Relatively little is known about how Networks such as QCN operate in low- and middle-income countries. To understand how QCN operated, the IDEAS project joined a UCL-led evaluation of the Network in Bangladesh, Malawi and Uganda, adding in the experience of Ethiopia. Research questions included:
- Which capacities were available to enable Network functioning?
- Which actions were taken to sustain QCN beyond the initial implementation period?
- What influenced the quality of QCN data in health facilities?
Capacity for Network functioning
Individual, organizational and system-level capacities all played an important role in shaping implementation success in network countries, and these levels were inter-linked. Across all levels, actions that enabled leadership, motivated and trained staff, and created a positive culture of data use were critical – from the policy making arena to the day-to-day frontline practice. Some characteristics of QCN actively supported these levels, for example shared learning forums for continuous learning, a focus on data and tracking progress, and emphasising the importance of coordinated efforts towards a common goal. However, inadequate health system financing and capacity hampered network functioning, especially in the face of external shocks.
Actions taken to sustain QCN
Although vulnerabilities were observed, there was evidence that actions were taken to institutionalize QCN within country health systems, to motivate micro-level actors, plan opportunities for reflection and adaptation from the outset, and to support strong government ownership. But financial uncertainty was not pro-actively managed, community ownership not always fostered, and actions were least strong at the sub-national level.
Overall, evidence suggested that the QCN model would not be sustained in its original format, largely because of financial vulnerability and insufficient time to embed the innovation at the sub-national level. However, the efforts made to institutionalize QCN in existing systems meant that some characteristics may be carried forward within broader government quality improvement initiatives.
Quality of QCN data
QCN placed considerable emphasis on the importance of good quality data for learning and tracking progress. This emphasis had a positive effect on perceptions about data and data use for decision-making, with actors across the health system describing the potential power of data. However, in reality there were only limited improvements in the quality of data being generated. New data points were introduced to registers but not all data points were integrated with the routine health information system, causing some duplication of effort. Facilities also continued to lack the skills or resources needed to routinely record accurate data.