Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa
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...
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Gespeichert in:
| Autor*in: |
Kabudula, Chodziwadziwa W [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Anmerkung: |
© Kabudula et al.; licensee BioMed Central Ltd. 2014 |
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| Übergeordnetes Werk: |
Enthalten in: Population health metrics - London : BioMed Central, 2003, 12(2014), 1 vom: 30. Aug. |
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| Übergeordnetes Werk: |
volume:12 ; year:2014 ; number:1 ; day:30 ; month:08 |
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| DOI / URN: |
10.1186/s12963-014-0023-z |
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| Katalog-ID: |
SPR02889782X |
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| 245 | 1 | 0 | |a Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa |
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| 520 | |a 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. | ||
| 650 | 4 | |a Health and demographic surveillance system (HDSS) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Agincourt HDSS |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Record linkage |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Civil registration system |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Death registration |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a South Africa |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Mortality |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Joubert, Jan D |4 aut | |
| 700 | 1 | |a Tuoane-Nkhasi, Maletela |4 aut | |
| 700 | 1 | |a Kahn, Kathleen |4 aut | |
| 700 | 1 | |a Rao, Chalapati |4 aut | |
| 700 | 1 | |a Gmez-Oliv, Francesc Xavier |4 aut | |
| 700 | 1 | |a Mee, Paul |4 aut | |
| 700 | 1 | |a Tollman, Stephen |4 aut | |
| 700 | 1 | |a Lopez, Alan D |4 aut | |
| 700 | 1 | |a Vos, Theo |4 aut | |
| 700 | 1 | |a Bradshaw, Debbie |4 aut | |
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10.1186/s12963-014-0023-z doi (DE-627)SPR02889782X (SPR)s12963-014-0023-z-e DE-627 ger DE-627 rakwb eng Kabudula, Chodziwadziwa W verfasserin aut Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kabudula et al.; licensee BioMed Central Ltd. 2014 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. Health and demographic surveillance system (HDSS) (dpeaa)DE-He213 Agincourt HDSS (dpeaa)DE-He213 Record linkage (dpeaa)DE-He213 Civil registration system (dpeaa)DE-He213 Death registration (dpeaa)DE-He213 South Africa (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Joubert, Jan D aut Tuoane-Nkhasi, Maletela aut Kahn, Kathleen aut Rao, Chalapati aut Gmez-Oliv, Francesc Xavier aut Mee, Paul aut Tollman, Stephen aut Lopez, Alan D aut Vos, Theo aut Bradshaw, Debbie aut Enthalten in Population health metrics London : BioMed Central, 2003 12(2014), 1 vom: 30. Aug. (DE-627)374139911 (DE-600)2127230-X 1478-7954 nnns volume:12 year:2014 number:1 day:30 month:08 https://dx.doi.org/10.1186/s12963-014-0023-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 30 08 |
| spelling |
10.1186/s12963-014-0023-z doi (DE-627)SPR02889782X (SPR)s12963-014-0023-z-e DE-627 ger DE-627 rakwb eng Kabudula, Chodziwadziwa W verfasserin aut Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kabudula et al.; licensee BioMed Central Ltd. 2014 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. Health and demographic surveillance system (HDSS) (dpeaa)DE-He213 Agincourt HDSS (dpeaa)DE-He213 Record linkage (dpeaa)DE-He213 Civil registration system (dpeaa)DE-He213 Death registration (dpeaa)DE-He213 South Africa (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Joubert, Jan D aut Tuoane-Nkhasi, Maletela aut Kahn, Kathleen aut Rao, Chalapati aut Gmez-Oliv, Francesc Xavier aut Mee, Paul aut Tollman, Stephen aut Lopez, Alan D aut Vos, Theo aut Bradshaw, Debbie aut Enthalten in Population health metrics London : BioMed Central, 2003 12(2014), 1 vom: 30. Aug. (DE-627)374139911 (DE-600)2127230-X 1478-7954 nnns volume:12 year:2014 number:1 day:30 month:08 https://dx.doi.org/10.1186/s12963-014-0023-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 30 08 |
| allfields_unstemmed |
10.1186/s12963-014-0023-z doi (DE-627)SPR02889782X (SPR)s12963-014-0023-z-e DE-627 ger DE-627 rakwb eng Kabudula, Chodziwadziwa W verfasserin aut Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kabudula et al.; licensee BioMed Central Ltd. 2014 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. Health and demographic surveillance system (HDSS) (dpeaa)DE-He213 Agincourt HDSS (dpeaa)DE-He213 Record linkage (dpeaa)DE-He213 Civil registration system (dpeaa)DE-He213 Death registration (dpeaa)DE-He213 South Africa (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Joubert, Jan D aut Tuoane-Nkhasi, Maletela aut Kahn, Kathleen aut Rao, Chalapati aut Gmez-Oliv, Francesc Xavier aut Mee, Paul aut Tollman, Stephen aut Lopez, Alan D aut Vos, Theo aut Bradshaw, Debbie aut Enthalten in Population health metrics London : BioMed Central, 2003 12(2014), 1 vom: 30. Aug. (DE-627)374139911 (DE-600)2127230-X 1478-7954 nnns volume:12 year:2014 number:1 day:30 month:08 https://dx.doi.org/10.1186/s12963-014-0023-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 30 08 |
| allfieldsGer |
10.1186/s12963-014-0023-z doi (DE-627)SPR02889782X (SPR)s12963-014-0023-z-e DE-627 ger DE-627 rakwb eng Kabudula, Chodziwadziwa W verfasserin aut Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kabudula et al.; licensee BioMed Central Ltd. 2014 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. Health and demographic surveillance system (HDSS) (dpeaa)DE-He213 Agincourt HDSS (dpeaa)DE-He213 Record linkage (dpeaa)DE-He213 Civil registration system (dpeaa)DE-He213 Death registration (dpeaa)DE-He213 South Africa (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Joubert, Jan D aut Tuoane-Nkhasi, Maletela aut Kahn, Kathleen aut Rao, Chalapati aut Gmez-Oliv, Francesc Xavier aut Mee, Paul aut Tollman, Stephen aut Lopez, Alan D aut Vos, Theo aut Bradshaw, Debbie aut Enthalten in Population health metrics London : BioMed Central, 2003 12(2014), 1 vom: 30. Aug. (DE-627)374139911 (DE-600)2127230-X 1478-7954 nnns volume:12 year:2014 number:1 day:30 month:08 https://dx.doi.org/10.1186/s12963-014-0023-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 30 08 |
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10.1186/s12963-014-0023-z doi (DE-627)SPR02889782X (SPR)s12963-014-0023-z-e DE-627 ger DE-627 rakwb eng Kabudula, Chodziwadziwa W verfasserin aut Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kabudula et al.; licensee BioMed Central Ltd. 2014 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. Health and demographic surveillance system (HDSS) (dpeaa)DE-He213 Agincourt HDSS (dpeaa)DE-He213 Record linkage (dpeaa)DE-He213 Civil registration system (dpeaa)DE-He213 Death registration (dpeaa)DE-He213 South Africa (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Joubert, Jan D aut Tuoane-Nkhasi, Maletela aut Kahn, Kathleen aut Rao, Chalapati aut Gmez-Oliv, Francesc Xavier aut Mee, Paul aut Tollman, Stephen aut Lopez, Alan D aut Vos, Theo aut Bradshaw, Debbie aut Enthalten in Population health metrics London : BioMed Central, 2003 12(2014), 1 vom: 30. Aug. (DE-627)374139911 (DE-600)2127230-X 1478-7954 nnns volume:12 year:2014 number:1 day:30 month:08 https://dx.doi.org/10.1186/s12963-014-0023-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 30 08 |
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Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa |
| 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. © Kabudula et al.; licensee BioMed Central Ltd. 2014 |
| abstractGer |
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. © Kabudula et al.; licensee BioMed Central Ltd. 2014 |
| abstract_unstemmed |
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. © Kabudula et al.; licensee BioMed Central Ltd. 2014 |
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| title_short |
Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa |
| url |
https://dx.doi.org/10.1186/s12963-014-0023-z |
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| author2 |
Joubert, Jan D Tuoane-Nkhasi, Maletela Kahn, Kathleen Rao, Chalapati Gmez-Oliv, Francesc Xavier Mee, Paul Tollman, Stephen Lopez, Alan D Vos, Theo Bradshaw, Debbie |
| author2Str |
Joubert, Jan D Tuoane-Nkhasi, Maletela Kahn, Kathleen Rao, Chalapati Gmez-Oliv, Francesc Xavier Mee, Paul Tollman, Stephen Lopez, Alan D Vos, Theo Bradshaw, Debbie |
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