VIEWER: An electronic audit and feedback tool for the delivery of population health management applied to mental health care

Abstract Background: Due to the burden and negative impacts of psychotic disorders, treatment alone is insufficient to reduce the gap in psychosis care thereby highlighting the need for greater investment in prevention strategies which are targeted towards an entire population to detect risk factors early and prevent adverse health outcomes at scale. This work evaluates the technical feasibility of implementing electronic audit and feedback (eA&F) to support population health management in mental health care by facilitating the visualisation of clinical health records to provide relevant summaries for eA&F. Methods: A Participatory Design approach was adopted as an integral framework throughout the design and development of an eA&F platform. The eA&F platform, VIEWER, was evaluated for its technical feasibility. The feasibility testing of the platform was carried out with clinical teams in the context of three different clinical use cases to support eA&F for managing the psychosis patient population. Results: An eA&F platform for supporting population health management was developed. The platform was used successfully for eA&F to support the identification of unmet needs, variations in care processes, and inequalities between groups of patients within the psychosis patient population. Conclusions: It is technically feasible to develop and deploy an eA&F platform that supports population health management in secondary mental healthcare. Using advanced clinical analytics to integrate population-level data with routine clinical practice raises exciting possibilities of building more intelligent services that are adaptive to the needs of the population, and adopt a more proactive, preventative approach. The innovative eA&F platform gives clinicians the flexibility to look at clinical data that is relevant to them at the level of abstraction that is appropriate for the decision being made. By sharing the methods and steps taken in this work, useful insights can be provided to other researchers and practitioners that are developing similar digital health interventions.