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

Kabudula, Chodziwadziwa W., Joubert, Jane D., Tuoane-Nkhasi, Maletela, Kahn, Kathleen, Rao, Chalapati, Gomez-Olive, Francesc Xavier, Mee, Paul, Tollman, Stephen, Lopez, Alan D., Vos, Theo and Bradshaw, Debbie (2014) Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa. Population Health Metrics, 12 1: 23.1-23.11. doi:10.1186/s12963-014-0023-z


Author Kabudula, Chodziwadziwa W.
Joubert, Jane D.
Tuoane-Nkhasi, Maletela
Kahn, Kathleen
Rao, Chalapati
Gomez-Olive, Francesc Xavier
Mee, Paul
Tollman, Stephen
Lopez, Alan D.
Vos, Theo
Bradshaw, Debbie
Title Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa
Journal name Population Health Metrics   Check publisher's open access policy
ISSN 1478-7954
Publication date 2014-08
Sub-type Article (original research)
DOI 10.1186/s12963-014-0023-z
Open Access Status DOI
Volume 12
Issue 1
Start page 23.1
End page 23.11
Total pages 11
Place of publication London, United Kingdom
Publisher BioMed Central
Collection year 2015
Language eng
Formatted 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.
Keyword Health and demographic surveillance system (HDSS)
Agincourt HDSS
Record linkage
Civil registration system
Death registration
South Africa
Mortality
Vital-Statistics
Agincourt Health
Global Burden
Death
Disease
Care
Epidemiology
Identifiers
Population
Validation
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Public Health Publications
 
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