JMIR Publications

ABSTRACT

Background:

Given the strong evidence for their effectiveness, early intervention services for psychosis (EIS) are being widely implemented. However, heterogeneity in the implementation of essential components, remains an ongoing challenge. Rapid learning health systems (RLHS), that embed data collection in clinical settings for real-time learning and continual quality improvement, can address this challenge. We therefore implemented a RLHS in 11 EIS in Quebec, Canada.

Objective:

This project aims to determine the feasibility and acceptability of implementing a RLHS in EIS, and to assess its impact on compliance with standards for essential EIS components.

Methods:

Following literature recommendations, the implementation of this RLHS involves six iterative phases: external and internal scan, design, implementation, evaluation, adjustment, and dissemination. Multiple stakeholder groups (service users, families, clinicians, researchers, decision makers, provincial EIS association) are involved in all phases. Meaningful indicators of EIS quality (e.g., satisfaction, timeliness of response to referrals) were selected based on literature review, provincial guidelines, and stakeholder consensus on indicators prioritisation. A digital infrastructure was designed and deployed that comprises (a) a user-friendly interface for routinely collecting data from programs (b) a digital terminal and mobile app to collect feedback from service users and families regarding care received, health, and quality of life (c) data analytic, visualization and reporting functionalities to provide participating programs with real-time feedback on their performance over time, and in relation to standards and to other programs, along with tailored recommendations. Community of practice activities are being conducted that leverage insights from data to build capacity among programs to continually progress towards aligning their practice with standards/best practices. Guided by the RE-AIM framework, we are collecting quantitative and qualitative data on the Reach, Effectiveness Adoption, Implementation and Maintenance of our RLHS. These RE-AIM data will be analyzed to evaluate our RLHS’s impacts.

Results:

Funding and ethics approval were received July and December 2019. Phase 1 (identifying indicators for the RLHS for EIS based on a literature synthesis, through a survey and consensus meetings of all stakeholder groups) and phase 2 (developing and implementing the RLHS digital infrastructure) are completed. Phases 3-5 are ongoing since June 2020: Continuous data collection through the RLHS data capture platforms and real time feedback to all stakeholders have been deployed. Phase 6 will assess the impact of the RLHS using the RE-AIM framework, with quantitative and qualitative data.

Conclusions:

This project will yield valuable insights about how a RLHS can be implemented by EIS, along with preliminary evidence for its acceptability, feasibility and impacts on program-level outcomes. Its findings will refine our RLHS further and advance approaches that bring data, stakeholder voices and collaborative learning to improve outcomes and service quality in psychosis. Clinical Trial: NA