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      Beyond statistics: health inequities in rural and remote communities of Australia

      , ,
      The Lancet Public Health
      Elsevier BV

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          Ensuring equity of access to primary health care in rural and remote Australia - what core services should be locally available?

          Introduction Australians in rural and remote areas experience poorer health status compared with many metropolitan residents, due partly to inequitable access to primary health care (PHC) services. Building on recent research that identified PHC services which all Australians should be able to access regardless of where they live, this paper aims to define the population thresholds governing which PHC services would be best provided by a resident health worker, and to outline attendant implementation issues. Methods A Delphi method comprising panellists with expertise in rural, remote and/or Indigenous PHC was used. Five population thresholds reflecting Australia’s diverse rural and remote geography were devised. Panellists participated in two electronic surveys. Using a Likert scale, they were asked at what population threshold each PHC service should be provided by a resident health worker. A follow-up focus group identified important underlying principles which guided the consensus process. Results Response rates were high. The population thresholds for core PHC services provided by a resident worker were less in remote communities compared with rural communities. For example, the population threshold for ‘care of the sick and injured,’ was ≤100 for remote compared with 101–500 for rural communities. For ‘mental health’, ‘maternal/child health’, ‘sexual health’ and ‘public health’ services in remote communities the population threshold was 101–500, compared to 501–1000 for rural communities. Principles underpinning implementation included the fundamental importance of equity; consideration of social determinants of health; flexibility, effective expenditure of resources, tailoring services to ensure consumer acceptability, prioritising services according to need, and providing services as close to home as possible. Conclusion This research can assist policy makers and service planners to determine the population thresholds at which PHC services should be delivered by a resident health worker, to allocate resources and provide services more equitably, and inform consumers about PHC services they can reasonably expect to access in their community. This framework assists in developing a systematic approach to strategies seeking to address existing rural–urban health workforce maldistribution, including the training of generalists as opposed to specialists, and providing necessary infrastructure in communities most in need. Electronic supplementary material The online version of this article (doi:10.1186/s12939-015-0228-1) contains supplementary material, which is available to authorized users.
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            Improved life expectancy for Indigenous and non‐Indigenous people in the Northern Territory, 1999–2018: overall and by underlying cause of death

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              The burden and trend of diseases and their risk factors in Australia, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

              (2023)
              Background A comprehensive understanding of temporal trends in the disease burden in Australia is lacking, and these trends are required to inform health service planning and improve population health. We explored the burden and trends of diseases and their risk factors in Australia from 1990 to 2019 through a comprehensive analysis of the Global Burden of Disease Study (GBD) 2019. Methods In this systematic analysis for GBD 2019, we estimated all-cause mortality using the standardised GBD methodology. Data sources included primarily vital registration systems with additional data from sample registrations, censuses, surveys, surveillance, registries, and verbal autopsies. A composite measure of health loss caused by fatal and non-fatal disease burden (disability-adjusted life-years [DALYs]) was calculated as the sum of years of life lost (YLLs) and years of life lived with disability (YLDs). Comparisons between Australia and 14 other high-income countries were made. Findings Life expectancy at birth in Australia improved from 77·0 years (95% uncertainty interval [UI] 76·9–77·1) in 1990 to 82·9 years (82·7–83·1) in 2019. Between 1990 and 2019, the age-standardised death rate decreased from 637·7 deaths (95% UI 634·1–641·3) to 389·2 deaths (381·4–397·6) per 100 000 population. In 2019, non-communicable diseases remained the major cause of mortality in Australia, accounting for 90·9% (95% UI 90·4–91·9) of total deaths, followed by injuries (5·7%, 5·3–6·1) and communicable, maternal, neonatal, and nutritional diseases (3·3%, 2·9–3·7). Ischaemic heart disease, self-harm, tracheal, bronchus, and lung cancer, stroke, and colorectal cancer were the leading causes of YLLs. The leading causes of YLDs were low back pain, depressive disorders, other musculoskeletal diseases, falls, and anxiety disorders. The leading risk factors for DALYs were high BMI, smoking, high blood pressure, high fasting plasma glucose, and drug use. Between 1990 and 2019, all-cause DALYs decreased by 24·6% (95% UI 21·5–28·1). Relative to similar countries, Australia's ranking improved for age-standardised death rates and life expectancy at birth but not for YLDs and YLLs between 1990 and 2019. Interpretation An important challenge for Australia is to address the health needs of people with non-communicable diseases. The health systems must be prepared to address the increasing demands of non-communicable diseases and ageing. Funding Bill & Melinda Gates Foundation.
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                Author and article information

                Journal
                The Lancet Public Health
                The Lancet Public Health
                Elsevier BV
                24682667
                November 2023
                November 2023
                : 8
                : 11
                : e834
                Article
                10.1016/S2468-2667(23)00246-3
                b7d6e99e-d429-4d76-a8c7-82301ed1c2fd
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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