The Dermatologist is Out? Assessment of Dermatologists in Ontario Accepting Ontario Health Insurance Plan (OHIP) Referrals for Hair Loss Evaluation
Bibliographic record
Abstract
BACKGROUND: The Ontario Health Insurance Plan (OHIP) insures appointments for the assessment and diagnosis of hair loss, or alopecia. Although anecdotal, discussion suggests that, increasingly, dermatologists decline to see referrals of this nature. There has been a lack of objective surveillance to determine the proportion of dermatologists in practice who accept referrals for this concern. OBJECTIVES: This study investigated the proportion of dermatologists in Ontario accepting OHIP referrals for hair loss. Secondary objectives included wait times, consultation fees for non-OHIP visits, and factors affecting referral acceptance or rejection. METHODS: A cross-sectional telephone survey was conducted, in which 284 dermatologists' offices listed by the College of Physicians and Surgeons of Ontario (CPSO) were contacted. The study investigated the acceptance of OHIP referrals for hair loss, wait times, additional referral requirements, and private consultation fees. Descriptive statistics were employed to summarize data. RESULTS: Of the 284 offices contacted, 38.38% (109/284) accepted OHIP referrals for hair loss, 48.59% (138/284) did not, and 13.03% (37/284) were unavailable for contact. The average wait time for offices that accepted referrals was 4.51 ± 4.07 months. Non-OHIP consultation fees ranged from $135 to $299 CAD. Some offices limited acceptance to specific conditions such as alopecia areata and male androgenetic alopecia. CONCLUSION: A total of 48.59% of dermatologists in Ontario do not accept OHIP referrals for hair loss, while the status of 13.03% remains unknown. This reality raises concerns about accessibility to care. Further research is needed to investigate factors influencing referral acceptance.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".