A Practical Approach to Hospital Visitation During a Pandemic: Responding With Compassion to Unjustified Restrictions
Bibliographic record
Abstract
During the COVID-19 pandemic, evidence-based resources have been sought to support decision-making and strategically inform hospitals' policies, procedures, and practices. While greatly emphasizing protection, most guiding documents have neglected to support and protect the psychosocial needs of frontline health care workers and patients and their families during provision of palliative and end-of-life care. Consequently, the stage has been set for increased anxiety, moral distress, and moral injury and extreme moral hazard. A family-centered approach to care has been unilaterally relinquished to a secondary and nonessential role during the current crisis. This phenomenon violates a foundational public health principle, namely, to apply the least restrictive means to achieve good for the many. Instead, there has been widespread adoption of utilitarian and paternalistic approaches. In many cases the foundational principles of palliative care have also been neglected. No circumstance, even a global public health emergency, should ever cause health care providers to deny their ethical obligations and human commitment to compassion. The lack of responsive protocols for family visitation, particularly at the end of life, is an important gap in the current recommendations for pandemic triage and contingency planning. A stepwise approach to hospital visitation using a tiered, standardized process for responding to emerging clinical circumstances and individual patients' needs should be considered, following the principle of proportionality. A contingency plan, based on epidemiological data, is the best strategy to refocus health care ethics in practice now and for the future.
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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 | 0.038 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.031 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.006 | 0.025 |
| Research integrity | 0.017 | 0.026 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".