Insights into vaccine hesitancy from systems thinking, Rwanda.

OBJECTIVE: To investigate vaccine hesitancy leading to underimmunization and a measles outbreak in Rwanda and to develop a conceptual, community-level model of behavioural factors. METHODS: Local immunization systems in two Rwandan communities (one recently experienced a measles outbreak) were explored using systems thinking, human-centred design and behavioural frameworks. Data were collected between 2018 and 2020 from: discussions with 11 vaccination service providers (i.e. hospital and health centre staff); interviews with 161 children's caregivers at health centres; and nine validation interviews with health centre staff. Factors influencing vaccine hesitancy were categorized using the 3Cs framework: confidence, complacency and convenience. A conceptual model of vaccine hesitancy mechanisms with feedback loops was developed. FINDINGS: A comparison of service providers' and caregivers' perspectives in both rural and peri-urban settings showed that similar factors strengthened vaccine uptake: (i) high trust in vaccines and service providers based on personal relationships with health centre staff; (ii) the connecting role of community health workers; and (iii) a strong sense of community. Factors identified as increasing vaccine hesitancy (e.g. service accessibility and inadequate follow-up) differed between service providers and caregivers and between settings. The conceptual model could be used to explain drivers of the recent measles outbreak and to guide interventions designed to increase vaccine uptake. CONCLUSION: The application of behavioural frameworks and systems thinking revealed vaccine hesitancy mechanisms in Rwandan communities that demonstrate the interrelationship between immunization services and caregivers' vaccination behaviour. Confidence-building social structures and context-dependent challenges that affect vaccine uptake were also identified.

Insights Gained From a Re-analysis of Five Improvement Cases in Healthcare Integrating System Dynamics Into Action Research.

BACKGROUND: Healthcare is complex with multi-professional staff and a variety of patient care pathways. Time pressure and minimal margins for errors, as well as tension between hierarchical power and the power of the professions, make it challenging to implement new policies or procedures. This paper explores five improvement cases in healthcare integrating system dynamics (SD) into action research (AR), aiming to identify methodological aspects of how this integration supported multi-professional groups to discover workable solutions to work-related challenges. METHODS: This re-analysis was conducted by a multi-disciplinary research group using an iterative abductive approach applying qualitative analysis to structure and understand the empirical material. Frameworks for consultancy assignments/client projects were used to identify case project stages (workflow steps) and socio-analytical questions were used to bridge between the AR and SD perspectives. RESULTS: All studied cases began with an extensive AR-inspired inventory of problems/objectives and ended with an SD-facilitated experimental phase where mutually agreed solutions were tested in silico. Time was primarily divided between facilitated group discussions during meetings and modelling work between meetings. Work principles ensured that the voice of each participant was heard, inspired engagement, interaction, and exploratory mutual learning activities. There was an overall pattern of two major divergent and convergent phases, as each group moved towards a mutually developed point of reference for their problem/objective and solution, a case-specific multi-professional knowledge repository. CONCLUSION: By integrating SD into AR, more favourable outcomes for the client organization may be achieved than when applying either approach in isolation. We found that SD provided a platform that facilitated experiential learning in the AR process. The identified results were calibrated to local needs and circumstances, and compared to traditional top-down implementation for change processes, improved the likelihood of sustained actualisation.