Background
Neonatal mortality accounts for the most significant and today increasing proportion of
under-5 mortality, especially in sub-Saharan Africa. The neonatal population is a sharp
target for intervention for these 2.5 million annual deaths. The limited availability of
quality data on morbidities leading up to this mortality hampers the development and
follow-up of effective interventions. For leverage, undoubtedly more detailed and
standardized data adapted to low and middle-income countries (LMICs) is urgently
needed.
Methods
Drawing on existing databases such as the Swiss Neonatal Network and Vermont Oxford
Network, 267 clinical, administrative, and structural variables of neonatal health and
healthcare services were selected and submitted for ranking to 42 experts through two
Delphi rounds. An empirically limited number of variables with the highest ranking for
availability and relevance in low and middle-income countries were field-tested in three
centres in Burkina Faso during one year for improvement and practicality.
Results
We report the database development process according to the Standards for Quality
Improvement Reporting Excellence (SQUIRE 2.0) recommendations. The final dataset is
composed of 73 clinical and 6 administrative patient variables, and 21 structural
healthcare center variables. Two-thirds of clinical variables maintain matching
definitions with high-income countries.
Conclusions
The developed minimal neonatal dataset is standardized and field-tested for relevance
and availability in LMICs allowing south-south and some south-north cross-comparison