Issues using linkage of hospital records and death certificate data to determine the size of a potential palliative care population

BACKGROUND: Studies aiming to identify palliative care populations have used data from death certificates and in some cases hospital records. The size and characteristics of the identified populations can show considerable variation depending on the data sources used. It is important that service planners and researchers are aware of this. AIM: To illustrate the differences in the size and characteristics of a potential palliative care population depending on the differential use of linked hospital records and death certificate data. DESIGN: Retrospective cohort study. SETTING/PARTICIPANTS: The cohort consisted of 23,852 people aged 20 years and over who died in Western Australia between 1 January 2009 and 31 December 2010 after excluding deaths related to pregnancy or trauma. Within this cohort, the number, proportion and characteristics of people who died from one or more of 10 medical conditions considered amenable to palliative care were identified using linked hospital records and death certificate data. RESULTS: Depending on the information source(s) used, between 43% and 73% of the 23,852 people who died had a condition potentially amenable to palliative care identified. The median age at death and the sex distribution of the decedents by condition also varied with the information source. CONCLUSION: Health service planners and researchers need to be aware of the limitations when using hospital records and death certificate data to determine a potential palliative care population. The use of Emergency Department and other administrative data sources could further exacerbate this variation

The effect of modifiable risk factors on geographic mortality differentials: a modelling study

Background Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%. Conclusions These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas. Background: Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods. We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results: Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas - accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men - accounting for 8.8% and 6.3% respectively - and only smoking contributing to the difference in women - accounting for 12.3%. Conclusions: These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas

Issues facing the future health care workforce: the importance of demand modelling

This article examines issues facing the future health care workforce in Australia in light of factors such as population ageing. It has been argued that population ageing in Australia is affecting the supply of health care professionals as the health workforce ages and at the same time increasing the demand for health care services and the health care workforce

Substance use outcomes following treatment : findings from the Australian Patient Pathways Study

Background and Aims: Our understanding of patient pathways through specialist Alcohol and Other Drug (AOD) treatment and broader health/welfare systems in Australia remains limited. This study examined how treatment outcomes are influenced by continuity in specialist AOD treatment, engagement with non-AOD community services, and mutual aid, as well as exploring differences between clients who present with a primary alcohol problem compared to those presenting with a primary drug issue. Method: In a prospective, multi-site treatment outcome study, 796 clients from 21 AOD services in Victoria and Western Australia completed a baseline interview between January 2012 and January 2013. 555 (70%) completed follow-up assessment of subsequent service use and AOD use outcomes 12-months later. Results: Just over half of the participants (52.0%) showed reliable reductions in use of, or abstinence from, their primary drug of concern. This was highest among clients who reported meth/amphetamine (66%) as their primary drug of concern and lowest among those who reported alcohol (47%), with 31% achieving abstinence from all drugs of concern. Continuity of specialist AOD care was associated with higher rates of abstinence than fragmented AOD care. Different predictors of treatment success emerged for clients with a primary drug problem as compared to those with a primary alcohol problem; mutual aid attendance (OR=2.5) and community service engagement (OR=2.0) for clients with alcohol as PDOC, and completion of the index treatment (OR=2.8) and continuity in AOD care (OR=1.8) for those with primary drug issues. Conclusion: This is the first multi-site Australian study to include treatment outcomes for alcohol and cannabis users, who represent 70% of treatment seekers in AOD services. The results suggest a substantial proportion of clients respond positively to treatment, but that clients with alcohol as their primary drug problem may require different treatment pathways, compared to those with illicit drug issues, to achieve desirable outcomes

Contextualising the 'Crisis in Aged Care' in Australia: A demographic perspective

Australia’s ‘old-old’ population is growing even faster than the total aged population and despite improved incomes, living conditions, health risk behaviours and health care this will result in a concomitant increase in the numbers of older people with disabilities. This paper examines ABS 2003 survey data on the incidence of disability among older Australians and their need for, and utilisation of, formal and informal care. It uses this as a basis for projecting the incidence of disability among older Australians and the need for informal and formal care up to 2031. These indicate there is a major challenge since the aged care workforce has grown only slowly in Australia and is concentrated in the older working ages presaging a loss of workers through retirement. There needs to be a significant effort put into attracting workers to both the skilled and unskilled parts of the aged care industry

Trends of emergency department presentations with a mental health diagnosis by age, Australia, 2004–05 to 2016–17:A secondary data analysis

Objectives: The present study aims to explore for Australia: (i) the trends of ED presentations with a mental health (MH) diagnosis by age group; and (ii) whether those trends differ from all ED presentations. Methods: ED presentations to Australian public hospitals, 2004–05 to 2016–17 were captured in the National Non-Admitted Patient Emergency Department Care Database. We assessed total change and annual rate of change in the number and rates of presentations per 10 000 population for all presentations and those with a MH principal diagnosis (ICD-10-AM F00 to F99, MHdx). Multivariable regression was used to assess the trend of the proportion of MHdx presentations. Results: Between 2004–05 and 2016–17, children (0–14 years), followed by older persons (≥65 years) had the highest ED utilisation; while youth (15–24 years) and younger adults (25–34 years) predominated for MHdx presentations. As a proportion of all presentations, MHdx presentations were lowest in children, and highest in people 35–44 years (13.2-times higher than for children). The rate of increase in MHdx presentations was higher than for all presentations in all age groups, reaching almost four times higher for children. Conclusion: The Australian Institute of Health and Welfare should consider expanding the breadth of MH diagnoses they report to better identify the impact of MH on ED presentations. Between 2004–05 and 2016–17, high ED utilisation by children and older persons, and the increasing burden of MHdx presentations for youth, younger adults and children suggest that healthcare planning strategies for urgent and emergency care cannot afford to overlook the growing impact of these sub-groups