Innovative preclinic triage system to guide Australians to the right mental health care first time.

This paper presents a case study of an innovative direct-to-consumer preclinic triage system designed to reduce predicted peak demand for Australian mental health services as a result of COVID-19 and its associated socioeconomic consequences by guiding Australians to the right mental health care first time. Our innovative, digital health solution comprises two components: (1) a highly personalised and measurement-based model of care (Brain and Mind Centre model of care) that considers both the heterogeneity of mental disorders and other underlying comorbidities, as well as clinical staging; and (2) a health information technology (i.e. the InnoWell Platform). This digital health solution has been embedded as part of standard service delivery into a community-based intake service, thus resulting in a redesigned service model. The service model is currently being implemented as part of a pilot feasibility study, the marker of acceptability at the health professional and service level, and is now under active evaluation to determine its effect on outcomes for consumers, health professionals and the service. For the purposes of this paper, this model served as a prototype for the preclinic triage system that was conceptualised for national scalability at the primary health network level. When implemented at a national level, our direct-to-consumer preclinic triage system is expected to be an effective population health demand management strategy to address the rapidly emerging mental health demand crisis in Australia, and is aligned with the recent recommendation from the Productivity Commission to develop a sustainable national digital platform to facilitate the assessment and referral process to ensure access to mental health care matched to an individual's level of need.What is known about the topic?Although there is increased recognition of the mental health demand crisis in Australia as a result of the COVID-19 pandemic, little has been done to 'flatten' the curve. The Australian Government committed additional funding to support the Better Access Pandemic Support measure; however, this approach to care fails to appreciate both the disparities in service availability across Australia and the gap fees that are prohibitive to some of those seeking help. Furthermore, the expansion of this program may only result in those in care remaining in care, thus further delaying access to those in need.What does this paper add?This paper describes a digital health solution, comprised of a highly personalised and measurement-based model of care coupled with a health information technology, that has been embedded as part of standard service delivery. Consumers seeking mental health care complete a multidimensional self-report assessment via the technology, the results of which are available in real-time and used to facilitate triage to pathways of care as indicated by the severity of the consumer's illness and level of need to more effectively and efficiently allocate consumers to care. The redesigned service model is now under active evaluation to determine its effects on outcomes at consumer, health professional and service levels.What are the implications for practitioners?The redesigned local service model served as a prototype for our innovative direct-to-consumer preclinic triage system specifically designed to allocate consumers to self-management, ambulatory care or acute care based on clinical stage and level of need. It is our hypothesis that the preclinic triage system will be an effective population health demand management strategy. Importantly, the proposed preclinic triage system aligns with the recent recommendation from the Productivity Commission for the Australian Government to fund the development and sustained implementation of a digital platform to facilitate assessment and referral to evidence-based interventions matched to a consumer's level of need.

The Impact of Technology-Enabled Care Coordination in a Complex Mental Health System: A Local System Dynamics Model.

BACKGROUND: Prior to the COVID-19 pandemic, major shortcomings in the way mental health care systems were organized were impairing the delivery of effective care. The mental health impacts of the pandemic, the recession, and the resulting social dislocation will depend on the extent to which care systems will become overwhelmed and on the strategic investments made across the system to effectively respond. OBJECTIVE: This study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination on mental health and suicide outcomes. METHODS: A system dynamics model for the regional population catchment of North Coast New South Wales, Australia, was developed that incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and suicidal behavior. The model reproduced historic time series data across a range of outcomes and was used to evaluate the relative impact of a set of scenarios on attempted suicide (ie, self-harm hospitalizations), suicide deaths, mental health-related emergency department (ED) presentations, and psychological distress over the period from 2021 to 2030. These scenarios include (1) business as usual, (2) increase in service capacity growth rate by 20%, (3) standard telehealth, and (4) technology-enabled care coordination. Each scenario was tested using both pre- and post-COVID-19 social and economic conditions. RESULTS: Technology-enabled care coordination was forecast to deliver a reduction in self-harm hospitalizations and suicide deaths by 6.71% (95% interval 5.63%-7.87%), mental health-related ED presentations by 10.33% (95% interval 8.58%-12.19%), and the prevalence of high psychological distress by 1.76 percentage points (95% interval 1.35-2.32 percentage points). Scenario testing demonstrated that increasing service capacity growth rate by 20% or standard telehealth had substantially lower impacts. This pattern of results was replicated under post-COVID-19 conditions with technology-enabled care coordination being the only tested scenario, which was forecast to reduce the negative impact of the pandemic on mental health and suicide. CONCLUSIONS: The use of technology-enabled care coordination is likely to improve mental health and suicide outcomes. The substantially lower effectiveness of targeting individual components of the mental health system (ie, increasing service capacity growth rate by 20% or standard telehealth) reiterates that strengthening the whole system has the greatest impact on patient outcomes. Investments into more of the same types of programs and services alone will not be enough to improve outcomes; instead, new models of care and the digital infrastructure to support them and their integration are needed.

Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants.

BACKGROUND: Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance of investments required to have the greatest impacts on SB. Real-world experimentation to establish the optimal targeting, timing, scale, frequency, and intensity of investments required across the determinants is unfeasible. Therefore, this study harnesses systems modelling and simulation to guide population-level decision making that represent best strategic allocation of limited resources. METHODS: Using a participatory approach, and informed by a range of national, state, and local datasets, a system dynamics model was developed, tested, and validated for a regional population catchment. The model incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and SB. Intervention scenarios were investigated to forecast their impact on SB over a 20-year period. RESULTS: A combination of social connectedness programs, technology-enabled coordinated care, post-attempt assertive aftercare, reductions in childhood adversity, and increasing youth employment projected the greatest impacts on SB, particularly in a youth population, reducing self-harm hospitalisations (suicide attempts) by 28.5% (95% interval 26.3-30.8%) and suicide deaths by 29.3% (95% interval 27.1-31.5%). Introducing additional interventions beyond the best performing suite of interventions produced only marginal improvement in population level impacts, highlighting that 'more is not necessarily better.' CONCLUSION: Results indicate that targeted investments in addressing the social determinants and in mental health services provides the best opportunity to reduce SB and suicide. Systems modelling and simulation offers a robust approach to leveraging best available research, data, and expert knowledge in a way that helps decision makers respond to the unique characteristics and drivers of SB in their catchments and more effectively focus limited health resources.