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.
Highlights
Congenital abnormalities are defined as malformations of organs or body parts during development in utero, present at birth and are of prenatal origin[1,2]
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. This is the first Minimum Data Set for a congenital abnormality surveillance programme in an African nation identified in the literature
The included datasets included the tools from EUROCAT8 and the WHO2 which are the best described guidance on surveillance programmes
Summary
Congenital abnormalities are defined as malformations of organs or body parts during development in utero, present at birth and are of prenatal origin[1,2]. Approximately 300,000 newborns die within four-weeks of birth, worldwide, due to congenital anomalies, representing approximately 11% of neonatal deaths[4]. In Rwanda, data monitoring is already being undertaken via the Integrated Health Management Information System (HMIS)[6] This is a nationwide data-surveillance programme, with health facilities reporting the total number of births with congenital anomalies, but no detail of individual cases. 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. 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. We have added some text to the discussion regarding the lack of description of how the previous studies identified their items
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