Model migration age schedules have proved valuable to demographers for a range of applications for over 40 years. The original Rogers-Castro curve has been extended over time to include a retirement curve, a post-retirement curve, and a student peak. With demographic analyses extending to higher age groups than in the past due to population ageing, it is important for the model schedule to faithfully reflect migration patterns at advanced ages. Recent data on internal migration in the nonagenarian and centenarian ages reveals several examples of rising then falling mobility with increasing age. This paper suggests an alternative specification of the post-retirement curve of the model schedule to reflect this pattern. The modified model migration schedule is successfully fitted to example internal migration age patterns from Australia, Canada and the Netherlands. The modified schedule should prove useful in preparing input data for population projections and analyses of migration age patterns extending to the highest ages.

Australia’s population at the highest ages is growing rapidly, driving increasing demand for a whole range of services often required at advanced ages. Unfortunately, official population statistics tend to become less accurate as age increases, especially in the centenarian ages. The aims of the paper are to (i) describe the growth of Australia’s population at the highest ages using methods which provide greater accuracy and more detail than is available from official statistical sources; (ii) understand the demographic drivers of population growth at these ages; and (iii) urge caution with the use of official population data at the highest ages, and warn of some of the implications of doing so. State-of-the-art Extinct Generation and Survivor Ratio methods were employed to prepare robust estimates of Australia’s population by sex and single years of age for each year of the period 1971 to 2018. Results show that Australia’s population at the highest ages is growing very quickly. Over the 20 years to 2018 nonagenarians (those aged 90-99) grew in number from 63,000 to 181,000 (an increase of 185%), but centenarians (aged 100+) increased at an even faster rate, growing by 215% (from about 1,300 to 4,200). Official population estimates can be relied upon up to about age 85, but at higher ages the quality of single year of age population numbers may be poor. We encourage the ABS to adopt the methods described in this paper to produce official population estimates at the highest ages.

OBJECTIVES: To assess levels of numerical, structural, timing and spatial aspects of ageing of the Aboriginal and Torres Strait Islander population. METHODS: Population projections for 15 Australian regions were created by a multi-state cohort-component model. RESULTS: The older (45-plus) population grew from 29,815 in 1986 to 167,259 in 2016. In the subsequent 30 years, we project growth to 448,785 people. Growth rates of the older population vary: from 200% in the 60-64-year-old group to 800% growth in the 85-plus age group by mid-century. This strong numerical ageing is reflected in a shift in structural ageing by about six percentage points. Selected areas outside of capital cities are structurally older than many cities. Numerical ageing is strongest in capital cities and New South Wales. Cohort flow is the primary driver of ageing. CONCLUSIONS: Numerical and structural ageing is projected to increase significantly to mid-century with important spatial variations. Population ageing is largely irreversible. Implications for public health: High numerical growth in the older Aboriginal and Torres Strait Islander population poses implications for increased demand for a range of health and care services. Variations in spatial and timing aspects of ageing indicate demand will peak earlier in some geographical locations relative to others.

The Australian Aboriginal and Torres Strait Islander population more than doubled in size between 1996 and 2016. Growth was highest in urban areas and lower in rural and remote areas. An important contributor to growth was identification change, whereby individuals report their Aboriginal status differently over time. Official population projections in Australia currently do not incorporate this phenomenon, leading to underestimation of future populations which affects policies, targets and planning for demand‐based services. We outline a new projection model to improve subnational estimates of future regional population growth by endogenizing identification change and Aboriginal/non‐Aboriginal childbearing. Results suggest that growth will be higher than currently projected, especially in urban‐dominated regions in New South Wales and Queensland where identification change is projected to account for more than 50% of growth. There will also be considerable population ageing, which has implications for services and policies relevant to Aboriginal and Torres Strait Islander people.

This updated edition will assist readers in their research by providing factual information, historical perspectives, theoretical approaches, reviews of literature, and provocative topical discussions that will stimulate creative thinking.

OBJECTIVES: The aim is to present updated estimates of the size of Australia's sexual minority adult population (gay, lesbian, bisexual, and other sexual minority identities). No estimate of this population is currently available from the Australian Bureau of Statistics, and very little is available from other sources. We obtained data on sexual minority identities from three data collections of two national surveys of recent years. Combining averaged prevalence rates from these surveys with official Estimated Resident Population data, we produce estimates of Australia's sexual minority population for recent years. RESULTS: According to percentages averaged across the three survey datasets, 3.6% of males and 3.4% of females described themselves with a minority sexual identity. When applied to Estimated Resident Populations, this gives a sexual minority population at ages 18 + in Australia of 599,500 in 2011 and 651,800 in 2016. Population estimates were also produced by sex and broad age group, revealing larger numbers and higher sexual minority percentages in the younger age groups, and smaller numbers and percentages in the oldest age group. Separate population estimates were also prepared for lesbian, gay, bisexual, and other sexual minority identities.

Victorian local governments (LGs) are required to develop evidence-based Municipal Public Health and Wellbeing Plans (MPHWPs) that improve health and wellbeing. This study evaluated the implementation of this requirement across 79 LGs. Evidence in 116 documents was categorised by source, issue, and policy specificity. Over 11,000 evidence-occurrences from 200 sources were recorded. More evidence on social determinants was identified than on epidemiology or health behaviours. Most (96%) evidence was descriptive and only 4% supported MPHWP actions. The results suggest the community is an important source of novel interventions, and proposes three related reasons for the dearth of intervention level evidence.

BACKGROUND: Rates of low-value care vary between hospitals in New South Wales, Australia. Understanding factors associated with this variation will help in understanding the drivers of low-value care and in planning initiatives to reduce low-value care. METHODS: For eight low-value procedures, we used Poisson regression of the number of low-value episodes at each hospital to assess the association between low-value care and hospital characteristics. We also used hierarchical clustering on the low-value procedures used and their rates at each hospital to try to identify groups of hospitals with higher or lower rates of low-value care across multiple procedures. RESULTS: Some hospital characteristics, such as hospital peer group and proportion of total episodes that involve the specific procedure, showed associations for some procedures, but none were consistent across all eight procedures. We clustered hospitals into five groups, but low-value care rates did not differ much between these groups. CONCLUSION: Available hospital variables show little association with rates of low-value care and no patterns across different low-value procedures. We need to investigate factors within hospitals, such as clinician knowledge and beliefs about low-value care.

INTRODUCTION: A new healthcare standard (Standard 5: Comprehensive Care) has been introduced by the Australian Commission on Safety and Quality in Healthcare. Standard 5 advocates for organisational leadership to develop and maintain systems and processes to deliver patient-centred comprehensive care plans that include appropriate screening to identify and mitigate risks associated with hospitalisation. The aim of this study is to evaluate the effectiveness and cost effectiveness of a comprehensive care and risk evaluation (Comprehensive Assessment and Risk Evaluation (CARE)) plan to reduce hospital acquired complications (HACs) in an Australian hospital network. METHODS AND ANALYSIS: This study will comprise a mixed-method pre and post implementation concurrent triangulation evaluation design. The primary clinical outcome will assess the reduction of routinely reported HACs (pressure care and falls), selected based on the likely reliability of routinely collected data prior to implementation. Secondary clinical outcomes will include length of stay and activity-based costing data for each episode, in-hospital mortality, expected and unplanned readmissions within 28 days, compliance with CARE plan completion and referrals for at risk patients, staff satisfaction, patient satisfaction and barriers and enablers to implementation. We expect that the incidence of other HACs (malnutrition, delirium, violence and aggression, and suicide and self-harm) may increase as routine methods for assessing risk were not in place prior to implementation of the CARE plan. We will therefore collect data on incidence of these HACs as tertiary outcomes. Our primary cost-effectiveness outcome will be calculation of an incremental cost-effectiveness ratio. ETHICS AND DISSEMINATION: Ethics approval has been received from Northern Health Low Risk Ethics Committee. The results of this study will be published in peer-reviewed journals and presented at conferences.

INTRODUCTION: Surveys and qualitative studies suggest that women physicians may delay childbearing, be at increased risk of adverse peripartum complications when they do become pregnant, and face discrimination and lower earnings as a result of parenthood. Observational studies enrolling large, representative samples of women physicians are needed to accurately evaluate their reproductive patterns, pregnancy outcomes, parental leave practices and earnings. This protocol provides a detailed research plan for such studies. METHODS AND ANALYSIS: The Dr Mom Cohort Study encompasses a series of retrospective observational studies of women physicians in Ontario, Canada. All practising physicians in Ontario are registered with the College of Physicians and Surgeons of Ontario (CPSO). By linking a dataset of physicians from the CPSO to existing provincial administrative databases, which hold health data and physician billing records, we will be able to retrospectively assess the healthcare utilisation, work practices and pregnancy outcomes of women physicians at the population level. Specific outcomes of interest include: (1) rates and timing of pregnancy; (2) pregnancy-related care and complications; and (3) duration of parental leave and subsequent earnings, each of which will be evaluated with regression methods appropriate to the form of the outcome. We estimate that, at minimum, 5000 women physicians will be eligible for inclusion. ETHICS AND DISSEMINATION: This protocol has been approved by the Research Ethics Board at St. Michael's Hospital in Toronto, Ontario, Canada (#18-248). We will disseminate findings through several peer-reviewed publications, presentations at national and international meetings, and engagement of physicians, residency programmes, department heads and medical societies.

OBJECTIVES: In comparison to quantitative research, the impact of qualitative articles in the medical literature has been questioned by the BMJ; to explore this, we compared the impact of quantitative and qualitative articles published in BMJ. DESIGN: Cross-sectional survey. SETTING: Articles published in the BMJ between 2007 and 2017. MAIN OUTCOME MEASURES: Bibliometric and altmetric measures of research impact were collected using Web of Science, Google Scholar, Scopus, Plum Analytics and ProQuest Altmetric. Bibliometric measures consisted of citation numbers, field weighted citation impact and citation percentile. Altmetric measures consisted of article usage, captures, mentions, readers, altmetric attention score and score percentile. Scores were compared using the Wilcoxon Rank-sum test. RESULTS: We screened a total of 7777 articles and identified 42 qualitative articles. Each qualitative article was matched to 3 quantitative articles published during the same year (126 quantitative articles). Citation numbers were not statistically different between the two research types; the median number of citations (google scholar) per quantitative article was 62 (IQR 38-111) versus 58 (IQR 36-85) per qualitative article (p=0.47). Using Plum Analytics, qualitative articles were found to have a significantly higher usage, with a median of 984 (IQR 581-1351) versus 379 (IQR 177-763) for quantitative (p<0.001). The Altmetric Attention Score was higher for quantitative articles at 16 (IQR 7-37) versus qualitative articles at 9 (IQR 5-23, p=0.05), as was the Altmetric Score percentile 93 (IQR 87-96) versus 88 (IQR 76-95; p=0.02). CONCLUSION: Qualitative and quantitative articles published in the BMJ between 2007 and 2017 both have a high impact. No article type was consistently superior in terms of bibliometric or altmetric measures, suggesting that type of article is not the major driver of impact.