RESEARCH IMPACT

Outline of the research

Understanding how health services are distributed relative to demographic and socio-economic characteristics of the populations that they are needed to service is a vital component not only of health service provision planning, but also urban planning more broadly. Ideally, health services would be distributed in a way that allow the entire population to access them without barriers. Addressing this equity of access has been a focus of both international and domestic concern; getting a handle on the scale and distribution of current and future need is the first step in addressing these inequities in access.

Dr. Alison Taylor and Professor Chris Pettit of the City Futures Research Centre at the University of New South Wales investigated the equity of the distribution of health services across New South Wales’ SA2s (Statistical Area Level 2) and LGAs (Local Government Areas). To do this, Dr. Taylor and Prof. Pettit used Gini coefficients to measure inequity in the distribution of health services relative to population distribution. Gini coefficients are most often used to measure income inequality (you can access SA2 estimates of income inequality – Gini coefficients – produced by both the Australian Bureau of Statistics and the National Centre for Social and Economic Modelling in the AURIN Workbench). However, their utility in measuring inequality in health outcomes, educational achievement and quality of life has become more prevalent both in Australia and Internationally.  Gini coefficients range from 0 (no inequality) to 1 (total inequality)

To estimate future potential demand, and likely spatial distribution of future inequity of health services in Greater Sydney, the authors estimated future population to service provider ratios for three scenarios of health provision (ratio improves by 10%, ratio worsens by 10%, ratio worsens by 25%), in addition to the baseline scenario, and applying those scenarios to population projections for the Greater Sydney region.

How AURIN was used

Dr. Taylor and Prof. Pettit used the National Health Service Directory (NHSD) dataset accessed via the AURIN Portal as central dataset for their analysis. The NHSD provides the point level location of every health provider in Australia, ranging from primary care providers such as GPs and Child and Maternity Services, to tertiary care such as major hospitals and emergency departments. The dataset contains a large number of variables which allow researchers to partition the health provider along multiple dimensions, enabling deep research questions. Any AURIN Portal user can request access to the NHSD via the AURIN website.

In addition to utilizing the NHSD dataset available through the AURIN workbench, Dr. Taylor and Prof. Pettit undertook their Gini coefficient calculations within the AURIN Portal. The Gini coefficient tool Index tools is one of several specialised index tools available in the AURIN portal, allowing users to develop a range of comparative indicators for their study areas and particular strands of research

Findings and Impacts of the Research

The results of these analyses showed substantial inequities in the distribution of health services relative to population. When ranked by population size, the most populous 20% of New South Wales SA2s contained approximately 37% of the state’s population, a Gini coefficient of approximately 0.323. However, when ranked by health services number, the 55% of health services were contained within the top 20% of New South Wales’ SA2s, while the bottom 20% of SA2s contained only fewer than 2% of health service (Gini coefficient of 0.534). When examining different health services by sector, the authors noted even starker inequities: for aged care, the Gini coefficient was 0.573. ­

Dr. Taylor and Prof. Pettit also partitioned inequality across dimensions of remoteness. They found that there were no substantial differences in the health inequality measures for Major Metropolitan and Inner Regional SA2s, although Inner Regional SA2s reported slightly higher Gini coefficients than Major Metropolitan SA2s. By contrast, Outer Regional SA2s reported considerably lower Gini coefficients; 40% of health services were located in the top 20% of SA2s (compared to 60% and 54% for Inner Regional and Major Metropolitan respectively)

The authors also showed that under the current population to service provider ratio, health service provision in Greater Sydney LGAs would have to grow by 5447 additional providers by 2036 to keep up with population growth. Most of this would be required in the Central and West Central districts, reflecting likely population growth in the east-west urban corridor connecting the central city to Parramatta and Blacktown. Under a scenario of improving health provision ratios, an additional 7850 health services would be required in Greater Sydney, while scenarios of declining service provision ratios would require an additional 3490, or 1150 new health services, for a 10% and 25% decline in ratios, respectively

Dr. Taylor and Prof. Pettit highlighted the central utility of AURIN to evidence-based decision-making about current and future health provision. Better access to data and suitable use of analytical tools, such as those available through the AURIN Workbench for the academic and government sectors will allow us to address equity of access issues which are fundamental a fair society.