Implementing structured follow-up of neonatal and paediatric patients: an evaluation of three university hospital case studies using the functional resonance analysis method.

backgroundIn complex critical neonatal and paediatric clinical practice, little is known about long-term patient outcomes and what follow-up care is most valuable for patients. Emma Children's Hospital, Amsterdam UMC (Netherlands), implemented a follow-up programme called Follow Me for neonatal and paediatric patient groups, to gain more insight into long-term outcomes and to use such outcomes to implement a learning cycle for clinical practice, improve follow-up care and facilitate research. Three departments initiated re-engineering and change processes. Each introduced multidisciplinary approaches to long-term follow-up, including regular standardised check-ups for defined age groups, based on medical indicators, developmental progress, and psychosocial outcomes in patients and their families. This research evaluates the implementation of the three follow-up programmes, comparing predefined procedures (work-as-imagined) with how the programmes were implemented in practice (work-as-done).

methodsThis study was conducted in 2019-2020 in the outpatient settings of the neonatal intensive care, paediatric intensive care and paediatric surgery departments of Emma Children's Hospital. It focused on the organisational structure of the follow-up care. The functional resonance analysis method (FRAM) was applied, using documentary analysis, semi-structured interviews, observations and feedback sessions.

resultsOne work-as-imagined model and four work-as-done models were described. The results showed vast data collection on medical, developmental and psychosocial indicators in all work-as-done models; however, process indicators for programme effectiveness and performance were missing. In practice there was a diverse allocation of roles and responsibilities and their interrelations to create a multidisciplinary team; there was no one-size-fits-all across the different departments. Although control and feedback loops for long-term outcomes were specified with respect to the follow-up groups within the programmes, they were found to overlap and misalign with other internal and external long-term outcome monitoring practices.

conclusionImplementing structured long-term follow-up may provide insights for improving daily practice and follow-up care, with the precondition of standardised measurements. Lessons learned from practice are (1) to address fragmentation in data collection and storage, (2) to incorporate the diverse ways to create a multidisciplinary team in practice, and (3) to include timely actionable indicators on programme effectiveness and performance, alongside medical, developmental and psychosocial indicators.