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Objective: To assess timeliness, efficiency, health outcomes and cost‐effectiveness of the 2018 redesigned Central Australian aeromedical retrieval model. Design: Pre‐ and postimplementation observational study of all patients receiving telehealth consultations from remote medical practitioners (RMPs) or Medical Retrieval and Consultation Centre (MRaCC) physicians between 1/1/2015 and 29/2/2020. Descriptive and inferential statistics measuring system efficiency, timeliness, health outcomes and incremental cost‐effectiveness. Findings: There were 9%–10% reductions in rates of total aeromedical retrievals, emergency department admissions and hospitalisations postimplementation, all p‐values < 0.001. Usage rates for total hospital bed days and ICU hours were 17% lower (both p < 0.001). After adjusting for periodicity (12% fewer retrievals on weekends), each postimplementation year, there were 0.7 fewer retrievals/day (p = 0.002). The mean time from initial consultation to aeromedical departure declined by 18 minutes post‐implementation (115 vs. 97 min, p = 0.007). The hazard of death within 365 days was nonsignificant (0.912, 95% CI 0.743–1.120). Postimplementation, it cost $302 more per hospital admission and $3051 more per year of life saved, with a 75% probability of cost‐effectiveness. These costs excluded estimated savings of $744,528/year in reduced hospitalisations and the substantial social and out‐of‐pocket costs to patients and their families associated with temporary relocation to Alice Springs. Conclusion: Central Australia's new critical care consultant‐led aeromedical retrieval model is more efficient, is dispatched faster and is more cost‐effective. These findings are highly relevant to other remote regions in Australia and internationally that have comparable GP‐led retrieval services. [ABSTRACT FROM AUTHOR]

Introduction: In February 2018 the Remote Medical Practitioner (RMP)‐led telehealth model for providing both primary care advice and aeromedical retrievals in Central Australia was replaced by the Medical Retrieval and Consultation Centre (MRaCC) and Remote Outreach Consultation Centre (ROCC). In this new model, specialists with advanced critical care skills provide telehealth consultations for emergencies 24/7 and afterhours primary care advice (MRaCC) while RMPs (general practitioners) provide primary care telehealth advice in business hours via the separate ROCC. Objective: To evaluate changes in clinicians' perceptions of efficiency and timeliness of the new (MRaCC) and (ROCC) model in Central Australia. Design: There were 103 and 72 respondents, respectively, to pre‐ and post‐implementation surveys of remote clinicians and specialist staff. Findings: Both emergency and primary care aspects of telehealth support were perceived as being significantly more timely and efficient under the newly introduced MRaCC/ROCC model. Importantly, health professionals in remote community were more likely to feel that their access to clinical support during emergencies was consistent and immediately available. Discussion: Respondents consistently perceived the new MRaCC/ROCC model more favourably than the previous RMP‐led model, suggesting that there are benefits to having separate referral streams for telehealth advice for primary health care and emergencies, and staffing the emergency stream with specialists with advanced critical care skills. Conclusion: Given the paucity of literature about optimal models for providing pre‐hospital medical care to remote residents, the findings have substantial local, national and international relevance and implications, particularly in similar geographically large countries, with low population density. [ABSTRACT FROM AUTHOR]

Objectives: To analyse rates of avoidable mortality in Aboriginal and non-Aboriginal residents of the Northern Territory (NT) from 1985 to 2004, in order to assess the contribution of health care to life expectancy improvements. Methods: Australian Bureau of Statistics (ABS) death registration data for NT residents were used to identify 'avoidable' deaths, with further separation into three categories of conditions amenable to either medical care or health policy, and a category for ischaemic heart disease (IHD). A Poisson regression model was used to calculate the average annual change in avoidable mortality by sex and Aboriginality in the NT compared with Australia as a whole. Results: In the 20 years between 1985 and 2004, avoidable mortality rates fell 18.9% in NT Aboriginal people, 61.1% in NT non-Aboriginal people and 59.5% in Australians overall. NT Aboriginal people continued to experience higher avoidable mortality than other Australians and the disparity increased over time. Most of the decline in avoidable mortality for Aboriginal Territorians occurred for conditions amenable to medical care. Conclusion: Medical care has made a significant contribution to improvements in Aboriginal life expectancy in the NT, however, reductions in avoidable mortality from IHD and conditions amenable to health policy have been variable. Implications: The results highlight the need for ongoing investment in comprehensive programs incorporating appropriate health policy interventions and management of chronic diseases. Key words: avoidable mortality, Aboriginal health, Northern Territory, health care. Aust NZ J Public Health. 2009; 33:544-50 doi: 10.1111/j. 1753-6405.2009.00451.x

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1745-5871.2008.00534.x Byline: YUEJEN ZHAO (1), STEVEN GUTHRIDGE (1) Keywords: remoteness; population density; geographical classifications; ARIA; ASGC; accessibility Abstract: Abstract This paper re-examines the characteristics and assumptions of current remoteness/accessibility classifications in Australia and proposes a simple and easily understandable alternative measure for remoteness. In this study, remoteness is redefined simply as the average distance between two nearest people within an appropriate spatial unit where population distribution is assumed to be homogenous. By definition, the most straightforward remoteness and incapacity index (RII) would be remoteness times a measure of the incapacity for social and commercial interaction, where remoteness is gauged by the square root of the area divided by the population, and incapacity is measured by the reciprocal of population. Australian Bureau of Statistics Statistical Local Area (SLA) level population data and digital boundaries have been utilised for assessment of this index. The utility of the RII is demonstrated with two examples of activity measures for general practitioner services and businesses. At the State/Territory level, RIIs are negatively related to both general practitioner services per person (Pearson correlation coefficient r=-0.873), and the number of businesses per person (r=-0.546). The correlation can be further enhanced by normalising the distributions of the remoteness scores with a simple logarithmic function. The strong correlations confirm that remoteness has a substantial inverse impact on daily activities. Greater distance means longer time and higher costs for travelling, diseconomy of scale, and higher personnel costs. The RII provides an alternative measure of remoteness that is both intuitive and statistically straightforward and, at an SLA level, closely coincides with the commonly used but complex Accessibility/Remoteness Index of Australia Plus (ARIA+). Significantly, the RII is free of the service specific and policy sensitive adjustments justified by accessibility that have been introduced into existing measures. Author Affiliation: (1)Institute of Advanced Studies, Charles Darwin University, Darwin, NT 0909, Australia. Article History: Received 25 June 2007; Revised 7 December 2007; Accepted 11 February 2008 Article note: (*) Corresponding author: Email: yuejen.zhao@nt.gov.au

Objective: To determine the prevalence rates of hypertension, diabetes, ischaemic heart disease (IHD), renal disease and chronic obstructive pulmonary disease (COPD), and their co-occurrence among the remote Aboriginal population of the Northern Territory (NT) in 2005. Methods: Information from a primary care chronic disease register (CDR) and hospital inpatient database were linked to a population list by using a unique patient identifier. A capture-recapture method (CRM) and multivariate log-linear models were then applied to analyse the multiple datasets to estimate the prevalence rates for the selected diseases and case ascertainment in each data source. Results: The NT remote Aboriginal communities had considerably higher prevalence rates across all five chronic diseases than national health survey figures. At ages 50 years and over, the prevalence rates for hypertension and renal disease were above 50%, diabetes 40%, COPD 30% and IHD above 20%. In terms of data completeness, CDR and hospital sources were both relatively incomplete, generally around 20-60%. The most common co-occurrences for the five chronic diseases were between hypertension, diabetes, IHD and renal disease. Conclusions and implications: The prevalence rates calculated using this method are comparable to estimates from rigorous small area studies, but are markedly higher than those from single clinical data sources. The results indicate that there is a considerable underdiagnosis of preventable chronic diseases in the Aboriginal communities. Keywords: Prevalence, data collection, epidemiology, chronic diseases, Indigenous health services doi: 10.1111/j.1753-6405.2008.00245.x

Objective: To compare cancer incidence and survival for the Northern Territory (NT) Indigenous population with that of other Australians, and to assess NT Indigenous incidence time trends. Methods: Cancer registry data were used to calculate cancer incidence rate ratios (NT Indigenous to total Australian), the average annual change in NT Indigenous cancer incidence and the relative risk of cancer death after diagnosis of cancer (NT Indigenous to combined Western Australian and Tasmanian cases) for 1991-2001. Results: For NT Indigenous people, incidence rates were high for cancers of the liver, gallbladder, cervix, vulva and thyroid and, in younger people only, for cancers of the oropharynx, oesophagus, pancreas and lung, but low for cancers of the colon and rectum, breast, ovary, prostate, bladder, kidney, melanoma and lymphoma. Incidence rate ratios ranged from 0.1 for melanoma to 7.4 for liver cancer. Incidence increased for breast and pancreatic cancers. Survival was low for almost all specific cancers examined, and for all cancers combined (relative risk of death 1.9, 95% CI 1.7-2.1). Conclusions: Compared with other Australians, NT Indigenous people have higher, and increasing, incidence for some cancers (particularly smoking-related cancers) and lower survival for most. Implications: Cancer has a greater impact on NT Indigenous people than other Australians. Well-established cancer risk factors should be more effectively tackled in Indigenous people and known effective screening programs more effectively implemented. Research is urgently required into the reasons why survival from cancer in NT Indigenous people is so much lower than in other Australians.

Abstract Background The estimated gap in life expectancy (LE) between Indigenous and non-Indigenous Australians was 12 years for men and 10 years for women, whereas the Northern Territory Indigenous LE gap was at least 50% greater than the national figures. This study aims to explain the Indigenous LE gap by common modifiable risk factors. Methods This study covered the period from 1986 to 2005. Unit record death data from the Northern Territory were used to assess the differences in LE at birth between the Indigenous and non-Indigenous populations by socioeconomic disadvantage, smoking, alcohol abuse, obesity, pollution, and intimate partner violence. The population attributable fractions were applied to estimate the numbers of deaths associated with the selected risks. The standard life table and cause decomposition technique was used to examine the individual and joint effects on health inequality. Results The findings from this study indicate that among the selected risk factors, socioeconomic disadvantage was the leading health risk and accounted for one-third to one-half of the Indigenous LE gap. A combination of all six selected risks explained over 60% of the Indigenous LE gap. Conclusions Improving socioeconomic status, smoking cessation, and overweight reduction are critical to closing the Indigenous LE gap. This paper presents a useful way to explain the impact of risk factors of health inequalities, and suggests that reducing poverty should be placed squarely at the centre of the strategies to close the Indigenous LE gap.

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1745-5871.2009.00602.x Byline: YUEJEN ZHAO, STEVE GUTHRIDGE Author Affiliation: Institute of Advanced Studies, Charles Darwin University, Darwin, NT 0909, Australia. Email:yuejen.zhao@nt.gov.au

Abstract Background The estimated life expectancy at birth for Indigenous Australians is 10-11 years less than the general Australian population. The mean family income for Indigenous people is also significantly lower than for non-Indigenous people. In this paper we examine poverty or socioeconomic disadvantage as an explanation for the Indigenous health gap in hospital morbidity in Australia. Methods We utilised a cross-sectional and ecological design using the Northern Territory public hospitalisation data from 1 July 2004 to 30 June 2008 and socio-economic indexes for areas (SEIFA) from the 2006 census. Multilevel logistic regression models were used to estimate odds ratios and confidence intervals. Both total and potentially avoidable hospitalisations were investigated. Results This study indicated that lifting SEIFA scores for family income and education/occupation by two quintile categories for low socio-economic Indigenous groups was sufficient to overcome the excess hospital utilisation among the Indigenous population compared with the non-Indigenous population. The results support a reframing of the Indigenous health gap as being a consequence of poverty and not simplistically of ethnicity. Conclusions Socio-economic disadvantage is a likely explanation for a substantial proportion of the hospital morbidity gap between Indigenous and non-Indigenous populations. Efforts to improve Indigenous health outcomes should recognise poverty as an underlying determinant of the health gap.