Cargando…

Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning

INTRODUCTION: Vital status is of central importance to hospital clinical research. However, hospital information systems record only in-hospital death information. Recently, the French government released a publicly available dataset containing death-certificate data for over 25 million individuals....

Descripción completa

Detalles Bibliográficos
Autores principales: Cossin, Sebastien, Diouf, Serigne, Griffier, Romain, Le Barrois d’Orgeval, Philippine, Diallo, Gayo, Jouhet, Vianney
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935495/
https://www.ncbi.nlm.nih.gov/pubmed/33709061
http://dx.doi.org/10.1093/jamiaopen/ooab005
_version_ 1783661008557965312
author Cossin, Sebastien
Diouf, Serigne
Griffier, Romain
Le Barrois d’Orgeval, Philippine
Diallo, Gayo
Jouhet, Vianney
author_facet Cossin, Sebastien
Diouf, Serigne
Griffier, Romain
Le Barrois d’Orgeval, Philippine
Diallo, Gayo
Jouhet, Vianney
author_sort Cossin, Sebastien
collection PubMed
description INTRODUCTION: Vital status is of central importance to hospital clinical research. However, hospital information systems record only in-hospital death information. Recently, the French government released a publicly available dataset containing death-certificate data for over 25 million individuals. The objective of this study was to link French death certificates to the Bordeaux University Hospital records to complete the vital status information. MATERIALS AND METHODS: Our linkage strategy was composed of a search engine to reduce the number of comparisons and machine-learning algorithms. The overall pipeline was evaluated by assembling a file containing 3,565 in-hospital deaths and 15,000 alive persons. RESULTS: The recall and precision of our linkage strategy were 97.5% and 99.97% for the upper threshold and 99.4% and 98.9% for the lower threshold, respectively. CONCLUSION: In this study, we demonstrated the feasibility of accurately linking hospital records with death certificates using a search engine and machine learning.
format Online
Article
Text
id pubmed-7935495
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-79354952021-03-10 Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning Cossin, Sebastien Diouf, Serigne Griffier, Romain Le Barrois d’Orgeval, Philippine Diallo, Gayo Jouhet, Vianney JAMIA Open Application Notes INTRODUCTION: Vital status is of central importance to hospital clinical research. However, hospital information systems record only in-hospital death information. Recently, the French government released a publicly available dataset containing death-certificate data for over 25 million individuals. The objective of this study was to link French death certificates to the Bordeaux University Hospital records to complete the vital status information. MATERIALS AND METHODS: Our linkage strategy was composed of a search engine to reduce the number of comparisons and machine-learning algorithms. The overall pipeline was evaluated by assembling a file containing 3,565 in-hospital deaths and 15,000 alive persons. RESULTS: The recall and precision of our linkage strategy were 97.5% and 99.97% for the upper threshold and 99.4% and 98.9% for the lower threshold, respectively. CONCLUSION: In this study, we demonstrated the feasibility of accurately linking hospital records with death certificates using a search engine and machine learning. Oxford University Press 2021-03-01 /pmc/articles/PMC7935495/ /pubmed/33709061 http://dx.doi.org/10.1093/jamiaopen/ooab005 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Application Notes
Cossin, Sebastien
Diouf, Serigne
Griffier, Romain
Le Barrois d’Orgeval, Philippine
Diallo, Gayo
Jouhet, Vianney
Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning
title Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning
title_full Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning
title_fullStr Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning
title_full_unstemmed Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning
title_short Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning
title_sort linkage of hospital records and death certificates by a search engine and machine learning
topic Application Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935495/
https://www.ncbi.nlm.nih.gov/pubmed/33709061
http://dx.doi.org/10.1093/jamiaopen/ooab005
work_keys_str_mv AT cossinsebastien linkageofhospitalrecordsanddeathcertificatesbyasearchengineandmachinelearning
AT dioufserigne linkageofhospitalrecordsanddeathcertificatesbyasearchengineandmachinelearning
AT griffierromain linkageofhospitalrecordsanddeathcertificatesbyasearchengineandmachinelearning
AT lebarroisdorgevalphilippine linkageofhospitalrecordsanddeathcertificatesbyasearchengineandmachinelearning
AT diallogayo linkageofhospitalrecordsanddeathcertificatesbyasearchengineandmachinelearning
AT jouhetvianney linkageofhospitalrecordsanddeathcertificatesbyasearchengineandmachinelearning