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

Debbie Bradshaw¹  Theo Vos⁶  Alan D Lopez⁷  Stephen Tollman⁸  Paul Mee²  Francesc Xavier Gómez-Olivé⁴  Chalapati Rao³  Kathleen Kahn⁸  Maletela Tuoane-Nkhasi⁵  Jané D Joubert³  Chodziwadziwa W Kabudula⁴ 

[1]Burden of Disease Research Unit, South African Medical Research Council, Parow Vallei, Western Cape, South Africa

[2]Umeå Centre for Global Health Research, Division of Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden

[3]School of Population Health, The University of Queensland, Herston, Brisbane, Queensland, Australia

[4]MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

[5]Health and Vital Statistics, Statistics South Africa, Pretoria, South Africa

[6]Institute of Health Metrics and Evaluation, University of Washington, Seattle, USA

[7]Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia

[8]INDEPTH Network, Accra, Ghana

关键词: Mortality;    South Africa;    Death registration;    Civil registration system;    Record linkage;    Agincourt HDSS;    Health and demographic surveillance system (HDSS);   

Others  :  1139678
DOI  :  10.1186/s12963-014-0023-z

 received in 2014-04-17, accepted in 2014-08-11,  发布年份 2014

【 摘 要 】

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.

【 授权许可】

   
2014 Kabudula et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

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