Healthcare services for people with acquired disability in South-East Queensland, Australia: Assessing potential proximity and its association with service obstacles

David N Borg; Joshua J Bon; Michele M Foster; Ali Lakhani; Melissa Kendall; Timothy Geraghty

doi:10.1016/j.ssmph.2022.101209

Healthcare services for people with acquired disability in South-East Queensland, Australia: Assessing potential proximity and its association with service obstacles

SSM Popul Health. 2022 Aug 17:19:101209. doi: 10.1016/j.ssmph.2022.101209. eCollection 2022 Sep.

Authors

David N Borg^{1

2}, Joshua J Bon^{1

3

4}, Michele M Foster^{1

2}, Ali Lakhani^{1

2

5}, Melissa Kendall^{1

6}, Timothy Geraghty^{1

6}

Affiliations

¹ The Hopkins Centre: Research for Rehabilitation and Resilience, Menzies Health Institute Queensland, Griffith University, Nathan, Brisbane, Australia.
² School of Health Sciences and Social Work, Griffith University, Brisbane, Australia.
³ Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, Brisbane, Australia.
⁴ School of Mathematical Sciences, Queensland University of Technology, St Lucia, Brisbane, Australia.
⁵ La Trobe University, Melbourne, Australia.
⁶ Division of Rehabilitation, Princess Alexandra Hospital, Metro South Health Hospital and Health Service, Brisbane, Australia.

Abstract

This study described access potential in South-East Queensland, to healthcare services commonly used by people with acquired disability; and investigated the association between service proximity and perceived service obstacles. First, we described accessibility by conducting a spatial analysis to create maps of potential accessibility to health services in South-East Queensland. Queensland statistical area level 2 (SA2) locations were combined with the residential locations of participants from a longitudinal cohort study involving people with ABI and SCI. The locations of selected health services of interest were identified from Health Direct's National Health Service Directory. Travel times via motor vehicle were modelled with Robust Gaussian Stochastic Process, to smoothly interpolate between the sparse time-to-service observations. Probabilistic predicted values were generated from the model and were used to construct service accessibility maps of South-East Queensland. Disability population data were used to identify SA2s with relatively low service access but a high disability population. Second, we examined perceived service obstacles, by investigating the relationship between potential access to services and perceived service obstacles was examined using data from 63 people with ABI or SCI discharged from the specialist state-wide rehabilitation services, located in South-East Queensland. Obstacles to accessing service in relation to resource availability, transportation and finances were collected three-months after discharge, using the Service Obstacle Scale. Travel times to the closest health service were computed for each individual and were compared to their Service Obstacle Scale responses. Access potential was highly variable, particularly for allied health services. We identified several low-access, high-disability population areas. These hotpots of poor access were generally to the north and west of greater Brisbane. Longer travel times to allied health services were associated with 260% higher odds of agreeing that resource availability was an obstacle to accessing services. Policy makers should be concerned with the hotspots of poor access identified.

Keywords: Access; Brain injury; Rehabilitation; Spinal cord injury.