This study provides an example of applying a needs-based planning model to inform mental health service development. It involved an assessment of existing resources and their utilisation to determine how future service design could ensure equitable service provision at the regional level. This was in alignment with the aims of Tasmania’s 2020 Rethink Strategy. Key findings related to each sector, and available indicators of service access, activity, and capacity, are discussed.
First, service access varied across and within HSRs. The North-West HSR had the highest rate of access to bed-based services. However, two LGAs in this region (i.e., Circular Head and King Island) had access rates among the lowest in the state, which may be explained by their remoteness (27). Across all HSRs, rates of access to bed-based services were highest in urban regions, where most services were located, with some anomalies. For example, Kingborough LGA had one of the lowest rates of access to bed-based services in the state, despite its proximity to a major service area (Hobart LGA). Kingborough is a relatively advantaged area and its residents may be accessing private hospitals; Hobart Clinic, a private service, is located just outside the Kingborough LGA. Patterns in rates of access to jurisdictional clinical ambulatory services were similar. In the primary care and private clinical ambulatory service sector, rates of access to PHT commissioned services were highest in the Northern HSRs as compared to the South; the opposite was true for MBS services. This likely represents the strategic location of PHT commissioned services to account for the fewer private MBS providers in the Northern HSRs as compared to the South. Indeed, PHT’s health service directory suggests that a majority of these providers are located in the South HSR (29).
Second, available beds were used as an indicator of the capacity of bed-based services. The number of available beds was largely comparable to the NMHSPF estimate. The number of acute adult beds, and the average associated annual separation rate, were also on par with NMHSPF estimates. At the time of analysis, stakeholders revealed that Tasmania’s Hospital in the Home program was scheduled to commence in 2020, further increasing adult acute bed capacity across the state. Whilst there were fewer sub- and non-acute beds in the Northern HSRs as compared to the South HSR, the beds in the South HSR were state-wide services. These beds were, however, largely used by South HSR residents. Further investigation is needed to understand why residents in the Northern HSRs are not accessing these services (e.g., are they less inclined to use services away from their support networks? Are there other service types in the Northern HSRs catering to populations that require this type of care?). At the time of this study there were no dedicated child and adolescent mental health beds in Tasmania. Without access to age-specialist beds, young people in need are likely to either receive no inpatient treatment, or be admitted to adult units which increases risk of iatrogenic harm (30). Notably, however, stakeholders mentioned the planned establishment of child and youth specific bed-based services that aim to fill this gap.
Third, the number of FTE staff employed in jurisdictional clinical ambulatory services was lower than the NMHSPF estimates, with this finding more pronounced in services for older persons. When interpreting these findings it should be acknowledged that the NMHSPF model carries assumptions about service operation (e.g. mix of professionals and hours worked in team-based services) and efficiency (e.g. the ratio of consumer-related time to other time such as travel, meetings etc.) that influence how estimates are produced. We ensured that on-the-ground FTE staff were defined and counted in a similar way to the NMHSPF to limit misinterpretation of the comparative analyses. The identified shortfalls in older persons FTE staff is not a new finding, nor is it unique to Tasmania. A recent inquiry noted that expansion in clinical ambulatory services across Australia is required to meet the needs of older persons (22). Tasmania currently has the oldest population in Australia which, due to internal migration, is ageing faster than any other jurisdiction (31). It is therefore expected that there will be continued increasing need for specialist services for older persons in Tasmania. Tasmania’s ‘Rethink 2020’ plan for mental health recognises that the recruitment of suitably qualified staff is one of the greatest challenges and is a key priority to meeting service demand (24).
Fourth, whilst funding/expenditure in the primary care and private clinical ambulatory services sector reached over half of the NMHSPF estimated indicative costs, activity (i.e. occasions of service) reached less than half of the NMHSPF estimate; there are several potential reasons for this finding. First, not all services in this sector were included in the comparative analysis (e.g. private health insurance, Department of Veterans’ Affairs and Worker’s Compensation funded ambulatory services). Additionally, even in included data collections there is the potential for missing data. For example, some mental health care provided by general practitioners is often not captured under the MBS mental health items included in the MBS data collection (Australian Institute of Health and Welfare, 2021). Alternatively, lower than expected service activity may be representative of underservicing due to barriers to service access. If the latter is true, future service design should account for this potential barrier. For example, headspace outreach services have recently been established to increase access and uptake of primary mental health care services among disadvantaged young people in Tasmania (32).
Fifth, funding for CMMHS was largely comparable to the NMHSPF estimated indicative costs. Due to lack of data, it was not feasible to investigate the level of activity occurring within these services. Future work should examine the level and scope of activity occurring within these services to ensure that funding is used to deliver the full range of psychosocial support service types projected by the NMHSPF. Developing a better understanding of activity within this sector would also be helpful to further explore potential system imbalances. For example, it might be that areas with good provision of psychosocial support services see a reduction in the utilisation of bed-based services or the average length of treatment within state clinical ambulatory services.
Limitations
This study had several limitations. First, data from some in-scope services were: (1) not routinely collected; or (2) not available for study purposes. Select indicators of service activity and capacity were therefore chosen for analysis based on the availability of on-the-ground services data. For example, for bed-based services, separations were used an as indicator of activity and available beds were used as an indicator of capacity. However, data on occupancy and staffing, which both have impacts on how services operate, were not available. Thus, a true like-for-like comparison for the bed-based services sector was not possible. Further, there were no routinely collected data for the CMMHS sector which meant that only a high-level comparative analysis of funding could be undertaken. Additionally, there were services data from ‘other’ primary care and private clinical ambulatory services that were not available for the purposes of this study. The inclusion of these data may have reduced the apparent activity and capacity gaps in this sector. However, these ‘other’ services are much smaller component of the overarching system compared to jurisdictionally funded specialist clinical services and MBS and PHN funded primary care services, as evidenced by the relatively smaller financial investment they receive (33). Similarly, data pertaining to access, activity and capacity of privately funded bed-based services were also not available. This data may have provided contextual information to further inform the interpretation of findings regarding bed-based services.
Second, even when data existed, not all data of interest could be provided. For example, often service capacity data in the form of FTE staff counts was not routinely collected. For some data collections, we used funding/expenditure data instead. However, funding data included in the comparative analysis, specifically in the CMHHS sector, may have included costs that are out-of-scope for the NMHSPF model (e.g. capital costs). Furthermore, the quality of available data was variable across and within data collections and services. Outliers in the data often prompted discussions with custodians as to whether there were issues with the reliability of available data or the services themselves (e.g. were occasions of service low because of poor reporting, or was there genuine low activity within a service/across a collection of services), but it was not possible to quantify to what extent the data was reliable or otherwise within this study. Investigation is, however, warranted to determine whether there are issues with the data collections. If this is the case, concerted effort should be directed at improving reporting. It is suggested that ensuring professionals are aware of the purpose of data collection, and receive feedback based on an analysis of the collected data, may improve adherence to data collection protocols (22).
Third, V2.2 of the NMHSPF uses national average age-specific estimates of the prevalence of mental health problems and applies these to the population size and age distribution of different area levels to determine the level of need and associated resourcing requirements. However, socioeconomic features of areas and degrees of remoteness also contribute to variation in mental health service needs across regions (34). According to the 2016 Census, Tasmania has the lowest proportion of people living in the most advantaged areas of all Australian states and territories and the highest proportion living in the most disadvantaged areas (35). Additionally, within Tasmania, the South HSR comprises relatively fewer areas of disadvantage than the North and North West HSRs (36). Much of the state is also considered outer regional or remote, while its two most populated cities, Hobart and Launceston, are classified as inner regional (27). Thus, by applying national average estimates of service need to Tasmania, and the smaller regions that comprise it, this study is likely to underestimate levels of required resourcing and potential service gaps, particularly in the North and North West HSRs.
Fourth, this study focused on understanding levels of mental health service capacity and activity from a population planning perspective. Health service utilisation is influenced by additional factors such as individual attitudes, stigma, and resource barriers including distance to and cost of services (37). These are important further considerations in ensuring that people with mental health needs have equitable access to mental health services, however were beyond the scope of this analysis.
Broader policy implications
This study has identified key considerations when mapping mental health services data and comparing these to the NMHSPF outputs. First, it has shown the importance of analysing services data at small area levels that are important for planning. Examining services data at larger area-levels (e.g. PHNs, LHNs or HSRs) may mask issues of service access, activity, and capacity at the local level at which planning decisions are made. Second, our study highlights the importance of using contextual information to interpret comparative analyses with the NMHSPF. The NMHSPF is an important starting point for understanding resourcing requirements but should be supplemented with information on unique sociodemographic and contextual features that may influence local service access and need. Findings from the current comparative analysis were contextualised by gathering information about existing services, services under development, and sociodemographic information for different geographical regions. Further development of the NMHSPF has since been completed to adapt its estimates for the specific mental health needs of Aboriginal and Torres Strait Islander and rural populations (38). Third, this study has identified the importance of understanding the assumptions that underlie NMHSPF outputs. Specifically, a sound comparative analysis with the NMHSPF relies on the comparison of like-for-like services data. In this study we worked closely with the data custodians and service funders to ensure that on-the-ground services data was comparable to the NMHSPF estimates based on data definitions and the NMHSPF taxonomy. Fourth, this work highlights the importance of developing a comprehensive map of all mental health services and collectively reviewing service location, access, activity, and capacity across service sectors. If services or sectors are examined in isolation, important information regarding system imbalances, or where one service type appears to fill the gap of another, may be missed.