Abstract
AbstractThe Network for Improving Quality of Care for Maternal, Newborn and Child Health (QCN) aims to work through learning, action, leadership and accountability. We aimed to evaluate the effectiveness of QCN in these four areas at the global level and in four QCN countries: Bangladesh, Ethiopia, Malawi and Uganda.This mixed method evaluation comprised 2-4 iterative rounds of data collection between 2019-2022, involving stakeholder interviews, hospital observations, QCN members survey, and document review. Qualitative data was analysed using a coding framework developed from underlying theories on network effectiveness, behaviour change, and QCN proposed theory of change. Survey data capturing respondents’ perception of QCN was analysed with descriptive statistics.The QCN global level, led by the WHO secretariat, was effective in bringing together network countries’ governments and global actors via providing online and in-person platforms for communication and learning. In-country, various interventions were delivered in ‘learning districts’, however often separately by different partners in different locations, and disrupted by the pandemic. Governance structures for quality of care were set-up, some preceding QCN, and were found to be stronger and better (though often externally) resourced at national than local levels. Awareness of operational plans and network activities was lower at local than national levels but increased from 2019 to 2022. Capacity building efforts were implemented – yet often dependent on implementing partners and donors. QCN stakeholders agreed 15 core monitoring indicators though data collection was challenging, especially for indicators requiring new or parallel systems including those on experience of care. Accountability through community engagement, scorecards, and ombudsmen was encouraged but these initiatives remained nascent in 2022.Global and national leadership elements of QCN have been most effective to date, with action, learning and accountability more challenging, partner or donor dependent, remaining to be scaled-up, and pandemic-disrupted.
Publisher
Cold Spring Harbor Laboratory
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