Lessons from using the Normalisation Process Theory to understand adherence to guidance on MgSO in preterm labour.

BACKGROUND

The administration of magnesium sulphate (MgSO) in preterm labour is an evidence-based intervention recommended by the United Kingdom's National Institute for Health and Care Excellence (NICE) to prevent neurological damage to the infant. However, uptake varies across UK maternity units. We used findings from three studies in England, Scotland and Wales investigating implementation of guidance on MgSO as neuroprotectant in preterm-labour to understand how knowledge mobilisation can drive scaling and spread of improvement.

METHODS

Remote semi-structured interviews were carried out as part of an evaluation of (1) the PReCePT (Preventing Cerebral Palsy in Pre-Term Labour) National Programme, and (2) the PReCePT cRCT study, and as part of a qualitative study investigating MgSO guidance implementation in Scotland and Wales. Normalisation Process Theory informed data collection and analysis. Data were analysed using the framework method.

RESULTS

Interviews with 86 strategic and clinical leads and implementers from the three nations suggested that despite evidence being necessary and important for policy decision-making and clinical buy-in, improvement interventions were motivated by audit data and benchmarking. Scaling of improvement was driven by knowledge sharing, diffusion of innovation, and capacity building through relational structures (e.g. networks, communities) spanning the perinatal ecosystem. Local champions operating in multiple communities and networks as boundary-spanners connected national and regional leadership, patient group representatives, implementers i.e. clinical leads and champions, and perinatal clinical teams to enable knowledge mobilisation. Their work relied on backfill funding and protected time, and social-cognitive and social-structural resources in their settings. Sense-making, cognitive participation, collective action and reflexive monitoring work took place iteratively and dynamically within and across these structures on each level of the system.

CONCLUSIONS

QI interventions driven by knowledge mobilisation can drive scaling and spreading of improvement, but require knowledge sharing and an infrastructure within the system to support improvement capacity building. Strong leadership with the ability to address power imbalances between co-actors, and secure protected funding for local champions is also required.