Trends in Emergency Department Visits by Retirement Home Residents: A Population-Based Study

Main Article Content

Wenshan Li
Richard Perez
Stephen Fung
James Lee
Chantal Backman

Abstract

Background
With persistent LTC shortages, retirement homes (RHs) house an increasingly large and frail population despite fewer on-site medical supports, leading to high rates of acute care use. Leveraging a postal code co-location method, we obtained a population-based capture of RH residents in Ontario, Canada and described trends in the rates/types of ED visits.


Methods
Using individually-linked health administrative datasets at ICES, we identified all ED visits (n=275,881) by RH residents from 2015–2023. Each visit was categorized using the Canadian Triage and Acuity Scale (CTAS), from Level I (Resuscitation-Critical) to Level V (Non-Urgent). We described annual ED visit rates by home characteristics and summarized main admission reasons and resident/home characteristics by CTAS category.


Results
Resident and home characteristics remained stable over time, though comorbidity burden declined slightly. Overall ED visit rates stayed at ~0.4 visits/10,000 person-days, except for a marked decline during early COVID-19 and rebound in 2021. Rural homes and homes without dementia programs had higher visit rates and greater volatility during COVID-19. Less-urgent visits (CTAS 4; top diagnoses included aftercare and cellulitis) decreased from 15.2% in 2015 to 7.6% in 2023, while urgent visits (CTAS 3; top diagnoses included heart failure and injuries) increased from 56.9% in 2015 to 65.6% in 2023.


Impact
The rising acuity of ED visits by RH residents may suggest a lack of clinical capacity and adequate preventative measures, exacerbated by structural inequities. Routine monitoring and stronger oversight of RHs may be necessary to reduce ED visits and ensure resident safety.

Article Details

How to Cite
Li, W., Perez, R., Fung, S., Lee, J. and Backman, C. (2026) “Trends in Emergency Department Visits by Retirement Home Residents: A Population-Based Study”, International Journal of Population Data Science, 11(5). doi: 10.23889/ijpds.v11i5.3737.