Cross-Sectoral Collaboration Between Mental Health Hospitals and Municipalities: A Scoping Review

Abstract

Introduction: Cross-sectoral collaboration between mental health hospitals and municipalities addresses the multifaceted needs of individuals with mental health conditions. Recovery-oriented care emphasizes personal empowerment, holistic support, and integrated services. However, barriers to collaboration hinder effective service delivery. This scoping review explores how recovery-oriented approaches are integrated within collaborative practices and identifies key barriers and facilitators to cross-sectoral collaboration. Methods: This review followed Arksey and O’Malley’s framework, with systematic searches conducted in PubMed, CINAHL, PsycINFO, and Web of Science. Studies published between 2012 and 2024 were included if they focused on cross-sectoral collaboration within a recovery-oriented framework. Data from 30 peer-reviewed articles were synthesized to identify themes related to barriers, facilitators, and best practices. Results: Barriers to collaboration included fragmented communication systems, cultural and professional differences, and power imbalances across sectors. Structural challenges, such as discrepancies in legislative and funding mechanisms, hindered integration. Successful models, such as Individual Placement and Support (IPS) and Open Dialogue, demonstrated the potential of structured frameworks in overcoming barriers. User involvement emerged as a pivotal facilitator of meaningful collaboration but remains underutilized in practice. Discussion: Recovery-oriented care necessitates overcoming systemic and cultural barriers to develop integrated, person-centered approaches. Despite promising practices, gaps in understanding long-term outcomes and user perspectives persist, highlighting the need for further research. Conclusion: Effective collaboration between mental health hospitals and municipalities is fundamental to delivering recovery-oriented care. Future research should explore standardized metrics, enhance user involvement, and assess the scalability of successful models to strengthen integration.