Fig 1.
Visit selection flow chart from the RESURGENCES database.
Fig 2.
Distribution of blocks of diagnoses in the 14 clusters.
Each cluster is represented by a unique color. The volume of each area is proportional to the number of patients affected by the given block of diagnoses during the study period. The label of each block can be found at: https://www.icd10data.com/ICD10CM/Codes or in S2 Table.
Table 1.
Characteristics of the 16 clusters to assess the impact analysis of new unscheduled care services (UCS) in clinics.
Fig 3.
Trends in clusters before and after the opening of UCS.
The numbers of weekly admissions are represented with boxplots where the middle line indicates the median and the boxes delimit the quartiles. The upper and lower whisker extends from the hinge to the largest and smallest (resp.) value no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles).
Table 2.
Before-after analysis of the weekly visits for each cluster to assess the impact analysis of new unscheduled care services (UCS) in clinics.
Table 3.
Before-after analysis of the weekly visits for each CIMU level in the decreasing clusters to assess the impact analysis of new unscheduled care services (UCSs) in clinics on acuity.
Fig 4.
Trends in unscheduled care in the Aube Region of France from December 2015 to December 2019.
The numbers of weekly admissions is represented using lines for each type of unscheduled care in the area surrounding the ED of Troyes. Ambulatory care is all the unscheduled consultations performed for the most part by general practitioners and nurses in the Aube territory via the SOS Médecin association and the Permanence Des Soins Ambulatoires (PDSA) registered in the Système Nationale des Données de Santé (SNDS, the National Health Information database).
Table 4.
Logistic regression model showing the factors associated with the probability of belonging to decreasing clusters.