Quantifying and Understanding Healthcare Service Access for Geographically Distributed Communities: The Application of Address-Level Intelligence.

Abstract

Aims: The population of Australia is unevenly distributed across a vast area. Australians living in rural areas face the ongoing challenge of accessing healthcare services when and where they need them. The application of address-level intelligence is presented as a viable addition to existing methods that will enhance resource allocation and service planning.

Context: Current methods for understanding where healthcare need is greatest and guide investment are constrained by the application of existing spatial administrative units. Administrative units tend to be larger in rural settings, masking locally important areas of heterogeneity-i.e., only the 'average' condition within a boundary is reported and therefore considered.

Approach: The widespread adoption of address-level intelligence describing the services available to a community based upon the time it takes to travel to services is offered as a scalable alternative to predefined spatial administrative units. Applied examples of this change are already in practice. These include a system-level adoption at a large rural health service that spans approximately 300 km and services 250 000 residents, through to national analyses that have contributed to key policy areas in both health and education.

Conclusion: Improvements in computational power and reduced processing time, coupled with increasingly granular datasets, have seen the adoption of address-level intelligence gathering momentum. A shift to (1) access measures that account for the service availability in communities rather than relying only on population size and (2) a focus on time to services rather than solely relying on distance are recommended.