The effectiveness of schemes that refine referrals between primary and secondary care—the UK experience with glaucoma referrals: the Health Innovation & Education Cluster (HIEC) Glaucoma Pathways Project
Bibliographic record
Abstract
OBJECTIVES: A comparison of glaucoma referral refinement schemes (GRRS) in the UK during a time period of considerable change in national policy and guidance. DESIGN: Retrospective multisite review. SETTING: The outcomes of clinical examinations by optometrists with a specialist interest in glaucoma (OSIs) were compared with optometrists with no specialist interest in glaucoma (non-OSIs). Data from Huntingdon and Nottingham assessed non-OSI findings, while Manchester and Gloucestershire reviewed OSI findings. PARTICIPANTS: 1086 patients. 434 patients were from Huntingdon, 179 from Manchester, 204 from Gloucestershire and 269 from Nottingham. RESULTS: The first-visit discharge rate (FVDR) for all time periods for OSIs was 14.1% compared with 36.1% from non-OSIs (difference 22%, CI 16.9% to 26.7%; p<0.001). The FVDR increased after the April 2009 National Institute for Health and Clinical Excellence (NICE) glaucoma guidelines compared with pre-NICE, which was particularly evident when pre-NICE was compared with the current practice time period (OSIs 6.2-17.2%, difference 11%, CI -24.7% to 4.3%; p=0.18, non-OSIs 29.2-43.9%, difference 14.7%, CI -27.8% to -0.30%; p=0.03). Elevated intraocular pressure (IOP) was the commonest reason for referral for OSIs and non-OSIs, 28.7% and 36.1%, respectively, of total referrals. The proportion of referrals for elevated IOP increased from 10.9% pre-NICE to 28.0% post-NICE for OSIs, and from 19% to 45.1% for non-OSIs. CONCLUSIONS: In terms of 'demand management', OSIs can reduce FVDR of patients reviewed in secondary care; however, in terms of 'patient safety' this study also shows that overemphasis on IOP as a criterion for referral is having an adverse effect on both the non-OSIs and indeed the OSIs ability to detect glaucomatous optic nerve features. It is recommended that referral letters from non-OSIs be stratified for risk, directing high-risk patients straight to secondary care, and low-risk patients to OSIs.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".