The application of a clinical staging model to an early intervention youth mental health service

The central aim of this thesis was to obtain and analyse demographic, clinical and service use data of young people attending a newly created youth mental health service initiative (known as ‘headspace’) in order to inform further service model enhancement. To do this, a new diagnostic framework for mental health, known as clinical staging, was applied. Used widely in other areas of medicine, the clinical staging model places individuals with mental distress and related functional impairment on a severity spectrum. This model is particularly well suited to youth mental health services and the young people they assist as it provides an account for early stage illness not typically recognised by the traditional mental health diagnostic system, such as the Diagnostic and Statistical Manual of Mental Disorders (DSM). Traditional services based on the categorical paradigm of the DSM tend to intervene too late, if at all. A number of studies have shown that mental disorders tend to develop and worsen for many over time. Furthermore, sub-threshold conditions (those that are below current diagnostic thresholds for disorder) can and often do develop into more significant and severe mental disorders over time. The creation of these new government-funded early intervention centres around Australia has improved the opportunities for young people and their carers to access timely mental health treatment. Research shows that many of those accessing these centres have early stage, sub-threshold disorders, and yet clear frameworks for the diagnosis and differential management of these young people accessing these centres are absent, resulting in many with diverse needs receiving essentially the same treatment. Initially, these services were established on the back of substantial and compelling epidemiological data that highlighted the high prevalence rates of mental disorder in young people in the community. The current series of studies sought to add to this evidence by utlising clinical service data from the people accessing these services to further inform and strengthen the model. In order to do this, two studies were conducted that examined the treatment patterns, service engagement and short-term clinical and functional outcomes of young people at early clinical stages to assist in informing the development of the model. The first study showed that the intensity of treatment differed across the two early clinical stages (stage 1a and 1b), with those at stage 1b much more likely to receive more combinations of treatment (medication, psychological therapy, case management) than those at 1a. Stage 1a young people showed improvements in both symptoms and functioning over 10 sessions (the usual treatment limit imposed by government funding), however those at stage 1b remained at high levels of distress and functional impairment after treatment despite improvement over time. The second study went on to show that those at stage 1b had significantly poorer rates of service attendance than those at stage 1a. Stage 1b patients made more appointments and missed more appointments, even when controlling for other potentially confounding variables. Further, the lack of diagnostic clarity for young people at stage 1b was shown to have a significant impact on their appointment behaviour, such that those with more diagnostic ambiguity had much poorer attendance. On the basis of the data obtained in the first two studies, and other research done in this area, a model of care for early intervention youth mental health services was developed based on the clinical staging concept. Here, more thorough initial assessment, better team management practices and assertive follow-up and monitoring of those at stage 1b were recommended. The third and fourth studies reported on the clinical outcomes of those at stage 1b managed under this new service model framework. Symptomatic and functional improvements in this group were equivalent to those reported in less severe clinical populations, and importantly, rates of clinically significant deterioration were much lower than reported elsewhere. Despite intervention, a portion of patients transitioned from stage 1b to stage 2, and these transitions were significantly associated with NEET (not in education, employment or training) status, as well as the presence of negative symptoms at initial assessment. Overall, the findings of the studies presented in this thesis support the use of models informed by clinical staging that essentially match severity and need to treatment intensity, akin to stepped care service models. In particular, those at clinical stage 1b represent a vulnerable group who appear to require greater treatment intensity with proactive outcome monitoring delivered over a period longer than that typically provided. To this end, the use of digital technologies that enable better information transfer between patient and clinician may assist with this challenge, as well as re-orienting services to sharpen their focus on this more vulnerable cohort through more sophisticated online supports that may reduce the burden on clinical services, which have the ultimate goal of providing the right level of care at the right time. Further and ongoing empirical testing of these model refinements will grow the evidence base that will result in better, more timely, more response and more personalised service systems for young people.