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Data accuracy in the Ontario birth Registry: a chart re-abstraction study
BACKGROUND: Ontario’s birth Registry (BORN) was established in 2009 to collect, interpret, and share critical data about pregnancy, birth and the early childhood period to facilitate and improve the provision of healthcare. Since the use of routinely-collected health data has been prioritized intern...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935171/ https://www.ncbi.nlm.nih.gov/pubmed/31881960 http://dx.doi.org/10.1186/s12913-019-4825-3 |
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author | Dunn, Sandra Lanes, Andrea Sprague, Ann E. Fell, Deshayne B. Weiss, Deborah Reszel, Jessica Taljaard, Monica Darling, Elizabeth K. Graham, Ian D. Grimshaw, Jeremy M. Harrold, JoAnn Smith, Graeme N. Peterson, Wendy Walker, Mark |
author_facet | Dunn, Sandra Lanes, Andrea Sprague, Ann E. Fell, Deshayne B. Weiss, Deborah Reszel, Jessica Taljaard, Monica Darling, Elizabeth K. Graham, Ian D. Grimshaw, Jeremy M. Harrold, JoAnn Smith, Graeme N. Peterson, Wendy Walker, Mark |
author_sort | Dunn, Sandra |
collection | PubMed |
description | BACKGROUND: Ontario’s birth Registry (BORN) was established in 2009 to collect, interpret, and share critical data about pregnancy, birth and the early childhood period to facilitate and improve the provision of healthcare. Since the use of routinely-collected health data has been prioritized internationally by governments and funding agencies to improve patient care, support health system planning, and facilitate epidemiological surveillance and research, high quality data is essential. The purpose of this study was to verify the accuracy of a selection of data elements that are entered in the Registry. METHODS: Data quality was assessed by comparing data re-abstracted from patient records to data entered into the Ontario birth Registry. A purposive sample of 10 hospitals representative of hospitals in Ontario based on level of care, birth volume and geography was selected and a random sample of 100 linked mother and newborn charts were audited for each site. Data for 29 data elements were compared to the corresponding data entered in the Ontario birth Registry using percent agreement, kappa statistics for categorical data elements and intra-class correlation coefficients (ICCs) for continuous data elements. RESULTS: Agreement ranged from 56.9 to 99.8%, but 76% of the data elements (22 of 29) had greater than 90% agreement. There was almost perfect (kappa 0.81–0.99) or substantial (kappa 0.61–0.80) agreement for 12 of the categorical elements. Six elements showed fair-to-moderate agreement (kappa <0.60). We found moderate-to-excellent agreement for four continuous data elements (ICC >0.50). CONCLUSION: Overall, the data elements we evaluated in the birth Registry were found to have good agreement with data from the patients’ charts. Data elements that showed moderate kappa or low ICC require further investigation. |
format | Online Article Text |
id | pubmed-6935171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69351712019-12-30 Data accuracy in the Ontario birth Registry: a chart re-abstraction study Dunn, Sandra Lanes, Andrea Sprague, Ann E. Fell, Deshayne B. Weiss, Deborah Reszel, Jessica Taljaard, Monica Darling, Elizabeth K. Graham, Ian D. Grimshaw, Jeremy M. Harrold, JoAnn Smith, Graeme N. Peterson, Wendy Walker, Mark BMC Health Serv Res Research Article BACKGROUND: Ontario’s birth Registry (BORN) was established in 2009 to collect, interpret, and share critical data about pregnancy, birth and the early childhood period to facilitate and improve the provision of healthcare. Since the use of routinely-collected health data has been prioritized internationally by governments and funding agencies to improve patient care, support health system planning, and facilitate epidemiological surveillance and research, high quality data is essential. The purpose of this study was to verify the accuracy of a selection of data elements that are entered in the Registry. METHODS: Data quality was assessed by comparing data re-abstracted from patient records to data entered into the Ontario birth Registry. A purposive sample of 10 hospitals representative of hospitals in Ontario based on level of care, birth volume and geography was selected and a random sample of 100 linked mother and newborn charts were audited for each site. Data for 29 data elements were compared to the corresponding data entered in the Ontario birth Registry using percent agreement, kappa statistics for categorical data elements and intra-class correlation coefficients (ICCs) for continuous data elements. RESULTS: Agreement ranged from 56.9 to 99.8%, but 76% of the data elements (22 of 29) had greater than 90% agreement. There was almost perfect (kappa 0.81–0.99) or substantial (kappa 0.61–0.80) agreement for 12 of the categorical elements. Six elements showed fair-to-moderate agreement (kappa <0.60). We found moderate-to-excellent agreement for four continuous data elements (ICC >0.50). CONCLUSION: Overall, the data elements we evaluated in the birth Registry were found to have good agreement with data from the patients’ charts. Data elements that showed moderate kappa or low ICC require further investigation. BioMed Central 2019-12-27 /pmc/articles/PMC6935171/ /pubmed/31881960 http://dx.doi.org/10.1186/s12913-019-4825-3 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Dunn, Sandra Lanes, Andrea Sprague, Ann E. Fell, Deshayne B. Weiss, Deborah Reszel, Jessica Taljaard, Monica Darling, Elizabeth K. Graham, Ian D. Grimshaw, Jeremy M. Harrold, JoAnn Smith, Graeme N. Peterson, Wendy Walker, Mark Data accuracy in the Ontario birth Registry: a chart re-abstraction study |
title | Data accuracy in the Ontario birth Registry: a chart re-abstraction study |
title_full | Data accuracy in the Ontario birth Registry: a chart re-abstraction study |
title_fullStr | Data accuracy in the Ontario birth Registry: a chart re-abstraction study |
title_full_unstemmed | Data accuracy in the Ontario birth Registry: a chart re-abstraction study |
title_short | Data accuracy in the Ontario birth Registry: a chart re-abstraction study |
title_sort | data accuracy in the ontario birth registry: a chart re-abstraction study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935171/ https://www.ncbi.nlm.nih.gov/pubmed/31881960 http://dx.doi.org/10.1186/s12913-019-4825-3 |
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