Difficult healthcare transitions
Bibliographic record
Abstract
BACKGROUND: In Ontario, Canada, patients who lack decision-making capacity and have no family or friends to act as substitute decision-makers currently rely on the Office of the Public Guardian and Trustee to consent to long-term care (nursing home) placement, but they have no legal representative for other placement decisions. OBJECTIVES: We highlight the current gap in legislation for difficult transition cases involving unrepresented patients and provide a novel framework for who ought to assist with making these decisions and how these decisions ought to be made. RESEARCH DESIGN: This paper considers models advanced by Volpe and Steinman with regard to who ought to make placement decisions for unrepresented patients, as well as current ethical models for analyzing how these decisions should be made. PARTICIPANTS AND RESEARCH CONTEXT: We describe an anonymized healthcare transition case to illustrate the fact that there is no legally recognized decision-maker for placement destinations other than long-term care facilities and to show how this impacts all stakeholders. ETHICAL CONSIDERATIONS: The case provided is an anonymized vignette representing a typical transition case involving an unrepresented patient. FINDINGS: As a result of a gap in provincial legislation, healthcare providers usually determine the appropriate placement destination without a clear framework to guide the process and this can cause significant moral distress. DISCUSSION: We argue for a team decision-making approach in the short term, and a legislative change in the long-term, to respect the patient voice, evaluate benefit and risk, enhance collaboration between healthcare providers and patients, and promote social justice. We believe that our approach, which draws upon the strengths of interprofessional teams, will be of interest to all who are concerned with the welfare and ethical treatment of the patients for whom they care. CONCLUSIONS: One of the main strengths of our recommendation is that it provides all members of the healthcare team (including nurses, social workers, therapists, and others) an increased opportunity to advocate on behalf of unrepresented patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".