Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa

Chodziwadziwa W. Kabudula*, Jané D. Joubert, Maletela Tuoane-Nkhasi, Kathleen Kahn, Chalapati Rao, Francesc X. Gómez-Olivé, Paul Mee, Stephen Tollman, Alan D. Lopez, Theo Vos, Debbie Bradshaw

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Background: Health and Demographic Surveillance Systems (HDSS) collect independent mortality data that could be used for assessing the quality of mortality data in national civil registration (CR) systems in low- and middle-income countries. However, the use of HDSS data for such purposes depends on the quality of record linkage between the two data sources. We describe and evaluate the quality of record linkage between HDSS and CR mortality data in South Africa with HDSS data from Agincourt HDSS.Methods: We applied deterministic and probabilistic record linkage approaches to mortality records from 2006 to 2009 from the Agincourt HDSS and those in the CR system. Quality of the matches generated by the probabilistic approach was evaluated using sensitivity and positive predictive value (PPV) calculated from a subset of records that were linked using national identity number. Matched and unmatched records from the Agincourt HDSS were compared to identify characteristics associated with successful matching. In addition, the distribution of background characteristics in all deaths that occurred in 2009 and those linked to CR records was compared to assess systematic bias in the resulting record-linked dataset in the latest time period.Results: Deterministic and probabilistic record linkage approaches combined linked a total of 2264 out of 3726 (60.8%) mortality records from the Agincourt HDSS to those in the CR system. Probabilistic approaches independently linked 1969 (87.0%) of the linked records. In a subset of 708 records that were linked using national identity number, the probabilistic approaches yielded sensitivity of 90.0% and PPV of 98.5%. Records belonging to more vulnerable people, including poorer persons, young children, and non-South Africans were less likely to be matched. Nevertheless, distribution of most background characteristics was similar between all Agincourt HDSS deaths and those matched to CR records in the latest time period.Conclusion: This study shows that record linkage of mortality data from HDSS and CR systems is possible and can be useful in South Africa. The study identifies predictors for death registration and data items and registration system characteristics that could be improved to achieve more optimal future matching possibilities.

Original languageEnglish
Article number23
JournalPopulation Health Metrics
Volume12
Issue number1
DOIs
Publication statusPublished - 30 Aug 2014
Externally publishedYes

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