Tracking clusters of patients over time enables extracting information from medico-administrative databases - Université de Paris - Faculté de Santé Access content directly
Journal Articles Journal of Biomedical Informatics Year : 2023

Tracking clusters of patients over time enables extracting information from medico-administrative databases

Abstract

Context Identifying clusters (i.e., subgroups) of patients from the analysis of medico-administrative databases is particularly important to better understand disease heterogeneity. However, these databases contain different types of longitudinal variables which are measured over different follow-up periods, generating truncated data. It is therefore fundamental to develop clustering approaches that can handle this type of data. Objective We propose here cluster-tracking approaches to identify clusters of patients from truncated longitudinal data contained in medico-administrative databases. Material and Methods We first cluster patients at each age. We then track the identified clusters over ages to construct cluster-trajectories. We compared our novel approaches with three classical longitudinal clustering approaches by calculating the silhouette score. As a use-case, we analyzed antithrombotic drugs used from 2008 to 2018 contained in the Échantillon Généraliste des Bénéficiaires (EGB), a French national cohort. Results Our cluster-tracking approaches allow us to identify several cluster-trajectories with clinical significance without any imputation of data. The comparison of the silhouette scores obtained with the different approaches highlights the better performances of the cluster-tracking approaches. Conclusion The cluster-tracking approaches are a novel and efficient alternative to identify patient clusters from medico-administrative databases by taking into account their specificities.
Fichier principal
Vignette du fichier
JLArticle_JBI_revisedversion_HAL.pdf (7.8 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04027783 , version 1 (14-03-2023)

Identifiers

Cite

Judith Lambert, Anne-Louise Leutenegger, Anne-Sophie Jannot, Anaïs Baudot. Tracking clusters of patients over time enables extracting information from medico-administrative databases. Journal of Biomedical Informatics, 2023, 139, pp.104309. ⟨10.1016/j.jbi.2023.104309⟩. ⟨hal-04027783⟩
34 View
43 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More