Improving patient access to symptomatic treatment through self-serving nausea stations at Peace Arch Hospital emergency department
Bibliographic record
Abstract
BACKGROUND: Nausea is a common complaint among patients waiting at the emergency department (ED). Previous research indicates that isopropyl alcohol (IPA) can provide symptomatic relief for nausea. However, the number of studies investigating this effect is limited, especially in ED settings. This study investigates the effect of IPA administration on patients presenting with nausea to the ED. We aim to provide symptomatic relief to 20% of these patients. METHODS: In the Peach Arch Hospital (PAH) ED, patients who reported feeling nauseous were provided with a single IPA swab, instructional materials and feedback surveys. Patients inhaled IPA at a self-serving booth and completed a standardised survey immediately after. Patients were included in the study if they presented with nausea and excluded if they were under the age of 18, were pregnant, were allergic to alcohol, had cognitive impairment and/or were taking disulfiram. Multiple plan-do-study-act cycles were implemented to refine this study, including changes in feedback collection, instructional materials and presentation of IPA swabs. RESULTS: The total number of surveys completed over the 25-week period was 41 (n=41). These surveys showed that IPA inhalation is effective in improving nausea symptoms in the ED, with 53% of survey respondents suggesting 'great improvement' or 'good improvement'. 88% of respondents felt there was improvement in symptoms. There were very limited participants (12%) who reported that IPA administration showed 'no improvement'. CONCLUSIONS: Self-serving nausea treatment stations may be an effective strategy in alleviating symptoms for patients awaiting to be seen by a physician while in the ED. These stations can enhance patient care through rapid treatment, optimise resources by reducing workload on nursing staff, and empower patients to manage their own symptoms.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".