Referral letters to pediatric rheumatology: referral content and impact on triage – an observational study
Bibliographic record
Abstract
BACKGROUND: Delays in access to care in rheumatology are well documented. Many factors contribute to these delays and studies in adult populations indicate that incomplete referral letters may play a role. This study aims to describe the content of referral letters to pediatric rheumatology and to investigate the impact of incomplete letters on time to triage and accessing care. FINDINGS: METHODS: We evaluated referrals to a tertiary care pediatric rheumatology centre for eight components of comprehensive referral letters. In addition, we compared time-to-triage and percentage of patients receiving rheumatic diagnoses between letters with sufficient content for immediate triage versus incomplete letters requiring further information. Logistic regression models identified factors associated with delayed triage. RESULTS: Further information was requested for 67/447 (15%) referrals, resulting in median delay in time-to-triage of seven days. Delayed triage was associated with four factors: lack of musculoskeletal physical examination, referral from family physicians versus other specialty, missing information regarding management, and lack of rheumatic diagnosis of concern. Rheumatic diagnoses resulted from 42% of all referrals overall, specifically from 170/384 (44%) of immediately triaged referrals and 19/63 (30%) of referrals requiring further information. Rheumatic diagnoses resulted less commonly from family physician referrals. CONCLUSIONS: Missing important details in referrals to pediatric rheumatology contribute to delayed assessment. These findings can inform initiatives to educate physicians around relevant content of referral letters to facilitate timely access to care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".