Record linkage with antenatal care clinics in western Kenya improves pregnancy data
A new data linkage study has revealed underreporting of stillbirths in a Health and Demographic Surveillance Systems (HDSS) in western Kenya, and substantial potential for downward bias in estimates of perinatal and neonatal mortality.
In a newly published article in the International Journal of Population Data Science (IJPDS), researchers leveraged record linkage with antenatal care (ANC) clinics to assess the quality and completeness of data collected on pregnancies and their outcomes in a HDSS in Siaya, Kenya. Their comparison with antenatal care clinic records of gestational age also indicated that miscarriages and stillbirths were likely subject to frequent misclassification in the HDSS.
In sub-Saharan Africa, incomplete civil registration and vital statistics systems complicate the monitoring of population health as well as efforts aimed at improving it. Alternative sources of information such as surveys and HDSS have been used to fill data gaps, but these sources are affected by well-documented data quality issues.
Linkage with health facility records is of increasing importance to generating rich primary data on population health throughout sub-Saharan Africa. In the past decade, a number of HDSS have undertaken linkage with health facilities serving the local population. Such data has proved valuable for investigating patterns of healthcare services utilisation, treatment outcomes, and the burden of disease. The applications of record linkage may also be extended to enhance and validate data collected by HDSS, as demonstrated in this unique contribution.
The study’s lead author, Hallie Eilerts-Spinelli, commented on the promise of record linkage for filling data gaps. "Record linkage between HDSS and health facilities is an efficient manner of augmenting population health information in sub-Saharan Africa, and addressing the lack of good quality data on pregnancy and early mortality. Such efforts have the potential to both improve our understanding of population health and our ability to accurately measure it."
You can read the full results of this study here
Hallie Eilerts-Spinelli, Population Studies Group, London School of Hygiene & Tropical Medicine
Eilerts-Spinelli, H., Romero Prieto, J., Ambia, J., Khagayi, S., Kabudula, C., Eaton, J. W. and Reniers, G. (2022) “Evaluating pregnancy reporting in Siaya Health and Demographic Surveillance System through record linkage with ANC clinics”, International Journal of Population Data Science, 7(4). doi: 10.23889/ijpds.v7i4.1762.