Abstract
Routine management of cystic fibrosis (CF) has recently turned a corner with an increase in ambulatory care, which would improve lifestyle and reduce in-hospital infections. Our objective was to cluster management patterns considering both chronology and places of care (ambulatory or in-hospital) through sequential analysis. CF patients were selected in 2016 within the French National Claims Databases (SNIIRAM), from which individual 2-year pathways for medical visits with specialists involved in CF management was built. Optimal matching was used to transform this pathway into 3-month sequences, prior to apply unsupervised methods classifying management patterns. Among the 10,568 CF patients identified, 7,360 were considered for the sequential analysis (no healthcare consumption: n=503; no medical visit of interest: n=2, 705). Patterns were highly differentiated for the place of care. The partition around Meloids (PAM) was the most successful method to classify trajectories. A 3-cluster typology was retained: 35% patients belonged to the “ambulatory” cluster, 32% to the “mixed” one – with both in and out-patient visits at each sequence -, and 33% to the “low management” one. From a multinomial regression analysis: (i) age is a determinant of management patterns (p<0.001) - with majority of preschool children [0-6[, school children [6-12[ and adolescents [12-18[ belonging to the “mixed cluster” (42%, 41% and 46%, respectively), while most of adults belonged to the “ambulatory” one (43%) -, (ii) incident patients were more likely to belong to the “mixed” cluster (p=0.023). A third of CF patients with medical follow-up is almost entirely managed in ambulatory, mainly adults; a third is managed by both in and outpatient care. The question patient with low or no management will be further assessed. On-going analyses will allow the identification of the determinants (e.g. comorbidities, treatments, medical devices) associated with the distribution of CF patients within the management patterns.
Published Version (Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have