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Objective: To scope how the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) has been applied to measure socio-economic status (SES) in peer-reviewed cardiovascular disease (CVD) research. Methods: The Joanna Briggs Institute's scoping review methodology was used. Results: The search retrieved 2788 unique citations, and 49 studies were included. Studies were heterogeneous in their approach to analysis using SEIFA. Not all studies provided information as to what version was used and how SEIFA was applied in analysis. Spatial unit of analysis varied between studies, with participant postcode most frequently applied. Study quality varied. Conclusions: The use of SEIFA in Australian CVD peer-reviewed research is widespread, with variations in the application of SEIFA to measure SES as an exposure. There is a need to improve the reporting of how SEIFA is applied in the methods sections of research papers for greater transparency and to ensure accurate interpretation of CVD research. What is known about the topic? A socio-economic status (SES) gradient is well established for cardiovascular disease (CVD). Research has generally applied two approaches to classifying SES: at an individual level using income, education or occupation data, and at an area level using a range of existing socio-economic information, including the Australian Bureau of Statistics (ABS) Socio-Economic Indexes for Areas (SEIFA). What does this paper add? This review examined how SEIFA has been applied to measure SES in Australian peer-reviewed CVD research and to identify any variations in research practice. What are the implications for practitioners? It is recommended that researchers provide a clear explanation in the methods section of research papers as to which SEIFA version and index was applied, how it was applied, at what spatial unit, and whether the spatial unit was an ABS or non-ABS unit. [ABSTRACT FROM AUTHOR]

Context: There is growing evidence supporting a shift towards 'grow your own' approaches to recruiting, training and retaining health professionals from and for rural communities. To achieve this, there is a need for sound methodologies by which universities can describe their area of geographic focus in a precise way that can be utilised to recruit students from their region and evaluate workforce outcomes for partner communities. In Australia, Deakin University operates a Rural Health Multidisciplinary Training (RHMT) program funded Rural Clinical School and University Department of Rural Health, with the purpose of producing a graduate health workforce through the provision of rural clinical placements in western and south-western Victoria. The desire to establish a dedicated Rural Training Stream within Deakin's Doctor of Medicine course acted as a catalyst for us to describe our 'rural footprint' in a way that could be used to prioritise local student recruitment as well as evaluate graduate workforce outcomes specifically for this region. Issue: In Australia, selection of rural students has relied on the Australian Statistical Geography Standard Remoteness Areas (ASGS-RA) or Modified Monash Model (MMM) to assign rural background status to medical course applicants, based on a standard definition provided by the RHMT program. Applicants meeting rural background criteria may be preferentially admitted to any medical school according to admission quotas or dedicated rural streams across the country. Until recently, evaluations of graduate workforce outcomes have also used these rurality classifications, but often without reference to particular geographic areas. Growing international evidence supports the importance of place-based connection and training, with medical graduates more likely to work in a region that they are from or in which they have trained. For universities to align rural student recruitment more strategically with training in specific geographic areas, there is a need to develop precise geographical definitions of areas of rural focus that can be applied during admissions processes. Lessons learned: As we strived to describe our rural activity area precisely, we modelled the application of several geographical and other frameworks, including the MMM, ASGS-RA, Primary Healthcare Networks (PHN), Local Government Areas (LGAs), postcodes and Statistical Areas. It became evident that there was no single geographical or rural framework that (1) accurately described our area of activity, (2) accurately described our desired workforce focus, (3) was practical to apply during the admissions process. We ultimately settled on a bespoke approach using a combination of the PHN and MMM to achieve the specificity required. This report provides an example of how a rural activity footprint can be accurately described and successfully employed to prioritise students from a geographical area for course admission. Lessons learned about the strengths and limitations of available geographical measures are shared. Applications of a precise footprint definition are described including student recruitment, evaluation of workforce outcomes for a geographic region, benefits to stakeholder relationships and an opportunity for more nuanced RHMT reporting. [ABSTRACT FROM AUTHOR]

Bold and comprehensive action is needed to prevent diet-related diseases in rural areas, which includes improving food environments to enable healthier dietary practices. Rural health services are integral to the health of rural populations, yet their role in community disease prevention is not swell understood. This study sought to understand health service, local government, and food outlet stakeholders' perspectives on (1) the drivers of unhealthy retail environments in a rural setting; (2) the role of rural health services in supporting changes in local food environments; and to (3) identify characteristics of potential interventions. Two Group Model Building workshops were held with health service and local government leaders (n = 9), and interviews were conducted with local food outlet participants (n = 13). Key themes included 'enablers to healthier food environments', 'barriers to healthier food environments', 'Rural health services are a leading broker of knowledge for healthy food environments', and 'characteristics of desirable healthy food environment interventions.'. Rural health services can play a key role in addressing the current barriers to healthy food environments in rural areas. Effective promotion of healthier diets in rural populations will require consideration of key stakeholder perspectives and the development of further evidence on the role that rural health services can play in improving the healthiness of food environments. [ABSTRACT FROM AUTHOR]

Introduction: Globally, primary care organisations responded rapidly to COVID-19 physical distancing requirements through the adoption of telehealth to maintain the delivery of health care to communities. In Australia, temporary Medicare Benefits Schedule (MBS) telehealth items were introduced in March 2020 to enable the provision of telehealth services in the primary care setting. These changes included funding for two modes of telehealth delivery: videoconferencing and telephone consultations. As primary care organisations, Aboriginal Community Controlled Health Organisations (ACCHOs) rapidly adopted telehealth consultations to maintain the delivery of primary care services to Aboriginal and Torres Strait Islander clients. The aim of the present study was to evaluate the implementation (specifically the uptake, acceptability and requirements for delivery) of telehealth primary healthcare services for Aboriginal and/or Torres Strait Islander peoples by a rural ACCHO during COVID-19. Methods: A single-site convergent--parallel mixed--methods study was undertaken in the context of an ongoing research partnership established between a rural ACCHO and a university department of rural health. De-identified health service data from March 2020 to March 2021 was extracted, including MBS telehealth consultations and client demographics (eg age, gender and postcode). Variables were analysed using descriptive statistics to examine the uptake of telehealth by Aboriginal and Torres Strait Islander clients. A geographical analysis of postcode data was also undertaken. Semi-structured interviews were undertaken concurrently with a purposive sample of health service personnel (including health professionals) involved in the implementation or delivery of telehealth, and Aboriginal and/or Torres Strait Islander clients who had accessed telehealth, to explore the acceptability of telehealth and requirements for delivery. Thematic analysis using an inductive approach was undertaken. The analyses of quantitative and qualitative findings were merged to identify key concepts pertaining to the uptake, acceptability and requirements for telehealth delivery. Results: During the first year of implementation, 435 telehealth primary healthcare consultations were delivered to Aboriginal and/or Torres Strait Islander clients. Seven health personnel and six Aboriginal and/or Torres Strait Islander clients participated in interviews. Merged findings from an analysis of quantitative and qualitative data were grouped under three concepts: uptake of telehealth consultations by Aboriginal and Torres Strait Islander clients, maintaining the delivery of ACCHO services during COVID-19, and implications for sustaining telehealth in an ACCHO. Findings identified that telehealth maintained the delivery of ACCHO services to Aboriginal and/or Torres Strait Islander clients across the lifespan during COVID-19, despite a preference for face-toface consultations. A greater uptake of telephone consultations compared to videoconferencing was identified. Barriers to the utilisation of videoconferencing were largely technology related, highlighting the need for additional support for clients. Conclusion: Telehealth was a useful addition to face-to-face consultations when used in the appropriate context such as the administration of long-term medication prescriptions by a GP. Engaging the ACCHO sector in the policy discourse around telehealth is imperative for identifying requirements for ongoing implementation. [ABSTRACT FROM AUTHOR]

Introduction: Inequitable distribution of health workforce limits access to healthcare services and contributes to adverse health outcomes. WHO recommends tracking health professionals from their points of entry into university and over their careers for the purpose of workforce development and planning. Previous research has focused on medical students and graduates’ choice of practice location. Few studies have targeted nursing and allied health graduates’ practice intentions and destinations. The Nursing and Allied Health Graduate Outcomes Tracking (NAHGOT) study is investigating factors affecting Australian nursing and allied health students and graduates’ choice of graduate practice location over the course of their studies and up to 10 years after graduation by linking multiple data sources, including routinely collected university administrative and professional placement data, surveys of students and graduates, and professional registration data. Methods: By using a prospective cohort study design, each year a new cohort of about 2000 students at each participating university (Deakin University, Monash University and the University of Newcastle) is tracked throughout their courses and for 10 years after graduation. Disciplines include medical radiation practice, nursing and midwifery, occupational therapy, optometry, paramedicine, pharmacy, physiotherapy, podiatry and psychology. University enrolment data are collected at admission and professional placement data are collected annually. Students’ practice destination intentions are collected via questions added into the national Student Experience Survey (SES). Data pertaining to graduates’ practice destination, intentions and factors influencing choice of practice location are collected in the first and third years after graduation via questions added to the Australian Graduate Outcomes Survey (GOS). Additionally, participants may volunteer to receive a NAHGOT survey in the second and fourthto-tenth years after graduation. Principal place of practice data are accessed via the Australian Health Practitioner Regulation Agency (Ahpra) annually. Linked data are aggregated and analysed to test hypotheses comparing associations between multiple variables and graduate practice location. Results: This study seeks to add to the limited empirical evidence about factors that lead to rural practice in the nursing and allied health professions. This prospective large-scale, comprehensive study tracks participants from eight different health professions across three universities through their pre-registration education and into their postgraduate careers, an approach not previously reported in Australia. To achieve this, the NAHGOT study links data drawn from university enrolment and professional placement data, the SES, the GOS, online NAHGOT graduate surveys, and Ahpra data. The prospective cohort study design enables the use of both comparative analysis and hypothesis testing. The flexible and inclusive study design is intended to enable other universities, as well as those allied health professions not regulated by Ahpra, to join the study over time. Conclusion: The study demonstrates how the systematic, institutional tracking and research approach advocated by the WHO can be applied to the nursing and allied health workforce in Australia. It is expected that this large-scale, longitudinal, multifactorial, multicentre study will help inform future nursing and allied health university admission, graduate pathways and health workforce planning. Furthermore, the project could be expanded to explore health workforce attrition and thereby influence health workforce planning overall. [ABSTRACT FROM AUTHOR]

Objective: To identity differences between a general access index (Accessibility/ Remoteness Index of Australia; ARIA+) and a specific acute and aftercare cardiac services access index (Cardiac ARIA). Research design and methods: Exploratory descriptive design. ARIA+ (2011) and Cardiac ARIA (2010) were compared using cross-tabulations (chi-square test for independence) and map visualisations. All Australian locations with ARIA+ and Cardiac ARIA values were included in the analysis (n = 20,223). The unit of analysis was Australian locations. Results: Of the 20,223 locations, 2757 (14% of total) had the highest level of acute cardiac access coupled with the highest level of general access. There were 1029 locations with the poorest access (5% of total). Approximately two thirds of locations in Australia were classed as having the highest level of cardiac aftercare. Locations in Major Cities, Inner Regional Australia, and Outer Regional Australia accounted for approximately 98% of this category. There were significant associations between ARIA+ and Cardiac ARIA acute (χ2 = 25250.73, df = 28, p<0.001, Cramer’s V = 0.559, p<0.001) and Cardiac ARIA aftercare (χ2 = 17204.38, df = 16, Cramer’s V = 0.461, p<0.001). Conclusions: Although there were significant associations between the indices, ARIA+ and Cardiac ARIA are not interchangeable. Systematic differences were apparent which can be attributed largely to the underlying specificity of the Cardiac ARIA (a time critical index that uses distance to the service of interest) compared to general accessibility quantified by the ARIA+ model (an index that uses distance to population centre). It is where the differences are located geographically that have a tangible impact upon the communities in these locations–i.e. peri-urban areas of the major capital cities, and around the more remote regional centres. There is a strong case for specific access models to be developed and updated to assist with efficient deployment of resources and targeted service provision. The reasoning behind the differences highlighted will be generalisable to any comparison between general and service-specific access models. [ABSTRACT FROM AUTHOR]

Objective: Gestational Diabetes Mellitus (GDM) increases the risk of type 2 diabetes. A register can be used to follow-up high risk women for early intervention to prevent progression to type 2 diabetes. We evaluate the performance of the world’s first national gestational diabetes register. Research design and methods: Observational study that used data linkage to merge: (1) pathology data from the Australian states of Victoria (VIC) and South Australia (SA); (2) birth records from the Consultative Council on Obstetric and Paediatric Mortality and Morbidity (CCOPMM, VIC) and the South Australian Perinatal Statistics Collection (SAPSC, SA); (3) GDM and type 2 diabetes register data from the National Gestational Diabetes Register (NGDR). All pregnancies registered on CCOPMM and SAPSC for 2012 and 2013 were included–other data back to 2008 were used to support the analyses. Rates of screening for GDM, rates of registration on the NGDR, and rates of follow-up laboratory screening for type 2 diabetes are reported. Results: Estimated GDM screening rates were 86% in SA and 97% in VIC. Rates of registration on the NGDR ranged from 73% in SA (2013) to 91% in VIC (2013). During the study period rates of screening at six weeks postpartum ranged from 43% in SA (2012) to 58% in VIC (2013). There was little evidence of recall letters resulting in screening 12 months follow-up. Conclusions: GDM Screening and NGDR registration was effective in Australia. Recall by mail-out to young mothers and their GP’s for type 2 diabetes follow-up testing proved ineffective. [ABSTRACT FROM AUTHOR]

An increase in plantation forestry has been linked to a reduction in streamflows in some catchments. Quantifying the relative contribution of this land-use change on streamflows can be complex when those changes occur during weather extremes such as drought. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to two sub-catchments in south-eastern Australia which have seen the introduction and establishment of plantation land use in the past 15 years, coinciding with severe drought (1997-2009). The models were both manually and auto-calibrated and produced very good fits to observed streamflow data during both calibration (1980-1991) and validation (1992-2009) periods. Sensitivity analyses indicated that the models were most sensitive to soil and groundwater parameterisation. Analysis of drought conditions on streamflows showed significant declines from long-term average streamflows, while assessment of baseflow contributions by the models indicated a mix of over- and underestimation depending on catchment and season. The modelled introduction of plantation forestry did not significantly change streamflows for a scenario which did not include the land-use change, suggesting that the modelled land-use change in the catchments was not sufficiently extensive to have an impact on streamflows despite simulating actual rates of change. The SWAT models developed by this study will be invaluable as a basis for future use in regional climate-change studies and for the assessment of land management and land-use change impact on streamflows. [ABSTRACT FROM AUTHOR]