Disparities in the use of Medicare-subsidised telehealth mental health services by Aboriginal and Torres Strait Islander Australians in Southeast Queensland

Abstract

Objective:

This study examines disparities in rates and number of telehealth used among Indigenous Medicare mental health services users in Southeast Queensland.

Methods:

We analysed the 2021 Census and Medicare Benefits Schedule data for 298,283 individuals who used MBS-subsidised community mental health services, including 78,048 who used telehealth. Descriptive and regression analyses were conducted.

Results:

Indigenous Australians were significantly less likely to use telehealth than non-Indigenous Australians (24.66% vs 26.23%, p < 0.001), although difference was small. Video-based telehealth was associated with a significantly greater increase in service use for non-Indigenous Australians than Indigenous Australians (coefficient = −0.76, p < 0.001). Indigenous adults who were female, aged 25–69, or not in the labour force were more likely to use telehealth, while number of telehealth services used was higher among those aged 40+, those who did not speak an Aboriginal language at home, and those receiving psychotherapies or video-based services. Indigenous children aged 12–17 years and those living in the Gold Coast Hospital and Health Service region were more likely to use telehealth, while greater telehealth utilisation was associated with psychotherapies and video services.

Conclusions:

Compared with non-Indigenous Australians, Indigenous Australians were less likely to use telehealth services, particularly for video services and psychotherapies, more likely to rely on general practitioner–delivered services and phone consultations. These patterns suggest systemic and cultural barriers, including cost, service availability, and preferences. Tailored telehealth interventions are needed to address these disparities and promote equitable utilisation.

Introduction

Mental health is a critical component of the holistic well-being of Aboriginal and Torres Strait Islander (hereafter respectfully Indigenous) Australians, encompassing social, emotional, and cultural dimensions (Ypinazar et al., 2007). Protective factors, including strong connections to culture, land, spirituality, community, and ancestry, play a crucial role in fostering resilience and supporting mental health (Fatima et al., 2022, 2023). However, significant disparities remain in accessing Medicare Benefits Schedule (MBS)-subsidised mental health services. These disparities are driven by systemic barriers, including racism, mistrust of mainstream services, culturally inappropriate services, and the lasting impacts of colonisation on social determinants of health (Australian Institute of Health and Welfare, 2024; Isaacs et al., 2010; McIntyre et al., 2017; Murrup-Stewart et al., 2019; O’Brien, 2006). The Close the Gap initiative by the Australian government highlights the urgency of eliminating systemic barriers and creating equitable mental health access for Indigenous Australians (Commonwealth of Australia, 2020).

Since 2020, the Australian Government has included additional telehealth services, such as videoconferencing and phone calls, in the MBS. Telehealth is seen as a potential solution to reduce geographical and cost barriers for Indigenous Australians, enabling them to access mental health care without leaving their communities (Sabesan et al., 2012). Telehealth services are also believed to support early diagnosis, improve treatment options (Metro South Health, 2018), and contribute to closing health outcome gaps between Indigenous and non-Indigenous Australians (Clair et al., 2019; Smith et al., 2019). Evidence on its impact, however, remains mixed. Telehealth has been shown to enhance mental health service utilisation and well-being for Indigenous Australians by enabling care in familiar environments with holistic support (Caffery et al., 2017, 2018), yet uptake remains low (Spurling et al., 2023) because of cultural challenges, difficulty in building rapport (Amos et al., 2022; Gibson et al., 2011), and limited suitability for conditions like schizophrenia or crises, which are more prominent in Indigenous Australians (Gibson et al., 2011; Ogilvie et al., 2021). While telehealth is widely accepted among the general population, there is concern that it may exacerbate disparities if telehealth is not adapted to Indigenous contexts (Robertson et al., 2021). Evidence has shown that the telehealth requires additional cultural adaptation (Goldin et al., 2021), requires more digital literacy and is highly dependent on well-established technological infrastructures (Gallegos-Rejas et al., 2023).

Existing research supporting telehealth to close the healthcare gap for Indigenous Australians has primarily been limited to commentaries (Clair et al., 2019; Smith et al., 2019). In addition, research on telehealth facilitators and barriers has largely been qualitative (Caffery et al., 2017). There is a critical gap in large-scale, data-driven research that examines actual telehealth use and its impact across Indigenous and non-Indigenous Australians. This study aimed to address this research gap by leveraging Medicare data and Census data to investigate disparities in telehealth use by Indigenous Australians, using Southeast Queensland (SEQ) as an example. This research is part of a broader project dedicated to improving mental health service access and equity for Indigenous Australians in SEQ (Poche Centre for Indigenous Health and Queensland Centre for Mental Health Research, 2021).

Methods

Setting, data source, and study population

We analysed Australian Bureau of Statistics (ABS) Person Level Integrated Data Asset (PLIDA) 2021 combined demographic, Medicare, and 2021 Census of Population and Housing data for individuals who resided in SEQ (Supplemental Appendix 1) for the whole of year 2021 and were not overseas visitors. SEQ is home to 11% of Australia’s and 38% of Queensland’s Indigenous population (Australian Bureau of Statistics, 2024) with the majority of its residents living in non-remote areas (Table 1). PLIDA’s combined Indigenous identifier (Australian Bureau of Statistics, 2023) was used to define the Indigenous population.

Table 1.

Sociodemographic characteristics of people who used Medicare mental health services in 2021 (n = 298,283).

Demographic characteristics	Indigenous (n = 12,439)	Non-Indigenous (n = 285,844)	p values	Chi-square/t
Female (%; count)	61.88% (7697)	62.58 (178,879)	0.114	2.50
Age (years old) (mean; SD)	30.39 (16.20)	36.36 (18.26)	<0.001	–35.84
ASGS Major cities (RA1) (%; count)	89.93% (6994)	94.04% (111,631)	<0.001	388.00
Household income percentile below 40% (count; %)	60.61% (36,056)	41.61 (827,319)	<0.001	2300.00
Married (registered or de facto marriage) (%; count) a	24.42% (3037)	38.82 (110,965)	<0.001	1300.00
Post-secondary degree (%; count) a	37.57% (4673)	51.47% (147,133)	<0.001	1200.00
Employed (%; count) a	40.03% (4979)	55.89% (159,762)	<0.001	1300.00
Has mental health history (%; count)	44.98% (5595)	37.86% (108,222)	<0.001	306.09

ASGS: Australian Statistical Geography Standard.

^aOnly include people over 15 years old.

Variables

Outcome variables included telehealth mental health service rates of use (the percentage of people who used telehealth services among those who used any MBS mental health services), and the number of telehealth services used (number of telehealth mental health items used in 2021 by those who used telehealth mental health services). Mental health services included community-based mental health-specific MBS items (Supplemental Appendix 2) delivered by general practitioners (GPs)/medical practitioners, psychiatrists, and psychologists/allied health providers. Telehealth included video and phone services.

The choice of independent variables was guided by Anderson’s behavioural model of health service use (Andersen, 1968), including: predisposing factors (sex, age, Indigenous status, Aboriginal language spoken at home, marital status, highest education level, household composition), contextual factors (remoteness, number of different residences in 2021), enabling factors (household income, labour force status), need factors (mental health diagnosis, number of other chronic health conditions), and health service factors (primary Hospital and Health Service (HHS) region of residence, including Metro North, Metro South, West Moreton, and Gold Coast HHS regions within Southeast Queensland, telehealth modalities, mental health service type, percentage of bulk billed sessions). Telehealth mental health service type was categorised into: GP mental health care plan, psychotherapy, or other mental health treatment. At person level, this was hierarchically categorised based on the combination of services received and providers seen by each individual (Supplemental Appendix 3).

Statistical analysis

Analyses were conducted with Stata 18 in ABS DataLab, a Secure Unified Research Environment for analysing linked data.

Descriptive analyses were conducted to explore the sociodemographic and service-related characteristics of people who used any MBS mental health services and telehealth-delivered MBS mental health services (chi-square analyses for categorical and t test analyses for continuous variables). Multivariate linear regression models with number of mental health items as dependent variable, and interaction term of Indigenous status (Indigenous and non-Indigenous) × healthcare modalities (face-to-face, phone and video) as independent variable were used to explore the varying impact of telehealth on mental health use for Indigenous and non-Indigenous Australians. In addition, Multivariate logistic regression analyses were used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for adults (⩾18) and children (<18) separately for: (a) rates of use of telehealth services by Indigenous status controlling for sociodemographic characteristics and (b) sociodemographic factors associated with rates of telehealth use. Multivariate linear regression analyses were used to explore sociodemographic and service-related factors associated with the number of telehealth services used (log of MBS-subsidised telehealth mental health items). To aid interpretation, exponentials of the coefficients (EC) and their 95% CIs were provided for log-transformed outcomes. SEQ residents with missing data on sociodemographic variables were removed from the regression analyses. Missing data on household income were estimated by using personal income percentile where available. For statistical significance, we considered p values <0.05 as indicative of significant differences in both descriptive and regression analyses. Throughout the manuscript, the term “significant” refers to statistical significance, while also considering the magnitude of the difference.

Sense-making process

Sense-making was integral to this study, aligning with Indigenous research principles by incorporating collaboration and contextual understanding. This process informed all stages, from identifying key variables to interpreting findings. An advisory group, including Indigenous Elders, clinicians, service providers, planners, researchers, and a community advisor, played a crucial role. Their insights guided study design, data interpretation, and result framing, ensuring cultural relevance and alignment with community priorities. This engagement strengthened the research by embedding Indigenous perspectives and lived experiences, leading to a more nuanced and culturally responsive analysis.

Results

Population demographic and service-related characteristics of MBS mental health service users

A total of 2,494,381 individuals (2.98% Indigenous) resided in SEQ throughout 2021. Of these, 298,283 (4.17% Indigenous) used MBS-subsidised mental health services. Table 1 summarises the sociodemographic characteristics of these mental health service users, revealing significant differences between Indigenous and non-Indigenous Australians. Indigenous service users were younger, less likely to reside in major cities, more likely to belong to the lowest 40% household income quantile, less likely to be married, less likely to hold a post-secondary degree, less likely to be employed, and more likely to have a history of mental health conditions. These patterns were consistent within the subset who used any MBS-subsidised telehealth mental health services (n = 78,048; 3.93% Indigenous) (see Supplemental Appendix 4). Table 2 presents the telehealth service-related characteristics of this group.

Table 2.

Service-related characteristics of people who used telehealth-delivered Medicare mental health services (n = 78,048).

Service-related characteristics	Indigenous (n = 3,067; 3.93%)	Non-Indigenous (n = 74,981; 96.70%)	p values	Chi-square/t
Rates of telehealth use within SEQ sample (n = 2,494,381) (%; count) a	4.12% (3067)	3.10% (74,981)	<0.001	248.93
Rates of telehealth use within MH sample (n = 259,578) (%; count) b	24.66% (3067)	26.23% (74,981)	<0.001	15.31
Telehealth modality (%; count) c			<0.001	65.78
Include video conference	40.53% (1243)	47.99% (35,984)
Include phone but not video conference	59.47% (1824)	52.01% (38,997)
Telehealth mental health service type (%; count) d			<0.001	122.21
Services include psychotherapies	61.88% (1898)	69.11% (51,817)
Services by only GP	18.49% (567)	12.06% (9042)
Other services	19.63% (602)	18.83% (14,122)
Percentage of bulk billed sessions (mean; SD)	81.61 (37.20)	62.24 (46.45)	<0.001	22.75
Mean gap payment for telehealth items (mean; SD)	14.92 (36.04)	31.48 (48.70)	<0.001	–18.58
Number of telehealth sessions total (mean; SD)	2.68 (3.31)	2.98 (3.79)	<0.001	–4.31
Number of telehealth sessions GP (mean; SD)	0.56 (1.04)	0.52 (1.05)	0.025	2.24
Number of telehealth sessions psychologists including clinical psychologists (mean; SD)	1.31 (2.44)	1.45 (2.65)	0.003	–2.92

GP: general practitioner; SEQ: Southeast Queensland.

^aRates of telehealth use within SEQ sample calculated the rates of telehealth use within the whole SEQ population (n = 2,494,381).

^bRates of telehealth use within MH sample calculated the rates of telehealth use within the population who utilised at least one MBS mental health services (n = 259,578).

^cHierarchical categories: (1) telehealth services included video conferences and (2) telehealth services did not include video conferences.

^dHierarchical categories: (1) services include psychotherapies, (2) services do not include psychotherapies and are only from GP(s), and (3) other combination of services (i.e. no psychotherapies but saw providers other than just GP).

Significant differences were also observed in telehealth service-related factors. Within the overall SEQ population, Indigenous individuals had higher rates of telehealth use (4.12% vs 3.10%, p < 0.001). However, within the population using any MBS-subsidised mental health services, Indigenous Australians had lower rates of telehealth use (24.66% vs 26.23%, p < 0.001), a pattern that persisted after adjusting for sociodemographic variables (adults: OR = 0.89, p < 0.001; children: OR = 0.89, p = 0.021; Supplemental Appendix 5).

Compared with their non-Indigenous counterparts, a smaller proportion of Indigenous telehealth users used telehealth-delivered psychotherapies (61.88% vs 69.11%, p < 0.001) and more used telehealth services provided only by GPs (18.49% vs 12.06%, p < 0.001). They were also less likely to use video services (40.53% vs 47.99%, p < 0.001) but more phone services (59.47% vs 52.01%, p < 0.001). In addition, Indigenous participants had a higher proportion of bulk-billed telehealth sessions (81.61% vs 62.24%, p < 0.001) and paid lower gap fees on average where not bulk-billed (AUD 14.92 vs AUD 31.48, p < 0.001).

In terms of the number of telehealth services used, Indigenous participants used fewer MBS-subsidised telehealth mental health services overall than non-Indigenous participants (2.68 vs 2.98, p < 0.001), including fewer services delivered by psychologists (1.31 vs 1.45, p = 0.003), but more services delivered by GPs (0.56 vs 0.52, p = 0.025).

Telehealth was associated with a smaller increase in number of mental health services used by Indigenous Australians

Table 3 presents the results of the linear regression analysis. Telehealth was significantly associated with an increased number of mental health services used for both Indigenous and non-Indigenous Australians. However, the increase in number of MBS-subsidised mental health service used was significantly smaller among Indigenous Australians compared with non-Indigenous Australians. This disparity was most notable for video-delivered telehealth services, with a significant interaction effect (coefficient = −0.76, p < 0.001).

Table 3.

Linear regression results examining the association between telehealth modalities and number of MBS mental health services used by Indigenous and non-Indigenous Australians.

	Total n = 298,283
	Coefficient	p value	95% CI lower	95% CI upper
Telehealth modalities
Include phone but not video a	3.69	<0.001	3.64	3.75
Include video a	6.40	<0.001	6.34	6.46
Indigenous status
Indigenous b	–0.76	<0.001	–0.87	–0.66
Telehealth modalities × Indigenous status
Include phone but not video × Indigenous c	–0.18	0.168	–0.45	0.08
Include video × Indigenous c	–0.76	<0.001	–1.07	–0.45

CI: confidence interval; MBS: Medicare Benefits Schedule.

^aReference group: face-to-face.

^bReference group: non-Indigenous.

^cReference group: non-Indigenous population who used face-to face services.

Factors associated with rates of telehealth-delivered MBS mental health service use among Indigenous Australians in SEQ

Table 4 presents the results of the multivariate logistic regression model examining factors associated with rates of telehealth mental health service use among Indigenous Australians in SEQ. Among Indigenous adults, predisposing factors significantly associated with higher rates of telehealth use included being female (OR = 1.38, p < 0.001), aged 25 to 69, and having a post-secondary degree. No significant predisposing factors were identified for Indigenous children. For non-Indigenous adults, similar predisposing factors were observed (Supplemental Appendix 6), but additional factors were found to be significant. Non-Indigenous adults who were unmarried (OR = 1.08, p < 0.001) or lived in non-family households (OR = 1.16, p < 0.001) showed higher rates of telehealth use, while those in two or more households had lower rates of telehealth use (OR = 0.90, p < 0.001). Among children, being aged 12 to 17 was associated with higher rates of telehealth use for non-Indigenous children (OR = 1.18, p < 0.001) but not for Indigenous children (OR = 1.07, p = 0.530).

Table 4.

Logistic regression model of rates of telehealth use for the 2021 Indigenous Australians who used any MBS mental health services in SEQ.

	Indigenous adults (n = 7866) Pseudo R2 = 0.03; AIC = 8905.62; BI = 9100.79				Indigenous children (n = 2645) Pseudo R2 = 0.03 AIC = 2606.54; BIC = 2706.50
	OR	p value	95% CI lower	95% CI upper	OR	p value	95% CI lower	95% CI upper
Predisposing factors
Sex
Male	1.00				1.00
Female	1.38	<0.001	1.239	1.54	0.87	0.155	0.71	1.06
Age (years old)
18–24 (0–11 for children)	1.00				1.00
25–39 (12–17 years for children)	1.22	0.006	1.059	1.40	1.07	0.530	0.87	1.32
40–54	1.28	0.002	1.093	1.51	NA	NA b	NA	NA
55–69	1.25	0.034	1.017	1.54	NA	NA	NA	NA
70 and older	1.10	0.647	0.721	1.69	NA	NA	NA	NA
Aboriginal language used at home
No	1.00				NA
Yes	1.20	0.272	0.869	1.65	NA	NA	NA	NA
Marital status
Married	1.00				NA
Not married	0.96	0.517	0.844	1.09	NA	NA	NA	NA
Not applicable	0.93	0.589	0.720	1.21	NA	NA	NA	NA
Education attainment
Year 10 and below	1.00				NA
Year 11 or 12	1.02	0.808	0.868	1.20	NA	NA	NA	NA
Post-secondary degree/certificate	1.22	0.007	1.056	1.41	NA	NA	NA	NA
Household composition
One family household	1.00				1.00
Two and more	0.90	0.390	0.720	1.14	1.01	0.962	0.67	1.52
Non-family household a	1.11	0.129	0.971	1.27	1.12	0.760	0.54	2.34
Contextual factors
Remoteness
Major cities	1.00				1.00
Regional or remote	1.20	0.051	0.999	1.44	0.95	0.751	0.69	1.30
Not applicable	1.31	0.468	0.631	2.72	NA	NA	NA	NA
Number of residence locations
One	1.00				1.00
Two	0.94	0.413	0.823	1.08	1.19	0.142	0.94	1.51
Three and more	1.04	0.763	0.797	1.36	0.83	0.482	0.50	1.39
Enabling factors
Household income quantile
0%–20%	1.00				1.00
21%–40%	0.92	0.223	0.794	1.06	1.00	0.978	0.78	1.29
41%–60%	1.05	0.524	0.900	1.23	0.95	0.720	0.72	1.26
61%–80%	0.93	0.499	0.767	1.14	1.55	0.012	1.10	2.18
81%–100%	1.19	0.115	0.958	1.49	0.94	0.810	0.56	1.58
Labour force status
Employed	1.00				NA
Unemployed	0.92	0.420	0.751	1.13	NA	NA	NA	NA
Not in the labour force	1.21	0.005	1.059	1.38	NA	NA	NA	NA
Need factors
History of mental health conditions
No history	1.00				1.00
Exist history	1.75	< 0.001	1.573	1.95	2.04	< 0.001	1.66	2.50
Number of chronic health conditions
No conditions	1.00				1.00
One or more conditions	0.96	0.433	0.855	1.07	1.00	0.993	0.79	1.27
Health service factors
HHS regions
Gold Coast HHS	1.00				1.00
Metro North HHS	0.99	0.868	0.845	1.15	0.68	0.007	0.51	0.90
Metro South HHS	1.08	0.328	0.926	1.26	0.63	0.001	0.48	0.84
West Moreton HHS	0.98	0.863	0.816	1.19	0.66	0.014	0.48	0.92

ABS: Australian Bureau of Statistics; AIC: Akaike information criterion; BIC: Bayesian information criterion; CI: confidence interval; HHS: Hospital and Health Service; MBS: Medicare Benefits Schedule; OR: odds ratio; SEQ: Southeast Queensland.

^aNon-family household includes lone person household, group household, visitors only, other non-classifiable households, unoccupied private dwellings, non-private dwellings, migratory, offshore and shipping SA1s.

^b“NA” refers to variables that are not applicable or not feasible to report for the children population (<18 years old). For example, age 40+ is not applicable to individuals under 18, and variables such as marital status, educational attainment, and labour force status do not apply to children. In addition, the “Aboriginal language spoken at home” variable was excluded for children due to the very small number of cases, which would risk re-identification when combining with other characteristics under ABS confidentiality rules. For the same confidentiality reasons, children fell into “not applicable” category was not included and reported as “NA.”

No contextual factors were found to be significantly associated with rates of telehealth use for Indigenous adults or children. However, housing instability (those with multiple residences in 2021) was associated with higher rates of telehealth use among non-Indigenous adults.

Regarding enabling factors, Indigenous adults not in the labour force had significantly higher rates of telehealth use (OR = 1.21, p = 0.005). For Indigenous children, household income in the 61 to 80% quantile was associated with higher rates of telehealth use (OR = 1.55, p = 0.012). Among non-Indigenous adults, higher household income was associated with higher rates of telehealth use.

For need factors, the history of mental health conditions was significantly associated with increased rates of telehealth use in both adults (OR = 1.75, p < 0.001) and children (OR = 1.95, p < 0.001). No significant differences in need factors were observed between Indigenous and non-Indigenous Australians.

Regarding health service factors, no significant associations were found for adults. However, Indigenous children living in the Gold Coast HHS had higher rates of telehealth use. In contrast, for non-Indigenous adults, residing in the Gold Coast HHS was associated with lower rates of telehealth use, a pattern not seen in Indigenous adults.

Factors associated with number of telehealth-delivered MBS mental health services used by Indigenous Australians in SEQ

Table 5 shows the results of multivariate linear regression models examining factors associated with number of telehealth-delivered MBS mental health services used by Indigenous adults and children in SEQ. Among Indigenous adults, those aged 40 and above and those not speaking an Aboriginal language at home used more MBS telehealth mental health services. For Indigenous children, ages 12 to 17 were associated with more telehealth use. Similar predisposing factors were significant for non-Indigenous adults (Supplemental Appendix 7), but additional factors emerged. Non-Indigenous adults who were unmarried, had higher educational attainment, or lived in non-family households used more telehealth mental health services – factors not significant for Indigenous adults.

Table 5.

Linear regression model of number of telehealth-delivered MBS mental health service used for the 2021 Indigenous Australians in SEQ who used any MBS telehealth mental health service.

	Indigenous adults (n = 2073)				Indigenous children (n = 524)
	R2 = 0.14; AIC = 4605.82; BIC = 4786.20				R2 = 0.14; AIC = 939.43; BIC = 1028.93
	EC	p value	95% CI lower	95% CI upper	EC	p value	95% CI lower	95% CI upper
Predisposing factors
Sex
Male	Reference				Reference
Female	1.04	0.293	0.97	1.12	0.93	0.156	0.84	1.03
Age (years old)
18–24 (0–11 for children)	Reference				Reference
25–39 (12–17 years for children)	1.07	0.116	0.98	1.16	1.12	0.029	1.01	1.25
40–54	1.15	0.006	1.04	1.27	NA b	NA	NA	NA
55–69	1.22	0.004	1.06	1.39	NA	NA	NA	NA
70 and older	1.27	0.047	1.00	1.62	NA	NA	NA	NA
Aboriginal language used at home
No	Reference				NA
Yes	0.83	0.025	0.70	0.98	NA	NA	NA	NA
Marital status
Married	Reference				NA
Not married	1.05	0.180	0.98	1.14	NA	NA	NA	NA
Not applicable	0.98	0.845	0.84	1.15	NA	NA	NA	NA
Education attainment
Year 10 and below	Reference				NA
Year 11 or 12	1.05	0.383	0.94	1.16	NA	NA	NA	NA
Post-secondary degree/certificate	1.03	0.476	0.94	1.14	NA	NA	NA	NA
Household composition
One family household	Reference				Reference
Two and more	0.98	0.812	0.85	1.14	1.20	0.144	0.94	1.55
Non-family household a	0.96	0.314	0.89	1.04	1.03	0.900	0.69	1.52
Contextual factors
Remoteness
Major cities	Reference				Reference
Regional or remote	1.09	0.130	0.97	1.22	1.05	0.618	0.87	1.26
Not applicable	0.84	0.353	0.59	1.21	NA	NA	NA	NA
Number of residence locations
One	Reference				Reference
Two	1.02	0.666	0.93	1.11	1.00	0.972	0.88	1.13
Three and more	0.91	0.313	0.76	1.09	0.88	0.265	0.70	1.11
Enabling factors
Household income quantile
0%–20%	Reference				Reference
21%–40%	0.98	0.680	0.90	1.07	0.93	0.279	0.82	1.06
41%–60%	0.97	0.607	0.89	1.07	0.95	0.552	0.82	1.11
61%–80%	0.91	0.132	0.81	1.03	0.80	0.011	0.67	0.95
81%–100%	1.01	0.887	0.88	1.16	0.86	0.330	0.64	1.16
Labour force status
Employed	Reference				NA
Unemployed	0.95	0.390	0.84	1.07	NA	NA	NA	NA
Not in the labour force	1.07	0.084	0.99	1.16	NA	NA	NA	NA
Need factors
History of mental health conditions
No history	Reference				Reference
Exist history	1.14	<0.001	1.07	1.22	1.15	0.009	1.04	1.29
Number of chronic health conditions
No conditions	Reference				Reference
One or more conditions	1.07	0.071	0.99	1.15	0.99	0.889	0.88	1.12
Health service factors
HHS regions
Gold Coast HHS	Reference				Reference
Metro North HHS	0.90	0.053	0.83	1.00	0.97	0.597	0.85	1.10
Metro South HHS	1.00	0.963	0.90	1.09	1.13	0.076	0.99	1.30
West Moreton HHS	0.93	0.243	0.83	1.05	1.07	0.460	0.90	1.28
Mental health service type
Not include psychotherapies	Reference				Reference
Only psychotherapies	1.16	0.035	1.01	1.32	1.31	0.006	1.08	1.58
Psychotherapies and others	1.34	<0.001	1.25	1.43	1.28	<0.001	1.15	1.42
Percentage of bulk-billed items	1.00	0.014	1.00	1.00	1.00	0.361	1.00	1.00
Telehealth modalities
Only phone services	Reference				Reference
Include video services	1.42	<0.001	1.32	1.52	1.25	<0.001	1.12	1.40

ABS: Australian Bureau of Statistics; AIC: Akaike information criterion; BIC: Bayesian information criterion; CI: confidence interval; EC: exponentiated coefficients; HHS: Hospital and Health Service; MBS: Medicare Benefits Schedule; SEQ: Southeast Queensland.

^aNon-family household includes lone person household, group household, visitors only, other non-classifiable households, unoccupied private dwellings, non-private dwellings, migratory, offshore and shipping SA1s.

^b“NA” refers to variables that are not applicable or not feasible to report for the children population (<18 years old). For example, age 40+ is not applicable to individuals under 18, and variables such as marital status, educational attainment, and labour force status do not apply to children. In addition, the “Aboriginal language spoken at home” variable was excluded for children due to the very small number of cases, which would risk re-identification when combining with other characteristics under ABS confidentiality rules. For the same confidentiality reasons, children fell into “not applicable” category was not included and reported as “NA.”

No contextual factors were associated with higher telehealth use in either Indigenous or non-Indigenous adults and children.

Regarding enabling factors, no associations were found for Indigenous adults. However, Indigenous children from households in the 61%–80% income quantile had a lower number of telehealth used (EC = 0.80, p = 0.011). For non-Indigenous adults, unemployment was associated with increased number of telehealth used (EC = 1.07, p < 0.001), though this was not observed for Indigenous adults (EC = 0.95, p = 0.390).

For need factors, a history of mental health conditions was associated with a higher number of telehealth used for adults (EC = 1.14, p < 0.001) and children (EC = 1.15, p = 0.009). No significant differences in need factors were found between Indigenous and non-Indigenous Australians.

Among health service factors, Indigenous adults using psychotherapy or video services used more telehealth-delivered mental health services (EC = 1.42, p < 0.001). Similarly, Indigenous children receiving psychotherapy or using video services showed an increased number of telehealth services used (EC = 1.25, p < 0.001). For non-Indigenous adults, residing in the Gold Coast HHS was associated with a lower number of telehealth services used, a trend not seen in Indigenous adults. Among non-Indigenous children, living in Metro North HHS was linked to reduced number of telehealth used (EC = 0.96, p = 0.032), while no such association was found for Indigenous children (EC = 0.97, p = 0.597).

Discussion

Mental health is the most prominent domain for telehealth applications in both research and service delivery for Indigenous Australians (Moecke et al., 2023). While telehealth has been shown to reduce health service disparities for Indigenous Australians (Clair et al., 2019; Couch et al., 2021; Smith et al., 2019), our analysis of population-level data from SEQ reveals differences in rates and the number of MBS-subsidised telehealth mental health services used among Indigenous Australians. Most studies estimate rates of telehealth use by comparing telehealth users to the general population, overlooking service need (Alam et al., 2019; Russell et al., 2015). Our study found that the rate of telehealth use among Indigenous Australians appeared higher when calculated using the general Indigenous population as the denominator. However, when accounting for service need—restricting the denominator to those who used any mental health services—Indigenous Australians demonstrated lower rates of telehealth mental health services use, and telehealth appeared to be associated with a smaller increase in the number of mental health services used than non-Indigenous Australians. Certain subgroups within Indigenous communities also encountered additional barriers to using these services. These findings align with previous research indicating that systemic, cultural, and socioeconomic factors contribute to disparities in telehealth service use.

The cultural appropriateness of telehealth for Indigenous Australians remains a topic of debate (Caffery et al., 2018; Terrill et al., 2025). The current study indicates that Indigenous Australians utilised telehealth services less frequently, highlighting the need for further evaluation and improvement of telehealth models to better support mental health management in these communities. Notably, in accordance with previous research (Beks et al., 2023) which found that rural Indigenous participants preferred phone services because of technology-related issues, our study found that Indigenous Australians used fewer video-based telehealth services than non-Indigenous Australians even in urban areas. This disparity may be partially attributed to limited access to the Internet and telehealth devices among Indigenous Australians. Strengthening telehealth infrastructure and building greater telehealth capacity within mental health services may help bridge this gap. For example, the Institute for Urban Indigenous Health provided the MobLink service—which involved mental health providers bringing telehealth devices directly to Indigenous communities—was well received and demonstrated high uptake. Cultural preferences for phone communication over video consultations may stem from perceptions of greater privacy and comfort when using the phone, as well as difficulties in establishing trust through video-based interactions. In addition, service types influence patterns of telehealth use, with Indigenous Australians relying more on GP-delivered and bulk-billed telehealth services. This reliance reflects financial and systemic barriers to using higher-cost services such as psychotherapy, which are often delivered via video (Banbury et al., 2022).

Second, consistent with previous research, the current study suggests that the uptake of telehealth in Australia has enhanced the use of mental health services for both Indigenous (Couch et al., 2021; Ferrari et al., 2023) and non-Indigenous Australians (Cantor et al., 2023), likely because of reduced time, cost, and travel barriers. However, telehealth, particularly video-based services, was associated with a greater number of mental health services used among non-Indigenous Australians compared with Indigenous Australians. This aligns with findings by Nariyoshi Miyata and colleagues (Miyata and North, 2024), which reported disproportionately higher failure-to-attend rates among Indigenous Australians in telehealth settings, potentially due to challenges in trust-building and differing cultural preferences. Despite patients’ preferences, mental health providers’ preferences also played a role in the uptake of telehealth services among Indigenous Australians. Providers have reported that telehealth is most effective when there is an established relationship with the client, when clients have good digital literacy, and when services are delivered in a culturally safe manner (Fitzpatrick et al., 2023). These factors highlight the need for culturally appropriate telehealth models that support relationship-building and account for varying levels of digital access and readiness among Indigenous communities. These findings raise concerns that the widespread adoption of telehealth could exacerbate existing health disparities unless services are tailored to be culturally appropriate and suitable for Indigenous communities. Future research should explore Indigenous Australians’ and their mental health providers’ perceptions and preferences regarding telehealth mental health services, and targeted measures are needed to improve access, particularly to video-based services.

This study identified several factors associated with rates and the number of telehealth services used among Indigenous adults and children in urban areas. Need factors were the most prominent predictors of the rate of telehealth use for both groups, previous research has demonstrated that people with mental health conditions such as depression, anxiety, and schizophrenia have difficulties in attending face-to-face mental health appointments (Binnie and Boden, 2016; Daniels et al., 2014; Moscrop et al., 2012). Our findings suggest that telehealth services may offer a more flexible and accessible alternative, resulting in higher rates of use among this population (Ferrari et al., 2023).

For the number of telehealth services used, health service factors played a critical role, indicating that alignment between telehealth service characteristics and Indigenous preferences strongly influences retention and dropout rates. In addition, several predisposing and enabling factors were associated with telehealth access and utilisation. Among adults, age and the use of Aboriginal languages at home were significant predisposing factors. Rates of telehealth use followed a bell-shaped pattern, with adults aged 40–54 having the highest rates of use, likely due to midlife mental health needs, work and family pressures, and familiarity with technology. Older adults may face barriers such as unfamiliarity with technology or cognitive decline. Targeted support, including caregiver involvement and user-friendly platforms, may help improve rates of telehealth service use for these groups. The number of telehealth services used, however, increased linearly with age, with those aged 70 and older using the most telehealth services, likely reflecting higher mental health needs and the convenience of telehealth for mobility challenges. Aboriginal language use at home, often considered a protective factor for Indigenous mental health, however, was associated with a lower number of telehealth services used. This finding may reflect several interconnected barriers identified in previous telehealth literature, including lower digital access and connectivity, linguistic barriers, concerns regarding cultural safety, and preferences for face-to-face or community-based communication approaches (Fitzpatrick et al., 2023; Gibson et al., 2011; Terrill et al., 2025). For some Indigenous communities, telehealth may also be perceived as less suitable for building trust and relational connection, which are central to culturally responsive mental health care. In addition, people who primarily speak Aboriginal languages at home may be more likely to reside in communities with reduced digital infrastructure and fewer culturally adapted telehealth services. These findings highlight the need for culturally responsive telehealth models, targeted outreach programmes, and telehealth approaches that better incorporate linguistic, relational, and community preferences.

For Indigenous children, age was the only significant predisposing factor, with those aged 12–17 using more telehealth services. Adolescence is a critical period for mental health care, and telehealth offers accessible and practical solutions for teenagers balancing school and other commitments. Caregivers may also find telehealth a time-efficient option. Enabling factors, such as household income, were significant for children but not for adults. Children in the 61%–80% income bracket had higher rates of telehealth service use but a lower number of services used, suggesting financial stability may facilitate initial engagement, while lower sustained use could reflect fewer ongoing needs or barriers like costs and caregiver responsibilities. In addition, Indigenous children in the Gold Coast HHS exhibited higher rates of telehealth use compared with other HHS regions within SEQ, including Metro North, Metro South, and West Moreton. Differences across HHS regions may reflect variation in healthcare infrastructure, digital connectivity, local service models, telehealth implementation practices, and population characteristics. This result may potentially be due to better healthcare infrastructure, greater digital connectivity, and targeted regional programmes. Proximity to urban centres with dense healthcare resources and socioeconomic factors may also contribute to this trend.

When compared with non-Indigenous Australians, significant factors influencing rates and the number of telehealth services used were similar for both groups, but non-Indigenous Australians displayed a broader range of predictors. This may reflect greater variability in telehealth use patterns due to factors like socioeconomic diversity and digital literacy. In contrast, systemic barriers, such as limited culturally appropriate services and infrastructure constraints, may overshadow the influence of sociodemographic factors for Indigenous Australians, highlighting the need for targeted interventions to improve telehealth equity.

Strengths and limitations

Several limitations should be considered when interpreting the results. First, the data were collected in 2021 when COVID-19 was a driver for increased telehealth services. Telehealth use could have changed since then. Moreover, our analysis excluded mental health care that could be provided under general MBS items (e.g. Level B consultation) or through services not subsidised by Medicare, which were not able to be identified within the dataset. This limitation could lead to an underestimation of mental health service use for Indigenous Australians. Finally, model fit statistics showed modest but consistent explanatory power (Pseudo R² ≈ 0.02–0.03; R² ≈ 0.12–0.14), which is typical for population-level studies. This indicates that key sociodemographic, need, and service-related factors were captured, while unmeasured contextual and cultural influences likely explain remaining variation. Overall, the models were stable and appropriately specified (AIC/BIC), supporting the robustness of findings and highlighting opportunities for future research integrating broader contextual and community-informed data. Finally, because of small subgroup sizes and ABS DataLab confidentiality requirements, more granular analyses of rurality were not feasible in the current study. Future research using larger national datasets and classifications such as the Modified Monash Model may provide a more detailed understanding of telehealth utilisation across different levels of rurality.

Implications

To ensure equitable telehealth use, policymakers should prioritise culturally appropriate initiatives, improve digital infrastructure, and expand bulk-billed services. Medicare has taken steps in this direction with the introduction of item number 294, which supports culturally appropriate telehealth care. However, further efforts are needed to strengthen co-designed telehealth programmes and culturally sensitive outreach to enhance engagement and trust. Future research should explore Indigenous preferences and the long-term impact of telehealth on mental health outcomes to inform more inclusive service delivery.

Conclusion

By using linked Medicare and Census data, this study demonstrates that telehealth alone does not address disparities in Medicare-funded mental health service use between Indigenous and non-Indigenous populations in SEQ. Although telehealth has contributed to increased mental health service utilisation among Indigenous populations, the magnitude of improvement is smaller than that observed for non-Indigenous populations. Furthermore, Indigenous Medicare mental health service users were overall less likely to use telehealth services. The findings also reveal that certain subgroups—particularly older adults, individuals with lower educational attainment, and those reliant on phone-based telehealth—continue to face additional barriers to using telehealth services. These barriers likely relate to limited digital infrastructure, privacy concerns, insufficient cultural adaptation, and challenges in trust-building within virtual care. Overall, this study highlights the need for targeted, culturally safe telehealth strategies that address the specific technological and cultural needs of Indigenous communities to fully harness telehealth’s potential in reducing mental health care inequities.