The Patient Path: a first approach

Essifi, Rim

Type de document :

Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes: Conférence invitée

Titre :

The Patient Path: a first approach

Auteur(s) :

Essifi, Rim [Auteur]
Inria Lille - Nord Europe
MOdel for Data Analysis and Learning [MODAL]

Titre de la manifestation scientifique :

CMStatistics 2022 - The 15th International Conference of the ERCIM WG on Computational and Methodological Statistics

Ville :

Londres

Pays :

Royaume-Uni

Date de début de la manifestation scientifique :

2022-12-17

Date de publication :

2022-12-17

Mot(s)-clé(s) en anglais :

care pathways
functional data analysis
longitudinal data analysis
clustering
Gaussian processes

Discipline(s) HAL :

Mathématiques [math]/Statistiques [math.ST]

Résumé en anglais : [en]

European healthcare systems are faced with multiple challenges, including anaging population, an increase in chronic diseases and patients withmulti-morbidity, and limited financial and human resources. The response tothese ...
Lire la suite >European healthcare systems are faced with multiple challenges, including anaging population, an increase in chronic diseases and patients withmulti-morbidity, and limited financial and human resources. The response tothese challenges is based in particular on the organisation of care into carepathways. Namely, Once the data necessary for the construction of a carepathway are acquired and processed, one has to model the patient pathwaymathematically in a generic way. After that, using clustering algorithms, one canidentify patients subgroups, then, mine for common treatments, predict thefuture of patient pathways and answer clinicians’ questions. All these steps wouldlead to an automated processes which has to be evaluated by medical experts.Available statistical methods remain limited and inefficient to construct carepathways. Indeed, data obtained from health care providers and insurancecompanies are all time-dependent, highly heterogeneous, qualitative in part, withseveral thousand possible modalities and mainly made up of missing data. Wepropose an approach based on functional data analysis combined withlongitudinal data analysis in order to construct care pathways.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL

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