Medication-related queries received for 'after hours GP helpline' - Comparison of callers' intentions with GPs' advice
Bibliographic record
Abstract
Background Limited studies have explored the actual usage of the ‘after hours GP helpline’ (AGPH). Objective/s The objectives of the article are to describe medication-related calls to the AGPH and compare callers’ original intentions versus the advice provided by the general practitioner (GP). Methods We performed a detailed descriptive statistical analysis of medication-related queries received by the AGPH in 2014. Results In 2014, 13,600 medication-related calls were made to the national AGPH. For 86.56% of calls, GPs advised callers to either self-care only, or self-care overnight and see their GP during business hours. Of the 1442 calls where the caller had originally intended to visit the emergency department (ED), 76.70% were advised by GPs to self-care, and only 5.48% were advised to call 000 or visit an ED. Overall, less than 2.26% of callers were directed to the ED, despite 10.60% of people originally calling with this intention. Discussion The availability of an after-hours service potentially prevented 1363 people from unnecessarily attending an ED and directed 228 people who had originally underestimated the seriousness of their condition to an ED.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".