Access to intensive care unit beds for neurosurgery patients: a qualitative case study
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
OBJECTIVES: The purpose of this study was to describe the process used to decide which patients are admitted to the intensive care unit (ICU) at a hospital with special focus on access for neurosurgery patients, and evaluate it using "accountability for reasonableness". METHODS: Qualitative case study methodology was used. Data were collected from documents, interviews with key informants, and observations. The data were subjected to thematic analysis and evaluated using the four conditions of "accountability for reasonableness" (relevance, publicity, appeals, enforcement) to identify good practices and opportunities for improvement. RESULTS: ICU admissions were based on the referring physician's assessment of the medical need of the patient for an ICU bed. Non-medical criteria (for example, family wishes) also influenced admission decisions. Although there was an ICU bed allocation policy, patient need always superceded the bed allocation policy. ICU admission guidelines were not used. Admission decisions and reasons were disseminated to the ICU charge nurse, the bed coordinator, the ICU resident, the intensivist, and the requesting physician/surgeon by word of mouth and by written documentation in the patient's chart, but not to the patient or family. Appeals occurred informally, through negotiations between clinicians. Enforcement of relevance, publicity, and appeals was felt to be either non-existent or deficient. CONCLUSIONS: Conducting a case study of priority setting decisions for patients requiring ICU beds, with a special focus on neurosurgical patients, and applying the ethical framework "accountability for reasonableness" can help critical care units improve the fairness of their priority setting.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it