Improving health with and for individuals with schizophrenia using a learning health system approach : From idea to daily practice

Abstract: Psychotic disorders like schizophrenia have a typical onset in early adulthood with symptoms of hallucinations and disturbances of thought. Despite knowledge on what constitutes effective schizophrenia care, more than 70% of treatment attempts fail in Sweden, sometimes leading to early death. An appraisal of schizophrenia care shows a lack of ways to jointly plan and evaluate care, and an absence of a trustworthy theory-of-change. The Learning Health System (LHS) is a vision that has been translated into theories and models associated with improved outcomes for patients with other chronic conditions. The aim of this thesis is to enhance the understanding of the applicability of the LHS vision in the context of schizophrenia care, from the perspectives of both individuals and the health system in enabling coproduction of better health by addressing two research questions:i) How can improvement of health for individuals with schizophrenia and improvement of system performance be supported by coproduction in an LHS model?ii) Can an LHS-based intervention, i.e. the use of a point of care dashboard, contribute to better health for individuals with schizophrenia?Studying the existing published knowledge of LHS show that the concept has not yet been applied in mental healthcare settings but has potential to increase patient coproduction, continuous improvement and better health. Different forms of coproduction are supported in the most comprehensive LHS models and applications, ranging from dashboards at point of care to platforms that can help facilitate improvement initiatives.A case study, focused on studying the use and usefulness of a point-of-care dashboard at patient visits in outpatient care at the Department of Schizophrenia Spectrum Disorders at Sahlgrenska University Hospital in western Sweden. Use of the dashboard is associated with improved communication and health for patients. Assessment of the dashboard-project’s complexity using the Non-adoption, abandonment, scale-up, spread and sustainability complexity assessment tool (NASSS-CAT) was perceived as helpful in evaluating challenges and provided insight that can guide future development. An LHS model, that builds on both the reviewing of the literature and practical testing, is proposed.Further research is proposed in two areas, exploration of how dashboard initiatives can support coproduction and better health for individuals with complex chronic conditions and further development of LHS models by studying different LHS initiatives regarding system properties, forms of coproduction at play and effects on health outcomes for individuals and populations.