How can we improve the evidence base for the treatment and care for patients with congenital heart disease?

Gaining evidence-based treatment and management advice for the growing population of patients with congenital heart disease (CHD) without prospective randomized controlled trials. Using population-based data, patients with CHD can be allocated to different groups according to the presence or absence of hypothesized risk factors, treatments, or care models (‘natural randomization’), and outcome can be comparatively analysed depending on group allocation over a long follow-up period. Such research can generate the hypothesis for further research that uses multicentre and multimodality data, including clinical, imaging, and genome and exome data collected in a large register for CHD. The data depth from such a data repository allows for research into treatment effects on specific and well-characterized subgroups of CHD and also on the mechanisms leading to adverse outcomes. The combination of both methods can help to strengthen the evidence base for the treatment and care for patients with CHD, hopefully resulting in further reduction of mortality and morbidity.