five

Datasheet1_Distinct care trajectories among persons living with arthritic conditions: A two-year state sequence analysis.pdf

收藏
NIAID Data Ecosystem2026-03-14 收录
下载链接:
https://figshare.com/articles/dataset/Datasheet1_Distinct_care_trajectories_among_persons_living_with_arthritic_conditions_A_two-year_state_sequence_analysis_pdf/21545604
下载链接
链接失效反馈
官方服务:
资源简介:
ObjectivesDeveloping 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. MethodsAnalyses 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). ResultsThe 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). DiscussionSate sequence analysis is an innovative method of studying CareTs and valuable for making evidence-based decisions taking into account inter- and intra-individual variability.
创建时间:
2022-11-12
二维码
社区交流群
二维码
科研交流群
商业服务