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 Health information technologies (HITs) are becoming increasingly recognized for their potential to provide innovative solutions to improve the delivery of mental health services and drive system reforms for better outcomes. Objective This paper describes the baseline results of a study designed to systematically monitor and evaluate the impact of implementing an HIT, namely the InnoWell Platform, into Australian mental health services to facilitate the iterative refinement of the HIT and the service model in which it is embedded to meet the needs of consumers and their supportive others as well as health professionals and service providers. Methods Data were collected via web-based surveys, semistructured interviews, and a workshop with staff from the mental health services implementing the InnoWell Platform to systematically monitor and evaluate its impact. Descriptive statistics, Fisher exact tests, and a reliability analysis were used to characterize the findings from the web-based surveys, including variability in the results between the services. Semistructured interviews were coded using a thematic analysis, and workshop data were coded using a basic content analysis. Results Baseline data were collected from the staff of 3 primary youth mental health services (n=18), a counseling service for veterans and their families (n=23), and a helpline for consumers affected by eating disorders and negative body image issues (n=6). As reported via web-based surveys, staff members across the services consistently agreed or strongly agreed that there was benefit associated with using technology as part of their work (38/47, 81%) and that the InnoWell Platform had the potential to improve outcomes for consumers (27/45, 60%); however, there was less certainty as to whether their consumers’ capability to use technology aligned with how the InnoWell Platform would be used as part of their mental health care (11/45, 24% of the participants strongly disagreed or disagreed; 15/45, 33% were neutral; and 19/45, 42% strongly agreed or agreed). During the semistructured interviews (n=3) and workshop, participants consistently indicated that the InnoWell Platform was appropriate for their respective services; however, they questioned whether the services’ respective consumers had the digital literacy required to use the technology. Additional potential barriers to implementation included health professionals’ digital literacy and service readiness for change. Conclusions Despite agreement among participants that HITs have the potential to result in improved outcomes for consumers and services, service readiness for change (eg, existing technology infrastructure and the digital literacy of staff and consumers) was noted to potentially impact the success of implementation, with less than half (20/45, 44%) of the participants indicating that their service was ready to implement new technologies to enhance mental health care. Furthermore, participants reported mixed opinions as to whether it was their responsibility to recommend technology as part of standard care.

No abstract

BACKGROUND Health information technologies (HITs) are becoming increasingly recognised for their potential to provide innovative solutions to improve the delivery of mental health services and drive system reform for better outcomes. A growing body of research aims to evaluate how innovative HITs can be co-designed and successfully implemented in mental health services to enhance their provision of care. OBJECTIVE The objective of this paper is to describe baseline results for a study designed to systematically monitor and evaluate the impact of implementing HIT-enabled solutions into Australian mental health services, with the aim of facilitating the iterative refinement of these solutions to meet the needs of consumers and their supportive others as well as health professionals and service providers. METHODS Data were collected via Web-based surveys, semi-structured interviews, and a workshop with staff from the mental health services implementing the HIT-enabled solutions to systematically monitor and evaluate their impact. Descriptive statistics and Fisher exact tests were used to characterise the findings from the Web-based surveys, including variability in the results based on service. Semi-structured interviews were coded using thematic analysis and workshop data was coded using basic content analysis. RESULTS At the end of the first phase of impact evaluation, baseline data had been collected from staff from three primary youth mental health services (n=18), a counselling service for veterans and their families (n=23), and a helpline for individuals affected by eating disorders and negative body image issues (n=6). As reported via Web-based surveys, staff members across the services consistently “agreed” or “strongly agreed” there was benefit associated with using technology as part of their work (80.9%) and that HIT-enabled solutions have the potential to improve outcomes for consumers (60.0%); however, there was less certainty as to whether their consumers’ capability to use technology aligned with how solutions would be used as part of their mental health care (24.4% “strongly disagreed” or “disagreed”; 33.3% “neutral”; and 42.2% “strongly agreed” or “agreed”). Implementation barriers and facilitators for consumers, health professionals and at the service level were derived from the baseline semi-structured interviews (n=3) and a workshop. Participants consistently indicated that the HIT-enabled solution was appropriate for their respective services; however, questioned whether their consumers had the digital literacy required to use the technology. Additional potential barriers to implementation included health professional’s digital literacy as well as service readiness for change in relation to adopting the HIT-enabled model of care. CONCLUSIONS Baseline data from the first phase of data collection highlight consistent themes related to the successful implementation of HIT-enabled solutions in mental health services, including the value of assessing service readiness for change (e.g. existing technology infrastructure and the digital literacy of staff and consumers), the importance of leadership from senior service management and local champions to drive quality improvement, and the necessity for effective education and training in the context of continuous on the ground support. Longitudinal data will provide a deeper understanding of the impact of HIT-enabled solutions on service quality and digital readiness and competence as well as the social return on investment and the quality, usability and acceptability of the solution.