Distinct care trajectories among persons living with arthritic conditions: A two-year state sequence analysis - Nguena Nguefack, Hermine Lore; Pagé, M. Gabrielle; Choinière, Manon; Vanasse, Alain; Deslauriers, Simon; Angarita-Fonseca, Adriana; Blanchette, Marc-André; Lacasse, Anaïs (Frontiers in Pain Research, 2022)
Objectives: Developing solutions to optimize care trajectories (CareTs) requires examining patient journeys through the health care system. This study aimed to describe CareTs among people living with arthritis and evaluate their association with self-reported health outcomes. Methods: Analyses were conducted using the TorSaDE Cohort (n=102,148), which connects the 2007 to 2016 Canadian Community Health Surveys (CCHS) with Quebec administrative databases (longitudinal claims). CareTs of participants living with arthritis according to CCHS (n=16,631), over the two years before CCHS completion, were clustered using state sequence analysis (months as a time unit). CareT group membership was then put in association with self-reported outcomes (pain intensity and interference, self-perceived general and mental health). Results: The analysis revealed five CareT groups characterized predominantly by: 1) arthritis-related visits to a specialist (n=2,756; 16.6%), 2) arthritis-related emergency department visits (n=2,928; 17.6%), 3) very high all-cause health care utilization and arthritis-related hospitalizations (n=1,570; 9.4%), 4) arthritis-related medical visits to general practitioners and specialists (n=2,708; 16.3%), 5) low all-cause health care utilization (n=6,669; 40.1%). Multivariable results revealed that CareT group membership was associated with higher levels of pain interference (CareT group #3 vs #5: OR: 1.4, 95%CI: 1.1-1.8) and fair/poor self-perceived general health (CareT group #1 vs #5: OR: 1.551, 95%CI: 1.319-1.824; #2 vs #5: OR: 1.244, 95%CI: 1.062-1.457; #3 vs #5: OR: 1.771, 95%CI: 1.451-2.162; #4 vs #5: OR: 1.481, 95%CI: 1.265-1.735). Discussion: Sate sequence analysis is an innovative method of studying CareTs and valuable for making evidence-based decisions taking into account inter- and intra-individual variability.