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Pré-publication, Document de travail

Disparities in accessibility to oncology care centers in France

Eric Daoud 1, 2 Anne-Sophie Hamy-Petit 3 Elise Dumas 4, 3 Lidia Delrieu 3 Beatriz Grandal Rejo 3 Christine Le Bihan-Benjamin 5 Sophie Houzard 5 Philippe-Jean Bousquet 6, 5 Judicaël Hotton 7 Aude-Marie Savoye 7 Christelle Jouannaud 7 Chloé-Agathe Azencott 4 Marc Lelarge 2 Fabien Reyal 7, 3 
2 DYOGENE - Dynamics of Geometric Networks
DI-ENS - Département d'informatique - ENS Paris, CNRS - Centre National de la Recherche Scientifique : UMR 8548, Inria de Paris
6 SESSTIM - U1252 INSERM - AMU - UMR 259 IRD - “Cancer, Biomedicine & Society” group
SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD - Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale
Abstract : Background Cancer caused nearly 10 million deaths in 2020. While most of the ongoing research focuses on finding new treatments, accessibility to oncology care receives less attention. However, access to health services plays a key role in cancer survival. Spatial accessibility methods have been successfully applied to measure accessibility to primary care. Yet, little research to date focused on oncology care specifically. Methods We focused on all care centers with medicine, surgery, or obstetric activity in metropolitan France. We propose a clustering algorithm to automatically label the hospitals in terms of oncology specialization. Then, we computed an accessibility score to these hospitals for every municipality in metropolitan France. Finally, we proposed an optimization algorithm to increase the oncology accessibility by identifying centers which should increase their capacity. Results We labelled 1,662 care centers into 8 clusters. Half of them were eligible for oncology care and 118 centers were identified as experts. We computed the oncology accessibility score for 34,877 municipalities in metropolitan France. Half of the population lived in the top 20% accessibility areas, and 6.3% in the bottom 20% zones. Accessibility was higher near dense cities, where the experts care centers were located. By combining the care centers clusters and the accessibility distributions, our optimization algorithm could identify hospitals to grow, to reduce accessibility disparities. Conclusion Our method made it possible to quantify oncology care accessibility across all metropolitan France, as well as to make suggestions on where to increase hospital capacity to improve accessibility, especially in more populated suburban areas. Our approach was deliberately non-specific to cancer type nor to the kind of stays, but it could be adapted to more specific scenarios. We packaged our method into a web application allowing the users to run the algorithms with various parameters and visualize the results. Highlights We computed the oncology accessibility score for 34,877 municipalities and highlighted disparities. Our optimization algorithm can identify hospitals to grow, to reduce accessibility disparities. We packaged our algorithms and results into a web application, opened to healthcare professionals
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Pré-publication, Document de travail
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https://hal-mines-paristech.archives-ouvertes.fr/hal-03511050
Contributeur : Chloé-Agathe Azencott Connectez-vous pour contacter le contributeur
Soumis le : mardi 4 janvier 2022 - 17:18:31
Dernière modification le : mardi 25 octobre 2022 - 16:23:03

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Eric Daoud, Anne-Sophie Hamy-Petit, Elise Dumas, Lidia Delrieu, Beatriz Grandal Rejo, et al.. Disparities in accessibility to oncology care centers in France. 2022. ⟨hal-03511050⟩

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