Back to Journals » International Journal of Chronic Obstructive Pulmonary Disease » Volume 15

Identification of Patient Profiles with High Risk of Hospital Re-Admissions for Acute COPD Exacerbations (AECOPD) in France Using a Machine Learning Model

Authors Cavailles A, Melloni B, Motola S, Dayde F, Laurent M, Le Lay K, Caumette D, Luciani L, Lleu PL, Berthon G, Flament T

Received 1 November 2019

Accepted for publication 10 March 2020

Published 30 April 2020 Volume 2020:15 Pages 949—962


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Richard Russell

Arnaud Cavailles,1 Boris Melloni,2 Stéphane Motola,3 Florent Dayde,3 Marie Laurent,3 Katell Le Lay,4 Didier Caumette,5 Laura Luciani,4 Pierre Louis Lleu,6 Geoffrey Berthon,7 Thomas Flament8

1Service de Pneumologie, Institut du Thorax, CHU de Nantes, Nantes, France; 2Service de Pneumologie, CHU Dupuytren, Limoges, France; 3HEVA, Lyon, France; 4HEOR/RWE, Boehringer Ingelheim, Paris, France; 5Institutional and Hospital Partnership, Boehringer Ingelheim, Paris, France; 6Medical Affairs, Boehringer Ingelheim, Paris, France; 7CHRU Tours, Tours, France; 8Service de Pneumologie, CHRU Bretonneau, Tours, France

Correspondence: Marie Laurent 186 Avenue Thiers, Lyon 69006, France
Tel +33 4 72 74 25 60

Purpose: To characterise patients with chronic obstructive pulmonary disease (COPD) who are rehospitalised for an acute exacerbation, to estimate the cost of these hospitalisations, to characterise high risk patient sub groups and to identify factors potentially associated with the risk of rehospitalisation.
Patients and Methods: This was a retrospective study using the French National Hospital Discharge Database. All patients aged ≥ 40 years hospitalised for an acute exacerbation of COPD between 2015 and 2016 were identified and followed for six months. Patients with at least one rehospitalisation for acute exacerbation of COPD constituted the rehospitalisation analysis population. A machine learning model was built to study the factors associated with the risk of rehospitalisation using decision tree analysis. A direct cost analysis was performed from the perspective of national health insurance.
Results: A total of  143,006 eligible patients were hospitalised for an acute exacerbation of COPD (AECOPD) in 2015– 2016 (mean age: 74 years; 62.1% men). 25,090 (18.8%) were rehospitalised for another exacerbation within six months. In this study,  8.5% of patients died during or immediately following the index hospitalisation and 10.5% died during or immediately after rehospitalisation (p < 0.001). The specific cost of these rehospitalisations was € 5304. The overall total cost per patient of all AECOPD-related stays was € 9623, being significantly higher in patients who were rehospitalised (€ 16,275) compared to those who were not (€ 8208). In decision tree analysis, the most important driver of rehospitalisation was hospitalisation in the previous two years (contributing 85% of the information).
Conclusion: Rehospitalisations for acute exacerbations of COPD carry a high epidemiological and economic burden. Since hospitalisation for an acute exacerbation is the most important determinant of future rehospitalisations, management of COPD needs to focus on interventions aimed at decreasing the rehospitalisation risk of in order to lower the burden of disease.

Keywords: comorbidity, rehospitalisation, decision tree analysis, cost

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]  View Full Text [HTML][Machine readable]