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

Chalapati Rao,Maletela Tuoane-Nkhasi,Paul Mee,Debbie Bradshaw,Theo Vos,Francesc Xavier Gmez-Oliv,Kathleen Kahn,Chodziwadziwa W Kabudula,Stephen Tollman,Alan D Lopez,Jan D Joubert

doi:10.1186/s12963-014-0023-z

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.

Highlights

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
The matched record pairs comprised of 2,039 record pairs that were obtained by linking Agincourt HDSS records to records in the trimmed CR dataset, and 225 record pairs obtained by linking the remaining Agincourt HDSS records with records in the full CR dataset
Deterministic and probabilistic record linkage approaches, respectively and independently, produced 1,394 and 1,969 of the record pairs that were obtained by linking Agincourt HDSS records to records in the trimmed CR dataset, and 1,324 (95.0%) of the records that were matched using the deterministic approach were matched using the probabilistic approach

Summary

Introduction

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. We describe and evaluate the quality of record linkage between HDSS and CR mortality data in South Africa with HDSS data from Agincourt HDSS. The country has adopted the Africa Programme on Accelerated Improvement of Civil Registration and Vital Statistics (APAI-CRVS) [6], building on the focused initiatives by Statistics South Africa, the Department of Health, and a group of researchers since the 1990s to improve and strengthen its CR system and cause of death information [10,11,12]. There is a continuous need for assessing the quality of CR mortality data to ascertain the impact of these initiatives and identify remaining gaps and options for further improvement

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Conclusion