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Are women with major depression in pregnancy identifiable in population health data?
BACKGROUND: Although record linkage of routinely collected health datasets is a valuable research resource, most datasets are established for administrative purposes and not for health outcomes research. In order for meaningful results to be extrapolated to specific populations, the limitations of t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3602106/ https://www.ncbi.nlm.nih.gov/pubmed/23497210 http://dx.doi.org/10.1186/1471-2393-13-63 |
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author | Colvin, Lyn Slack-Smith, Linda Stanley, Fiona J Bower, Carol |
author_facet | Colvin, Lyn Slack-Smith, Linda Stanley, Fiona J Bower, Carol |
author_sort | Colvin, Lyn |
collection | PubMed |
description | BACKGROUND: Although record linkage of routinely collected health datasets is a valuable research resource, most datasets are established for administrative purposes and not for health outcomes research. In order for meaningful results to be extrapolated to specific populations, the limitations of the data and linkage methodology need to be investigated and clarified. It is the objective of this study to investigate the differences in ascertainment which may arise between a hospital admission dataset and a dispensing claims dataset, using major depression in pregnancy as an example. The safe use of antidepressants in pregnancy is an ongoing issue for clinicians with around 10% of pregnant women suffer from depression. As the birth admission will be the first admission to hospital during their pregnancy for most women, their use of antidepressants, or their depressive condition, may not be revealed to the attending hospital clinicians. This may result in adverse outcomes for the mother and infant. METHODS: Population-based de-identified data were provided from the Western Australian Data Linkage System linking the administrative health records of women with a delivery to related records from the Midwives’ Notification System, the Hospital Morbidity Data System and the national Pharmaceutical Benefits Scheme dataset. The women with depression during their pregnancy were ascertained in two ways: women with dispensing records relating to dispensed antidepressant medicines with an WHO ATC code to the 3rd level, pharmacological subgroup, ‘N06A Antidepressants’; and, women with any hospital admission during pregnancy, including the birth admission, if a comorbidity was recorded relating to depression. RESULTS: From 2002 to 2005, there were 96698 births in WA. At least one antidepressant was dispensed to 4485 (4.6%) pregnant women. There were 3010 (3.1%) women with a comorbidity related to depression recorded on their delivery admission, or other admission to hospital during pregnancy. There were a total of 7495 pregnancies identified by either set of records. Using data linkage, we determined that these records represented 6596 individual pregnancies. Only 899 pregnancies were found in both groups (13.6% of all cases). 80% of women dispensed an antidepressant did not have depression recorded as a comorbidity on their hospital records. A simple capture-recapture calculation suggests the prevalence of depression in this population of pregnant women to be around 16%. CONCLUSION: No single data source is likely to provide a complete health profile for an individual. For women with depression in pregnancy and dispensed antidepressants, the hospital admission data do not adequately capture all cases. |
format | Online Article Text |
id | pubmed-3602106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36021062013-03-20 Are women with major depression in pregnancy identifiable in population health data? Colvin, Lyn Slack-Smith, Linda Stanley, Fiona J Bower, Carol BMC Pregnancy Childbirth Research Article BACKGROUND: Although record linkage of routinely collected health datasets is a valuable research resource, most datasets are established for administrative purposes and not for health outcomes research. In order for meaningful results to be extrapolated to specific populations, the limitations of the data and linkage methodology need to be investigated and clarified. It is the objective of this study to investigate the differences in ascertainment which may arise between a hospital admission dataset and a dispensing claims dataset, using major depression in pregnancy as an example. The safe use of antidepressants in pregnancy is an ongoing issue for clinicians with around 10% of pregnant women suffer from depression. As the birth admission will be the first admission to hospital during their pregnancy for most women, their use of antidepressants, or their depressive condition, may not be revealed to the attending hospital clinicians. This may result in adverse outcomes for the mother and infant. METHODS: Population-based de-identified data were provided from the Western Australian Data Linkage System linking the administrative health records of women with a delivery to related records from the Midwives’ Notification System, the Hospital Morbidity Data System and the national Pharmaceutical Benefits Scheme dataset. The women with depression during their pregnancy were ascertained in two ways: women with dispensing records relating to dispensed antidepressant medicines with an WHO ATC code to the 3rd level, pharmacological subgroup, ‘N06A Antidepressants’; and, women with any hospital admission during pregnancy, including the birth admission, if a comorbidity was recorded relating to depression. RESULTS: From 2002 to 2005, there were 96698 births in WA. At least one antidepressant was dispensed to 4485 (4.6%) pregnant women. There were 3010 (3.1%) women with a comorbidity related to depression recorded on their delivery admission, or other admission to hospital during pregnancy. There were a total of 7495 pregnancies identified by either set of records. Using data linkage, we determined that these records represented 6596 individual pregnancies. Only 899 pregnancies were found in both groups (13.6% of all cases). 80% of women dispensed an antidepressant did not have depression recorded as a comorbidity on their hospital records. A simple capture-recapture calculation suggests the prevalence of depression in this population of pregnant women to be around 16%. CONCLUSION: No single data source is likely to provide a complete health profile for an individual. For women with depression in pregnancy and dispensed antidepressants, the hospital admission data do not adequately capture all cases. BioMed Central 2013-03-12 /pmc/articles/PMC3602106/ /pubmed/23497210 http://dx.doi.org/10.1186/1471-2393-13-63 Text en Copyright ©2013 Colvin 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 Colvin, Lyn Slack-Smith, Linda Stanley, Fiona J Bower, Carol Are women with major depression in pregnancy identifiable in population health data? |
title | Are women with major depression in pregnancy identifiable in population health data? |
title_full | Are women with major depression in pregnancy identifiable in population health data? |
title_fullStr | Are women with major depression in pregnancy identifiable in population health data? |
title_full_unstemmed | Are women with major depression in pregnancy identifiable in population health data? |
title_short | Are women with major depression in pregnancy identifiable in population health data? |
title_sort | are women with major depression in pregnancy identifiable in population health data? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3602106/ https://www.ncbi.nlm.nih.gov/pubmed/23497210 http://dx.doi.org/10.1186/1471-2393-13-63 |
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