A retrospective audit of general practitioner’s referrals to Guys and St Thomas’ specialist menopause clinic between 2021 and 2022
Bibliographic record
Abstract
Purpose: We performed a retrospective audit of General Practitioners’ (GPs) referrals to the specialist Menopause Clinic at Guys and St Thomas’s (GSTT) between 2021 and 2022. We aim to establish the indication for the referrals and whether they were compliant with the National Institute for Health and Care Excellence Guidance NICE. Background: GSTT is a teaching hospital in central London that educates gynaecologists in training as well as (GP) for specialist certification in Menopause. The menopause clinic receives approximately 580 GP referrals per month from South East London practices. The current waiting time for an initial appointment is up to 1 year. This delay reflects an increase in demand for menopause care and a deficit in service provision in many areas of the UK. NICE has recommended that GPs refer complicated cases to menopause specialists, with 11 specific criteria. Study Sample and Data Collection: We randomly selected 50 patients referred to the GSTT clinic by a GP between 2021 and 2022. Patient data were collected, including patient demographics, date of referral, indication for referral, date of consultation, waiting time, past medical history, investigations, and treatment instigated during the appointment. Results: The majority of referrals to the GSTT menopause Specialist clinic met the NICE guidelines (76%). One-sixth of the referrals could have been prevented or managed through alternative routes. Finally, although this is a small study, some patient unmet needs (PUNS) and GPs’ educational needs have been identified.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".