visiting GPs, number of medication rounds, and mortality rates in each nursing home. Resident specific measures collected included age, gender, length of stay, recent hospitalisation and care needs. Main outcome measures: The number of PRN orders prescribed per resident and the number of PRN doses given per week averaged over the number of PRN medications given at all in the seven-day period. Results: Approximately 35% of medications were prescribed for PRN use. Higher PRN use was found for residents with the lower care needs, recent hospitalisation and more frequent doses of regularly scheduled medications. With increasing length of stay, PRN medication orders initially increased then declined but the number of doses given declined from admission. While some resident-specific characteristics did influence PRN drug use, the key determinant for PRN medication orders was the specific nursing home in which a resident lived. Resident age and gender were not determinants of PRN drug use. Conclusion: The determinants of PRN drug use suggest that interventions to optimize PRN medications should target the care of individual residents, prescribing and the nursing home processes and policies that govern PRN drug use.

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In the last few decades, private health insurance rates have declined in many countries. In countries and states with community rating, a major cause is adverse selection. In order to address age-based adverse selection, Australia has recently begun a novel approach which imposes stiff penalties for buying private insurance later in life, when expected costs are higher. In this paper, we analyze Australiarsquos Lifetime Cover in the context of a modified version of the Rothschild-Stiglitz insurance model (Rothschild and Stiglitz, 1976). We allow empirically-based probabilities to increase by age for low-risk types. The model highlights the shortcomings of the Australian plan. Based on empirically-based probabilities of illness, we predict that Lifetime Cover will not arrest adverse selection. The model has many policy implications for government regulation encouraging long-term health coverage.

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The measurement of lifetime prevalence of depression in cross-sectional surveys is biased by recall problems. We estimated it indirectly for two countries using modelling, and quantified the underestimation in the empirical estimate for one. A microsimulation model was used to generate population-based epidemiological measures of depression. We fitted the model to 1-and 12-month prevalence data from the Netherlands Mental Health Survey and Incidence Study (NEMESIS) and the Australian Adult Mental Health and Wellbeing Survey. The lowest proportion of cases ever having an episode in their life is 30% of men and 40% of women, for both countries. This corresponds to a lifetime prevalence of 20 and 30%, respectively, in a cross-sectional setting (aged 15-65). The NEMESIS data were 38% lower than these estimates. We conclude that modelling enabled us to estimate lifetime prevalence of depression indirectly. This method is useful in the absence of direct measurement, but also showed that direct estimates are underestimated by recall bias and by the cross-sectional setting.

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This paper considers the problem of inducing low-risk individuals of all ages to buy private health insurance in Australia. Our proposed subsidy scheme improves upon the age-based penalty scheme under the current "Australian Lifetime Cover" (LTC) scheme. We generate an alternative subsidy profile that obviates adverse selection in private health insurance markets with mandated, age-based, community rating. Our proposal is novel in that we generate subsidies that are both risk- and age-specific, based upon actual risk probabilities. The approach we take may prove useful in other jurisdictions where the extant law mandates community rating in private health insurance markets. Furthermore, our approach is useful in jurisdictions that seek to maintain private insurance to complement existing universal public systems.

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Background: Recent work has demonstrated that the lifetime suicide risk for patients with DSM IV Major Depression cannot mathematically approximate the accepted figure of 15%. Gender and age significantly affect both the prevalence of major depression and suicide risk, Methods: Gender and age stratified calculations were made on the entire population of the USA in 1994 using a mathematical algorithm. Sex specific corrections for under-reporting were incorporated into the design. Results: The lifetime suicide risks for men and women were 7% and 1%, respectively. The combined risk was 3.4%. The male:female ratio for suicide risk in major depression was 10:1 for youths under 25, and 5.6:1 for adults. Conclusions: Suicide in major depression is predominantly a male problem, although complacency towards female sufferers is to be avoided. Diagnosis of major depression is of limited help in predicting suicide risk compared to case specific factors. The male experience of depression that leads to suicide is often not identified as a legitimate medical complaint by either sufferers or professionals. Increasing help-accessing by males is a priority. Clinical implications: Patients with a history of hospitalisation; comorbidity, especially for substance abuse; and who are male, require greater vigilance for suicide risk. It may be that for males che threshold for diagnosing and treating major depression needs to be lowered. Limitations: This research is based on a mathematical algorithm to approximate a life-long longitudinal study that identifies community cases of depression. Our findings therefore rely on the validity of the statistics used. Extrapolation is limited to populations with an actual suicide rate of 17/100,000 or less and a lifetime prevalence of major depression of 17% or more. (C) 1999 Elsevier Science B.V. All rights reserved.

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