Implementing large-system, value-based healthcare initiatives: a realist study protocol for seven natural experiments

Abstract

<jats:sec><jats:title>Introduction</jats:title><jats:p>Value-based healthcare delivery models have emerged to address the unprecedented pressure on long-term health system performance and sustainability and to respond to the changing needs and expectations of patients. Implementing and scaling the benefits from these care delivery models to achieve large-system transformation are challenging and require consideration of complexity and context. Realist studies enable researchers to explore factors beyond ‘what works’ towards more nuanced understanding of ‘what tends to work for whom under which circumstances’. This research proposes a realist study of the implementation approach for seven large-system, value-based healthcare initiatives in New South Wales, Australia, to elucidate how different implementation strategies and processes stimulate the uptake, adoption, fidelity and adherence of initiatives to achieve sustainable impacts across a variety of contexts.</jats:p></jats:sec><jats:sec><jats:title>Methods and analysis</jats:title><jats:p>This exploratory, sequential, mixed methods realist study followed RAMESES II (Realist And Meta-narrative Evidence Syntheses: Evolving Standards) reporting standards for realist studies. Stage 1 will formulate initial programme theories from review of existing literature, analysis of programme documents and qualitative interviews with programme designers, implementation support staff and evaluators. Stage 2 envisages testing and refining these hypothesised programme theories through qualitative interviews with local hospital network staff running initiatives, and analyses of quantitative data from the programme evaluation, hospital administrative systems and an implementation outcome survey. Stage 3 proposes to produce generalisable middle-range theories by synthesising data from context–mechanism–outcome configurations across initiatives. Qualitative data will be analysed retroductively and quantitative data will be analysed to identify relationships between the implementation strategies and processes, and implementation and programme outcomes. Mixed methods triangulation will be performed.</jats:p></jats:sec><jats:sec><jats:title>Ethics and dissemination</jats:title><jats:p>Ethical approval has been granted by Macquarie University (Project ID 23816) and Hunter New England (Project ID 2020/ETH02186) Human Research Ethics Committees. The findings will be published in peer-reviewed journals. Results will be fed back to partner organisations and roundtable discussions with other health jurisdictions will be held, to share learnings.</jats:p></jats:sec>