Comparative end-of-life communication and support in hospitalised decedents before and during the COVID-19 pandemic: a retrospective regional cohort study in Ottawa, Canada
Bibliographic record
Abstract
OBJECTIVE: To compare end-of-life in-person family presence, patient-family communication and healthcare team-family communication encounters in hospitalised decedents before and during the COVID-19 pandemic. DESIGN: In a regional multicentre retrospective cohort study, electronic health record data were abstracted for a prepandemic group (pre-COVID) and two intrapandemic (March-August 2020, wave 1) groups, one COVID-19 free (COVID-ve) and one with COVID-19 infection (COVID+ve). Pre-COVID and COVID-ve groups were matched 2:1 (age, sex and care service) with the COVID+ve group. SETTING: One quaternary and two tertiary adult, acute care hospitals in Ottawa, Canada. PARTICIPANTS: Decedents (n=425): COVID+ve (n=85), COVID-ve (n=170) and pre-COVID (n=170). MAIN OUTCOME MEASURES: End-of-life (last 48 hours) in-person family presence and virtual (video) patient-family communication, and end-of-life (last 5 days) virtual team-family communication encounter occurrences were examined using logistic regression with ORs and 95% CIs. End-of-life (last 5 days) rates of in-person and telephone team-family communication encounters were examined using mixed-effects negative binomial models with incidence rate ratios (IRRs) and 95% CIs. RESULTS: End-of-life in-person family presence decreased progressively across pre-COVID (90.6%), COVID-ve (79.4%) and COVID+ve (47.1%) groups: adjusted ORs=0.38 (0.2-0.73) and 0.09 (0.04-0.17) for COVID-ve and COVID+ve groups, respectively. COVID-ve and COVID+ve groups had reduced in-person but increased telephone team-family communication encounters: IRRs=0.76 (0.64-0.9) and 0.61 (0.47-0.79) for in-person, and IRRs=2.6 (2.1-3.3) and 4.8 (3.7-6.1) for telephone communications, respectively. Virtual team-family communication encounters occurred in 17/85 (20%) and 10/170 (5.9%) of the COVID+ve and COVID-ve groups, respectively: adjusted OR=3.68 (1.51-8.95). CONCLUSIONS: In hospitalised COVID-19 pandemic wave 1 decedents, in-person family presence and in-person team-family communication encounters decreased at end of life, particularly in the COVID+ve group; virtual modalities were adopted for communication, and telephone use increased in team-family communication encounters. The implications of these communication changes for the patient, family and healthcare team warrant further study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".