Health service use among ex-serving Australian Defence Force members

The previous sections described overall health service use, including the proportion of ex-serving members accessing each health service, the types of health services used, and average number of health services used. However, those analyses considered each health service type in isolation and did not show how individuals used several health services in combination or whether distinct patterns of health service engagement existed within the cohort.

This section presents results from a modelling technique called latent class analysis (LCA) used to identify subgroups (or groups) of health service users among ex-serving members. This data-driven analytical approach groups individuals based on their patterns of engagement across seven indicators of health service use, derived from hospital (ED and admitted care), PBS/RPBS and MBS data for 2019–20. These indicators captured mental health, non-mental health and investigation-related services (such as diagnostic procedures, diagnostic imaging, and pathology from MBS), providing more holistic view of health service use.

Understanding these patterns provides insights beyond simple averages into how ex-serving members interacted with the health system and where gaps in engagement may have occurred. For example, some ex-serving members may have limited contact with health services or may rely on one type of care (like prescriptions) without using others (such as hospitals). The analysis presented below was limited to ex-serving members for 2019–20 as the most recent year in the data because patterns were found to be similar in earlier years.

The LCA identified four groups of health service users among ex-serving members. These groups reflect differences in the frequency, type or combination of health services used. Labels were assigned descriptively, based on the relative frequency and type of health service use across the cohort rather than fixed thresholds, and are intended to summarise the dominant health service use characteristics within each group. Table 2 shows the predicted average number of health service use per person across the seven indicators for each user group.

Each of the groups are described as follows based on average health service use per person in 2019–20:

• Minimal service user: ex-serving members in this group represent the lowest users of health services, with lowest average use across all health services, totalling 0.7 health services per person. This group included 45,900 ex-serving members (20% of the cohort).
• Moderate service user (higher mental health): ex-serving members in this group showed higher use than the minimal user group, and notably higher use of mental health medications and hospital services. They included 45,100 ex-serving members (20% of the cohort) and had average total health service use of 24 services per person.
• Moderate service user (mixed): this group showed moderate health service use overall. They included 106,000 ex-serving members (47% of the cohort) and had average total health service use of 33 services per person.
• High service user: this group demonstrated high overall service use, driven primarily by non-mental health services. This group included 30,500 ex-serving members (13% of the cohort) and had average total health service use of 109 services per person. This group likely includes individuals with multiple or complex health needs.

Source: AIHW Veterans Health Dataset (VHD), July 2014–June 2020.

The distribution of ex-serving members across the four latent groups remained stable over the study period. The proportion of minimal service users decreased slightly, from 23.4% in 2013–14 to 20.2% in 2019–20, while the high user group increased from 11.8% to 13.4% over the same period (which may have been due to the ex-serving population becoming older over the period). The moderate user groups showed small year-to-year variation but remained the largest subgroups overall. These trends suggest a gradual increase in the proportion of ex-serving members with higher health service use. This may reflect increased health needs, improved access to care, reduced stigma, or a combination of these factors. Observing such changes in how ex-serving members engage with health services may help inform future planning, service delivery, and support strategies to better meet evolving health needs.

Which ex-serving members are using more health services?

The distribution of characteristics (demographics, service-related and health-related) across the four groups was examined to understand which characteristics were more commonly observed in each group, based on their relative proportions. AIHW also performed multinomial logistic regression to further assess the relationship between each characteristic and allocation to a group.

Compared to the minimal user (reference) group, those aged 55 years and over, with 20 or more years of ADF service, separated from ADF involuntarily due to medical reasons, those with one or more comorbidities and high continuity of GP care were more likely to be in one of the three higher health service user groups (moderate user (higher mental health), moderate user (mixed) and high user). Females were more commonly represented in the moderate user (mixed) and high user groups, compared with males.

In contrast, ex-serving members who were younger (aged under 35 years), or had no identified comorbidities were more likely to belong into the minimal health service use group. These patterns are visually shown in Figure 4, with supporting relative risk ratio estimates presented in Supplementary Table S4.4.

A relatively high proportion of DVA clients were in the moderate user (higher mental health) group and less were in the minimal group. The multinomial logistic regression found that DVA clients were more likely to be in each of the three higher health service user groups. It should be noted that DVA-funded MBS equivalent services were not included in this analysis. Therefore, DVA clients were grouped as higher service users irrespective of their use of DVA-funded services.