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Objectives: To examine individual, medication, system, and healthcare related predictors of hospitalization and emergency department (ED) presentation within 90 days of entering the aged care sector, and to create risk-profiles associated with these outcomes. Design and setting: Retrospective population-based cohort study using data from the Registry of Senior Australians. Participants: Older people (aged 65 and older) with an aged care eligibility assessment in South Australia between January 1, 2013 and May 31, 2016 (N = 22,130). Measurements: Primary outcomes were unplanned hospitalization and ED presentation within 90 days of assessment. Individual, medication, system, and healthcare related predictors of the outcomes at the time of assessment, within 90 days or 1-year prior. Fine–Gray models were used to calculate subdistribution hazard ratios (sHR) and 95% confidence intervals (CI). Harrell's C-index assessed predictive ability. Results: Four thousand nine-hundred and six (22.2%) individuals were hospitalized and 5028 (22.7%) had an ED presentation within 90 days. Predictors of hospitalization included: being a man (hospitalization sHR = 1.33, 95% CI 1.26–1.42), ≥3 urgent after-hours attendances (hospitalization sHR = 1.21, 95% CI 1.06–1.39), increasing frailty index score (hospitalization sHR = 1.19, 95% CI 1.11–1.28), individuals using glucocorticoids (hospitalization sHR = 1.11, 95% CI 1.02–1.20), sulfonamides (hospitalization sHR = 1.18, 95% CI 1.10–1.27), trimethoprim antibiotics (hospitalization sHR = 1.15, 95% CI 1.03–1.29), unplanned hospitalizations 30 days prior (hospitalization sHR = 1.13, 95% CI 1.04–1.23), and ED presentations 1 year prior (hospitalization sHR = 1.07, 95% CI 1.04–1.10). Similar predictors and hazard estimates were also observed for ED presentations. The hospitalization models out-of-sample predictive ability (C-index = 0.653, 95% CI 0.635–0.670) and ED presentations (C-index = 0.647, 95% CI 0.630–0.663) were moderate. Conclusio

Introduction Adults with lower levels of health literacy are less likely to engage in health-promoting behaviours. Our trial evaluates the impacts and outcomes of a mobile health-enhanced preventive intervention in primary care for people who are overweight or obese. Methods and analysis A two-arm pragmatic practicelevel cluster randomised trial will be conducted in 40 practices in low socioeconomic areas in Sydney and Adelaide, Australia. Forty patients aged 40-70 years with a body mass index ≥28 kg/m2 will be enrolled per practice. The HeLP-general practitioner (GP) intervention includes a practice-level quality improvement intervention (medical record audit and feedback, staff training and practice facilitation visits) to support practices to implement the clinical intervention for patients. The clinical intervention involves a health check visit with a practice nurse based on the 5As framework (assess, advise, agree, assist and arrange), the use of a purpose-built patientfacing app, my snapp, and referral for telephone coaching. The primary outcomes are change in health literacy, lifestyle behaviours, weight, waist circumference and blood pressure. The study will also evaluate changes in quality of life and health service use to determine the cost-effectiveness of the intervention and examine the experiences of practices in implementing the programme. Ethics and dissemination The study has been approved by the University of New South Wales (UNSW) Human Research Ethics Committee (HC17474) and ratified by the University of Adelaide Human Research Ethics committee. There are no restrictions on publication, and findings of the study will be made available to the public via the Centre for Primary Health Care and Equity website and through conference presentations and research publications. Deidentified data and meta-data will be stored in a repository at UNSW and made available subject to ethics committee approval

INTRODUCTION: Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses-where outcomes are considered separately, with their joint relationship under uncertainty ignored-lead to incorrect inference regarding preferred strategies. OBJECTIVE: The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. METHODS: Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. RESULTS: Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. CONCLUSION: Comparison in CDU space and associated summary measures have distinct advantages

Background:Early diagnosis and improved treatment outcomes have increased breast cancer survival rates that, in turn, have led to increased numbers of women undergoing follow-up after completion of primary treatment. The current workload growth is unsustainable for breast cancer specialists who also provide care for women newly diagnosed or with a recurrence. Appropriate and acceptable follow-up care is important; yet, currently we know little about patient preferences. The aim of this study was to explore the preferences of Australian breast cancer survivors for alternative modes of delivery of follow-up services.Methods:A self-administered questionnaire (online or paper) was developed. The questionnaire contained a discrete choice experiment (DCE) designed to explore patient preferences with respect to provider, location, frequency and method of delivery of routine follow-up care in years 3, 4 and 5 after diagnosis, as well as the perceived value of 'drop-in' clinics providing additional support. Participants were recruited throughout Australia over a 6-month period from May to October 2012. Preference scores and choice probabilities were used to rank the top 10 most preferred follow-up scenarios for respondents.Results:A total of 836 women participated in the study, of whom 722 (86.4%) completed the DCE. In the absence of specialist follow-up, the 10 most valued surveillance scenarios all included a Breast Physician as the provider of follow-up care. The most preferred scenario is a face-to-face local breast cancer follow-up clinic held every 6 months and led by a Breast Physician, where additional clinics focused on the side effects of treatment are also provided.Conclusion:Beyond the first 2 years from diagnosis, in the absence of a specialist led follow-up, women prefer to have their routine breast cancer follow-up by a Breast Physician (or a Breast Cancer Nurse) in a dedicated local breast cancer clinic, rather than with their local General Practitioner. Drop