Developing a Minimum Data Set for a congenital abnormalities surveillance programme in Rwanda – a modified e-Delphi consensus study

Abstract

Background: In 2015 it was reported that approximately 300,000 newborns die within four weeks of birth every year, worldwide, due to congenital anomalies. This represents approximately 11% of neonatal deaths. This has led scientists, clinicians and public health authorities to establish congenital abnormality registries (CARs). There is currently no CAR in Rwanda. In establishing such a registry, it was determined that the first step was to identify the Minimum Data Set (MDS) of items/variables and outcomes for the registry to ensure that the final results are meaningful and employable. This study aimed to use Delphi consensus methods to identify a methodologically robust MDS for a congenital abnormality surveillance programme in Rwanda. Methods: A three-round, modified Delphi study was undertaken between April and June 2017. Round 1 was a literature and internet search followed by an open and closed question round with experts in Rounds 2 and 3, respectively. Results: An initial draft MDS of 134 items was created from a review of 15 African studies and 14 international repository tools including the European Surveillance of Congenital Anomalies and the World Health Organization surveillance guidance. In total, 36 and 34 eligible participants were included in Rounds 2 and 3, respectively. A total of 32 new items were added by participants in Round 2. 103 items met the pre-defined consensus criteria and made up the final MDS in Round 3. Conclusions: This is the first Minimum Data Set for a congenital abnormality surveillance programme in an African nation identified in the literature. The next stage is to field-test the surveillance programme using passive case-finding in teaching hospitals in Rwanda.