Assessing Rehabilitation Eligibility of Older Patients: An Ethical Analysis of the Impact of Bias
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hospitalized older patients are more vulnerable to physical or cognitive functional decline. Inpatient rehabilitation programs improve significantly their functional status and may prevent their admission to nursing homes. While inpatient rehabilitation institutions have established admission criteria that can be seen as objective, the risk of bias remains and raises the question of equitable access for more vulnerable populations such as older patients. This paper reviews some established eligibility criteria for inpatient rehabilitation by examining a framework used in Montreal, Québec, Canada for assessing rehabilitation eligibility and by applying this framework to a case study. It also highlights the unique ethical challenges presented by the assessment of older patients. We conclude that in order to appropriately protect the vulnerable population of older patients in the context of priority setting and allocation of scarce resources, there is a need to establish more specific criteria that can better guide the assessment of this particular population.
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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 | 0.047 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it