Back

Serious Illness Conversations in Older Patients at High Risk of Mortality in Primary Care During the COVID-19 Pandemic: A Quasi-Experimental Study

Chicoine, G.; Germain, N.; Turcotte, S.; Cote, E.; Gelinas, V.; Legare, F.; Paquette, J.-S.; Totten, A. M.; Morin, M.; Straus, S. E.; Archambault, P. M.

2026-07-15 primary care research
10.64898/2026.07.12.26357462 medRxiv
Show abstract

Purpose: Serious Illness Conversations (SICs) are essential to delivering person-centered care for older adults with chronic conditions, but are rarely integrated into routine primary care. To address this gap, we compared the effectiveness of a structured training strategy versus passive dissemination of educational materials on SIC documentation rates during the COVID-19 pandemic. Methods: A quasi-experimental study across 13 primary care clinics in Quebec, Canada. Five clinics received structured team-based Serious Illness Care Program training (intervention group) with a provincially disseminated SIC toolkit and eight received the toolkit only (control group). The primary outcome was the proportion of patients with a documented SIC across three time periods (Period 1, pre pandemic; Period 2, pandemic initial wave; and Period 3, post dissemination of SIC toolkit). We used generalized estimating equations (GEE). Results: Across 13 clinics, 2,368 eligible patients (mean age 75.8 years (SD = 7.5), 54% female, with a mean Charlson Comorbidity Index of 4.88 (SD = 2)) accounted for 19,134 clinical visits, 49.5% in person and 49.6% virtually. SIC documentation rates were 3.3% (control) and 3.4% (intervention) in Period 1, 9.3% and 4.3% in Period 2, and 6.4% and 4.8% in Period 3, respectively. There was no statistically significant improvement to SIC documentation in the intervention group at Period 2 nor Period 3. Conclusion: Structured training was not more effective than passive dissemination for SIC documentation. Educational interventions must be supported by structural changes, workflow integration, and organizational leadership. Multi-level implementation strategies are needed to embed SICs sustainably into primary care.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.