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Implementing structured follow-up of neonatal and paediatric patients: an evaluation of three university hospital
Véronique Bos1, Daniëlle Roorda2, Eleonore de Sonnaville3
1Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, Netherlands. v.l.bos@amsterdamumc.nl.
Insights
Implementing structured long-term follow-up programs for neonatal and paediatric patients improves care. Standardized measurements are crucial for effective data collection and multidisciplinary team integration in clinical practice.
Area of Science:
- Neonatal and Paediatric Clinical Practice
- Healthcare Management
- Patient Outcomes Research
Background:
- Limited knowledge exists on long-term patient outcomes and optimal follow-up care in complex neonatal and paediatric settings.
- Emma Children's Hospital implemented the 'Follow Me' program to gain insights into long-term outcomes and foster a learning cycle for clinical practice improvement.
- Three departments initiated multidisciplinary approaches to long-term follow-up, incorporating standardized check-ups based on medical, developmental, and psychosocial indicators.
Purpose of the Study:
- To evaluate the implementation of three structured long-term follow-up programs at Emma Children's Hospital.
- To compare predefined procedures (work-as-imagined) with actual implementation (work-as-done) of these follow-up programs.
- To identify areas for improvement in clinical practice and patient follow-up care.
Main Methods:
- The study was conducted in 2019-2020 in outpatient settings of neonatal intensive care, paediatric intensive care, and paediatric surgery departments.
- The Functional Resonance Analysis Method (FRAM) was employed, utilizing documentary analysis, semi-structured interviews, observations, and feedback sessions.
- The focus was on the organizational structure and practical implementation of the follow-up care programs.
Main Results:
- One work-as-imagined model and four work-as-done models were identified, highlighting variations in practical implementation.
- Extensive data collection on medical, developmental, and psychosocial indicators was observed, but process indicators for program effectiveness were lacking.
- Diverse role allocation within multidisciplinary teams and misalignments in long-term outcome monitoring were noted across departments.
Conclusions:
- Structured long-term follow-up can enhance clinical practice and patient care, provided standardized measurements are implemented.
- Key lessons learned include addressing data fragmentation, embracing diverse multidisciplinary team structures, and incorporating timely, actionable indicators for program effectiveness.
- Standardization of measurements is a critical precondition for leveraging long-term follow-up insights to improve care.
Background:
In 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).
Methods:
This 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.
Results:
One 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.
Conclusion:
Implementing 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.