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Linkage of Hospital Records and Death Certificates by a Search Engine and Machine Learning
Sebastien Cossin1,2, Serigne Diouf1,2, Romain Griffier1,2
1CHU de Bordeaux, Pôle de Santé Publique, Service d'information Médicale, Informatique et Archivistique Médicales (IAM), Bordeaux F-33000, France.
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.
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01:19Purpose of Health Records II
01:11Purpose of Health Records I
Here's a breakdown of how health records serve these purposes: