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Investigating linkage rates among probabilistically linked birth and hospitalization records

BACKGROUND: With the increasing use of probabilistically linked administrative data in health research, it is important to understand whether systematic differences occur between the populations with linked and unlinked records. While probabilistic linkage involves combining records for individuals,...

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Autores principales: Bentley, Jason P, Ford, Jane B, Taylor, Lee K, Irvine, Katie A, Roberts, Christine L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3533905/
https://www.ncbi.nlm.nih.gov/pubmed/23009079
http://dx.doi.org/10.1186/1471-2288-12-149
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author Bentley, Jason P
Ford, Jane B
Taylor, Lee K
Irvine, Katie A
Roberts, Christine L
author_facet Bentley, Jason P
Ford, Jane B
Taylor, Lee K
Irvine, Katie A
Roberts, Christine L
author_sort Bentley, Jason P
collection PubMed
description BACKGROUND: With the increasing use of probabilistically linked administrative data in health research, it is important to understand whether systematic differences occur between the populations with linked and unlinked records. While probabilistic linkage involves combining records for individuals, population perinatal health research requires a combination of information from both the mother and her infant(s). The aims of this study were to (i) describe probabilistic linkage for perinatal records in New South Wales (NSW) Australia, (ii) determine linkage proportions for these perinatal records, and (iii) assess records with linked mother and infant hospital-birth record, and unlinked records for systematic differences. METHODS: This is a population-based study of probabilistically linked statutory birth and hospital records from New South Wales, Australia, 2001-2008. Linkage groups were created where the birth record had complete linkage with hospital admission records for both the mother and infant(s), partial linkage (the mother only or the infant(s) only) or neither. Unlinked hospital records for mothers and infants were also examined. Rates of linkage as a percentage of birth records and descriptive statistics for maternal and infant characteristics by linkage groups were determined. RESULTS: Complete linkage (mother hospital record – birth record – infant hospital record) was available for 95.9% of birth records, partial linkage for 3.6%, and 0.5% with no linked hospital records (unlinked). Among live born singletons (complete linkage = 96.5%) the mothers without linked infant records (1.6%) had slightly higher proportions of young, non-Australian born, socially disadvantaged women with adverse pregnancy outcomes. The unlinked birth records (0.4%) had slightly higher proportions of nulliparous, older, Australian born women giving birth in private hospitals by caesarean section. Stillbirths had the highest rate of unlinked records (3-4%). CONCLUSIONS: This study shows that probabilistic linkage of perinatal records can achieve high, representative levels of complete linkage. Records for mother’s that did not link to infant records and unlinked records had slightly different characteristics to fully linked records. However, these groups were small and unlikely to bias results and conclusions in a substantive way. Stillbirths present additional challenges to the linkage process due to lower rates of linkage for lower gestational ages, where most stillbirths occur.
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spelling pubmed-35339052013-01-07 Investigating linkage rates among probabilistically linked birth and hospitalization records Bentley, Jason P Ford, Jane B Taylor, Lee K Irvine, Katie A Roberts, Christine L BMC Med Res Methodol Research Article BACKGROUND: With the increasing use of probabilistically linked administrative data in health research, it is important to understand whether systematic differences occur between the populations with linked and unlinked records. While probabilistic linkage involves combining records for individuals, population perinatal health research requires a combination of information from both the mother and her infant(s). The aims of this study were to (i) describe probabilistic linkage for perinatal records in New South Wales (NSW) Australia, (ii) determine linkage proportions for these perinatal records, and (iii) assess records with linked mother and infant hospital-birth record, and unlinked records for systematic differences. METHODS: This is a population-based study of probabilistically linked statutory birth and hospital records from New South Wales, Australia, 2001-2008. Linkage groups were created where the birth record had complete linkage with hospital admission records for both the mother and infant(s), partial linkage (the mother only or the infant(s) only) or neither. Unlinked hospital records for mothers and infants were also examined. Rates of linkage as a percentage of birth records and descriptive statistics for maternal and infant characteristics by linkage groups were determined. RESULTS: Complete linkage (mother hospital record – birth record – infant hospital record) was available for 95.9% of birth records, partial linkage for 3.6%, and 0.5% with no linked hospital records (unlinked). Among live born singletons (complete linkage = 96.5%) the mothers without linked infant records (1.6%) had slightly higher proportions of young, non-Australian born, socially disadvantaged women with adverse pregnancy outcomes. The unlinked birth records (0.4%) had slightly higher proportions of nulliparous, older, Australian born women giving birth in private hospitals by caesarean section. Stillbirths had the highest rate of unlinked records (3-4%). CONCLUSIONS: This study shows that probabilistic linkage of perinatal records can achieve high, representative levels of complete linkage. Records for mother’s that did not link to infant records and unlinked records had slightly different characteristics to fully linked records. However, these groups were small and unlikely to bias results and conclusions in a substantive way. Stillbirths present additional challenges to the linkage process due to lower rates of linkage for lower gestational ages, where most stillbirths occur. BioMed Central 2012-09-25 /pmc/articles/PMC3533905/ /pubmed/23009079 http://dx.doi.org/10.1186/1471-2288-12-149 Text en Copyright ©2012 Bentley et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Bentley, Jason P
Ford, Jane B
Taylor, Lee K
Irvine, Katie A
Roberts, Christine L
Investigating linkage rates among probabilistically linked birth and hospitalization records
title Investigating linkage rates among probabilistically linked birth and hospitalization records
title_full Investigating linkage rates among probabilistically linked birth and hospitalization records
title_fullStr Investigating linkage rates among probabilistically linked birth and hospitalization records
title_full_unstemmed Investigating linkage rates among probabilistically linked birth and hospitalization records
title_short Investigating linkage rates among probabilistically linked birth and hospitalization records
title_sort investigating linkage rates among probabilistically linked birth and hospitalization records
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3533905/
https://www.ncbi.nlm.nih.gov/pubmed/23009079
http://dx.doi.org/10.1186/1471-2288-12-149
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