Who Gets Seen in Rural Australia? New Study Maps the Real Barriers to Care

When people in rural Australia struggle to see a doctor, the obvious suspects are distance, cost and long waiting lists. But a new study from rural Victoria suggests the reality is far more nuanced, and in some ways more surprising. Researchers led by Kristen Glenister of the University of Melbourne’s Department of Rural Health surveyed more than 2,600 households across a rural Australian region and found that many of the barriers residents complained about, including travel distance, out-of-pocket cost and waiting time, did not actually stop them from using general practice or medical specialist services. Instead, the strongest predictors of whether someone saw a doctor were who they were: their sex, their education, where they were born and the size of the town they lived in. Only dental care told a different story, one in which cost and perceived need genuinely kept people out of the chair.

The study, published in BMC Health Services Research, applied a classic framework from health services science known as Andersen’s behavioral model. Developed in the late 1960s by health economist Ronald Andersen, the model organises the determinants of health service use into three broad categories. Predisposing factors are the characteristics people bring with them, such as age, sex, education and cultural background. Enabling factors are the resources that make care possible, including income, insurance, transport and the availability of services nearby. Need factors capture illness itself, from chronic conditions to self-rated health. By sorting variables into these buckets, researchers can ask which forces matter most, and whether policy aimed at enabling access is actually reaching the people who need it.

What makes the Victorian study methodologically distinctive is its multilevel design. Rather than treating every respondent as an independent data point, the researchers used multilevel regression, a statistical approach that acknowledges people are nested within households and communities. This matters because health service use is often shaped by local context: the presence of a clinic, the character of a small town, the distance to the regional centre. Multilevel models partition the variation in utilisation into individual-level and area-level components, producing odds ratios that describe how each factor shifts the likelihood of care while accounting for the clustering of people within places. The team also drew on an extension of Andersen’s framework associated with health services researcher Thomas Yeatts, which incorporates barriers to access directly into the analysis, allowing the authors to test whether reported barriers translated into measurably lower utilisation.

The data came from a cross-sectional survey in which households were randomly selected from local government lists, a sampling strategy that reduces the self-selection bias that plagues convenience surveys. Trained research assistants asked respondents about their health, their use of general practitioners, medical specialists and dental services, the barriers they faced in accessing care, and their demographic details. In total, 2,680 household respondents provided usable data, giving the study a solid foundation for the regression models that followed. Ethics approval was granted by the Goulburn Valley Human Ethics Research Committee in 2016, and the work was funded by Australia’s National Health and Medical Research Council.

The results on general practice utilisation were striking for their simplicity. The single clearest signal was sex: men were markedly less likely than women to visit a general practitioner, with an odds ratio of 0.57, meaning their odds of use were roughly 43 percent lower after adjustment for other factors. This echoes a well-documented international pattern in which women consult primary care more frequently, partly reflecting reproductive and preventive care needs, and partly reflecting entrenched differences in health-seeking behavior between men and women. Notably, the barriers people reported, cost, distance and waiting time, were not statistically associated with reduced general practice use in this population.

Medical specialist care told a more layered story. People without Year 12 educational attainment were less likely to see a specialist than those who had finished secondary school, with an odds ratio of 0.81. People born overseas were substantially less likely to use specialist services than those born in Australia, at an odds ratio of 0.67. And residents of small towns were less likely than those in the regional centre to see a specialist, with an odds ratio of 0.82. Taken together, these findings suggest that specialist care in rural Victoria is not distributed purely according to medical need. Education likely operates as a proxy for health literacy, the ability to navigate referral pathways, understand specialist recommendations and persist through bureaucratic systems. Country of birth may reflect language barriers, unfamiliarity with the Australian health system or differences in how symptoms are interpreted and acted upon. Town size points to the geography of specialist supply, which concentrates in regional centres and thins out across smaller communities.

Dental care was the outlier, and arguably the most policy-relevant finding of the study. Men were less likely than women to visit a dentist, with an odds ratio of 0.71, and people who were not employed were about half as likely to use dental services as those in work, with an odds ratio of 0.51. Crucially, the barriers reported for dental care, chiefly cost and a perceived lack of need, were genuinely associated with reduced utilisation. In Australia, dentistry sits largely outside the universal Medicare scheme, so most dental care is paid out of pocket or through private insurance. The study’s results align with what that financing structure would predict: when the price signal is direct and substantial, cost becomes a real deterrent rather than a complaint. The finding that perceived need also suppressed dental use adds a behavioral dimension, suggesting some residents simply did not regard dental problems as warranting professional attention, a view that can allow silent disease such as periodontal disease and caries to progress untreated.

The authors’ central conclusion is subtle but important: the barriers residents reported for medical services appear to delay, inconvenience or complicate the patient journey rather than prevent it altogether. That distinction has real consequences for how rural health policy is designed and evaluated. If distance and waiting time merely make care harder rather than impossible, then simply counting consultation rates can mask a degraded experience of care, one involving longer trips, postponed appointments and fragmented follow-up. Utilisation statistics alone may therefore understate the access problem in rural areas, while barrier surveys alone may overstate it. The Victorian study, by measuring both in the same population and testing their association, offers a template for distinguishing between friction and exclusion in health systems research.

For rural communities, the equity implications are concentrated in three groups. Men in rural areas emerge as an under-served population in primary care, with potential downstream consequences for late diagnosis of chronic conditions. Overseas-born residents face reduced access to specialist care, raising questions about interpreter services, culturally responsive care and system navigation support. And people outside the workforce face a dental access gap driven by affordability, which compounds the broader association between socioeconomic disadvantage and oral health. Meanwhile, the reduced specialist use in small towns underscores a persistent spatial inequity: the further a community sits from the regional centre, the thinner its access to the most specialised layers of medicine.

The study is not without limits inherent to its design. As a cross-sectional survey, it captures a single moment in time and cannot establish causation; it is possible, for example, that unmeasured health need drives some of the observed associations. Self-reported utilisation and barriers are also subject to recall and interpretation effects. Yet the scale of the sample, the random household selection and the rigorous multilevel modeling give the findings considerable weight. Published open access in BMC Health Services Research, the study arrives at a moment when rural health workforce shortages and access inequities are high on the policy agenda in Australia and beyond. Its message to policymakers is double-edged: fixing cost and distance alone will not equalise medical care, because who people are, their sex, schooling, birthplace and postcode, quietly shapes who gets seen. But for dental care, the fix may be more straightforward than anyone hoped: make it affordable, and people will come.

Subject of Research: Determinants of health service utilisation in rural Victoria analysed using Andersen's behavioral model

Article Title: Factors associated with health service utilisation in rural Victoria: a multilevel analysis informed by Andersen’s behavioral model

Article References: Glenister, K. M., Hamilton, A. J., Bourke, L., McNeil, R., & Simmons, D. (2026). Factors associated with health service utilisation in rural Victoria: a multilevel analysis informed by Andersen’s behavioral model. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15773-8

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15773-8

Keywords: rural health, health service utilisation, Andersen behavioral model, multilevel analysis, healthcare access, access barriers, general practice, medical specialists, dental care, Victoria, health equity, cross-sectional survey