Summary Project Synergy aims to test the potential of new and emerging technologies to enhance the quality of mental health care provided by traditional face‐to‐face services. Specifically, it seeks to ensure that consumers get the right care, first time (delivery of effective mental health care early in the course of illness). Using co‐design with affected individuals, Project Synergy has built, implemented and evaluated an online platform to assist the assessment, feedback, management and monitoring of people with mental disorders. It also promotes the maintenance of wellbeing by collating health and social information from consumers, their supportive others and health professionals. This information is reported back openly to consumers and their service providers to promote genuine collaborative care. The online platform does not provide stand‐alone medical or health advice, risk assessment, clinical diagnosis or treatment; instead, it supports users to decide what may be suitable care options. Using an iterative cycle of research and development, the first four studies of Project Synergy (2014–2016) involved the development of different types of online prototypes for young people (i) attending university; (ii) in three disadvantaged communities in New South Wales; (iii) at risk of suicide; and (iv) attending five headspace centres. These contributed valuable information concerning the co‐design, build, user testing and evaluation of prototypes, as well as staff experiences during development and service quality improvements following implementation. Through ongoing research and development (2017–2020), these prototypes underpin one online platform that aims to support better multidimensional mental health outcomes for consumers; more efficient, effective and appropriate use of health professional knowledge and clinical skills; and quality improvements in mental health service delivery.
Background Health information technologies are being rapidly developed to improve the delivery of mental health care; however, a range of facilitators, barriers, and contextual conditions can impact the adoption and sustainment of these solutions. An implementation science protocol supports researchers to achieve primary effectiveness goals in relation to mental health services reform and aids in the optimization of implementation processes to promote quality health care, prolonging sustainability. Objective The aim of this paper is to describe our implementation science protocol, which serves as a foundation by which to systematically guide the implementation of technology-enabled solutions in traditional face-to-face and Web-based mental health services, allowing for revisions over time on the basis of retrospective review and constructive feedback from the services in which the technology-enabled solutions are implemented. Methods Our implementation science protocol comprises four phases. The primary objective of the scoping and feasibility phase (Phase 1) is to determine the alignment between the service partner and the quality improvement goals supported by the technology-enabled solution. This is followed by Phase 2, the local co-design and preimplementation phase, which aims to utilize co-design methodologies, including service pathway modelling, participatory design, and user (acceptance) testing, to determine how the solutions could be used to enhance the service. In Phase 3, implementation, the accepted solution is embedded in the mental health service to achieve better outcomes for consumers and their families as well as health professionals and service managers. Using iterative evaluative processes throughout Phase 3, the solution is continuously developed, designed, and refined during implementation to adapt to the changing needs of the stakeholders, including consumers with lived experience and their families as well as the service. Thus, the primary outcome of Phase 3 is the optimized technology-enabled solution that can be maintained in a service during the sustainment and scalability phase (Phase 4) for the purposes of mental health services reform. Results Funding for the protocol was provided by the Australian Government Department of Health in June of 2017 for a period of 3 years. At the time of this publication, the protocol had been initiated in 11 services, serving three populations, all of which are currently operating in Phase 3. The first results are expected to be submitted for publication in 2020. Conclusions With the aim of improving mental health service quality, our implementation science protocol aids in the identification of factors that predict the likelihood of implementation success, as well as the development of strategies to proactively mitigate potential barriers to achieve better implementation outcomes. Putting in place a theoretically sound implementation science protocol is essential to facilitate the uptake of novel technology-enabled solutions and evidence-based practices into routine clinical practice for the purposes of improved outcomes.
Background Globally, there are fundamental shortcomings in mental health care systems, including restricted access, siloed services, interventions that are poorly matched to service users’ needs, underuse of personal outcome monitoring to track progress, exclusion of family and carers, and suboptimal experiences of care. Health information technologies (HITs) hold great potential to improve these aspects that underpin the enhanced quality of mental health care. Objective Project Synergy aimed to co-design, implement, and evaluate novel HITs, as exemplified by the InnoWell Platform, to work with standard health care organizations. The goals were to deliver improved outcomes for specific populations under focus and support organizations to enact significant system-level reforms. Methods Participating health care organizations included the following: Open Arms–Veterans & Families Counselling (in Sydney and Lismore, New South Wales [NSW]); NSW North Coast headspace centers for youth (Port Macquarie, Coffs Harbour, Grafton, Lismore, and Tweed Heads); the Butterfly Foundation’s National Helpline for eating disorders; Kildare Road Medical Centre for enhanced primary care; and Connect to Wellbeing North Coast NSW (administered by Neami National), for population-based intake and assessment. Service users, families and carers, health professionals, and administrators of services across Australia were actively engaged in the configuration of the InnoWell Platform to meet service needs, identify barriers to and facilitators of quality mental health care, and highlight potentially the best points in the service pathway to integrate the InnoWell Platform. The locally configured InnoWell Platform was then implemented within the respective services. A mixed methods approach, including surveys, semistructured interviews, and workshops, was used to evaluate the impact of the InnoWell Platform. A participatory systems modeling approach involving co-design with local stakeholders was also undertaken to simulate the likely impact of the platform in combination with other services being considered for implementation within the North Coast Primary Health Network to explore resulting impacts on mental health outcomes, including suicide prevention. Results Despite overwhelming support for integrating digital health solutions into mental health service settings and promising impacts of the platform simulated under idealized implementation conditions, our results emphasized that successful implementation is dependent on health professional and service readiness for change, leadership at the local service level, the appropriateness and responsiveness of the technology for the target end users, and, critically, funding models being available to support implementation. The key places of interoperability of digital solutions and a willingness to use technology to coordinate health care system use were also highlighted. Conclusions Although the COVID-19 pandemic has resulted in the widespread acceptance of very basic digital health solutions, Project Synergy highlights the critical need to support equity of access to HITs, provide funding for digital infrastructure and digital mental health care, and actively promote the use of technology-enabled, coordinated systems of care.
Background Culturally diverse populations (including Aboriginal and Torres Strait Islander people, people of diverse genders and sexualities, and culturally and linguistically diverse people) in nonurban areas face compounded barriers to accessing mental health care. Health information technologies (HITs) show promising potential to overcome these barriers. Objective This study aims to identify how best to improve a mental health and well-being HIT for culturally diverse Australians in nonurban areas. Methods We conducted 10 co-design workshops (N=105 participants) in primary youth mental health services across predominantly nonurban areas of Australia and conducted template analysis on the workshop outputs. Owing to local (including service) demographics, the workshop participants naturalistically reflected culturally diverse groups. Results We identified 4 main themes: control, usability, affirmation, and health service delivery factors. The first 3 themes overlap with the 3 basic needs postulated by self-determination theory (autonomy, competence, and relatedness) and describe participant recommendations on how to design an HIT. The final theme includes barriers to adopting HITs for mental health care and how HITs can be used to support care coordination and delivery. Hence, it describes participant recommendations on how to use an HIT. Conclusions Although culturally diverse groups have specific concerns, their expressed needs fall broadly within the relatively universal design principles identified in this study. The findings of this study provide further support for applying self-determination theory to the design of HITs and reflect the tension in designing technologies for complex problems that overlap multiple medical, regulatory, and social domains, such as mental health care. Finally, we synthesize the identified themes into general recommendations for designing HITs for mental health and provide concrete examples of design features recommended by participants.
Enhanced care coordination is essential to improving access to and navigation between youth mental health services. By facilitating better communication and coordination within and between youth mental health services, the goal is to guide young people quickly to the level of care they need and reduce instances of those receiving inappropriate care (too much or too little), or no care at all. Yet, it is often unclear how this goal can be achieved in a scalable way in local regions. We recommend using technology-enabled care coordination to facilitate streamlined transitions for young people across primary, secondary, more specialised or hospital-based care. First, we describe how technology-enabled care coordination could be achieved through two fundamental shifts in current service provisions; a model of care which puts the person at the centre of their care; and a technology infrastructure that facilitates this model. Second, we detail how dynamic simulation modelling can be used to rapidly test the operational features of implementation and the likely impacts of technology-enabled care coordination in a local service environment. Combined with traditional implementation research, dynamic simulation modelling can facilitate the transformation of real-world services. This work demonstrates the benefits of creating a smart health service infrastructure with embedded dynamic simulation modelling to improve operational efficiency and clinical outcomes through participatory and data driven health service planning.
Background The World Economic Forum has recently highlighted substantial problems in mental health service provision and called for the rapid deployment of smarter, digitally-enhanced health services as a means to facilitate effective care coordination and address issues of demand. In mental health, the biggest enabler of digital solutions is the implementation of an effective model of care that is facilitated by integrated health information technologies (HITs); the latter ensuring the solution is easily accessible, scalable and sustainable. The University of Sydney’s Brain and Mind Centre (BMC) has developed an innovative digital health solution – delivered through the Youth Mental Health and Technology Program – which incorporates two components: 1) a highly personalised and measurement-based (data-driven) model of youth mental health care; and 2) an industrial grade HIT registered on the Australian Register of Therapeutic Goods. This paper describes a research protocol to evaluate the impact of implementing the BMC’s digital health solution into youth mental health services (i.e. headspace - a highly accessible, youth-friendly integrated service that responds to the mental health, physical health, alcohol or other substance use, and vocational concerns of young people aged 12 to 25 years) within urban and regional areas of Australia. Methods The digital health solution will be implemented into participating headspace centres using a naturalistic research design. Quantitative and qualitative data will be collected from headspace health professionals, service managers and administrators, as well as from lead agency and local Primary Health Network (PHN) staff, via service audits, Implementation Officer logs, online surveys, and semi-structured interviews, at baseline and then three-monthly intervals over the course of 12 months. Discussion At the time of publication, six headspace centres had been recruited to this study and had commenced implementation and impact evaluation. The first results are expected to be submitted for publication in 2021. This study will focus on the impact of implementing a digital health solution at both a service and staff level, and will evaluate digital readiness of service and staff adoption; quality, usability and acceptability of the solution by staff; staff self-reported clinical competency; overall impact on headspace centres as well as their lead agencies and local PHNs; and social return on investment.
Background Scaling evidence-based interventions are key to impacting population health. The National DPP lifestyle change program is one such intervention that has been scaled across the USA over the past 20 years; however, enrollment is an ongoing challenge. Furthermore, little is known about which organizations are most successful with program delivery, enrollment, and scaling. This study aims to understand more about the internal and external organization factors that impact program implementation and reach. Methods Between August 2020 and January 2021, data were collected through semi-structured key informant interviews with 30 National DPP delivery organization implementers. This study uses a qualitative cross-case construct rating methodology to assess which Consolidated Framework for Implementation Research (CFIR) inner and outer setting constructs contributed (both in valence and magnitude) to the organization’s current level of implementation reach (measured by average participant enrollment per year). A construct by case matrix was created with ratings for each CFIR construct by interviewee and grouped by implementation reach level. Results Across the 16 inner and outer setting constructs and subconstructs, the interviewees with greater enrollment per year provided stronger and more positive examples related to implementation and enrollment of the program, while the lower reach groups reported stronger and more negative examples across rated constructs. Four inner setting constructs/subconstructs (structural characteristics, compatibility, goals and feedback, and leadership engagement) were identified as “distinguishing” between enrollment reach levels based on the difference between groups by average rating, the examination of the number of extreme ratings within levels, and the thematic analysis of the content discussed. Within these constructs, factors such as organization size and administrative processes; program fit with existing organization services and programs; the presence of enrollment goals; and active leadership involvement in implementation were identified as influencing program reach. Conclusions Our study identified a number of influential CFIR constructs and their impact on National DPP implementation reach. These findings can be leveraged to improve efforts in recruiting and assisting delivery organizations to increase the reach and scale of the National DPP as well as other evidence-based interventions.
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