End-of-Life Care During the Coronavirus Disease 2019 Pandemic: The 3 Wishes Program
Bibliographic record
Abstract
OBJECTIVES: Patient- and family-centered end-of-life care can be difficult to achieve in light of visitation restrictions and infection-prevention measures. We evaluated how the 3 Wishes Program evolved to allow continued provision of compassionate end-of-life care for critically ill patients during the coronavirus disease 2019 pandemic. DESIGN: This is a prospective observational study where data were collected 1 year prior to the coronavirus disease 2019 pandemic and 1 year after (from March 1, 2019, to March 31, 2021). The number of deceased patients whose care involved the 3 Wishes Program, their characteristics, and wishes were compared between prepandemic and pandemic periods. SETTING: Six adult ICUs of a two-hospital health system in Los Angeles. PATIENTS: Deceased patients whose care involved the 3 Wishes Program. INTERVENTIONS: The 3 Wishes Program is a palliative care intervention in which individualized wishes are implemented for dying patients and their families. MEASUREMENTS AND MAIN RESULTS: During the study period, the end-of-life care for 523 patients involved the 3 Wishes Program; more patients received the 3 Wishes Program as part of their end-of-life care during the pandemic period than during the prepandemic study period (24.8 vs 17.6 patients/mo; p = 0.044). Patients who died during the pandemic compared with prepandemic were less likely to have family at the bedside and more likely to have postmortem wishes fulfilled for their families. Compared with the 736 wishes implemented during the prepandemic period, the 969 wishes completed during the pandemic were more likely to involve keepsakes. Wishes were most commonly implemented by bedside nurses, although the 3 Wishes Program project manager (not involved in the patient’s clinical care) was more likely to assist remotely during the pandemic (24.8% vs 12.1%; p < 0.001). CONCLUSIONS: Bedside innovations, programmatic adaptations, and institutional support made it possible for healthcare workers to continue the 3 Wishes Program and provide compassionate end-of-life care in the ICU during this pandemic.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".