An Ethics-informed, Policy-based Approach to the Management of Challenges Posed by Living-at-Risk, Frequent Users of Emergency Departments
Bibliographic record
Abstract
The complex health and social circumstances of living-at-risk, frequent users of emergency departments (aREDFUs) in the health jurisdictions of high-income countries, and the related, significant challenges posed for emergency departments and the health care providers working within them, are identified and explored in the paper. Ethical analyses of a set of relevant domains are performed, i.e., individual and relational autonomy considerations, relevant social construction and personal responsibility conceptions, patient welfare principles (beneficence, nonmaleficence, continuity of care), harm reduction methodologies and their applications, health equity, and justice considerations of the distributive, formal and social types. The outcomes of these analyses demonstrate that there are ethically compelling reasons for emergency departments to adopt an ethics-informed, policy-based approach to the longitudinal care and management of living-at-risk, frequent users of emergency departments. From a formal justice perspective, the development and uses of such an approach are justified by a demonstrable relevant difference between living-at-risk, frequent users of emergency departments and other persons and groups of patients who visit emergency departments. We propose an example of such a policy-based approach. Examples of possible, pragmatic applications of this approach, which help ensure that aREDFUs who present to the ED are managed in a fair and optimally consistent manner, are provided for the consideration of an urban emergency department’s policymaking working group.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".