Variation in the Geographic Distribution of the Otolaryngology Workforce: A National Geospatial Analysis
Bibliographic record
Abstract
Objective To examine the current geographic distribution of otolaryngologists in the United States and the disparities in socioeconomic demographics at the county and hospital referral region (HRR) level. Study Design Cross‐sectional study. Setting National cohort analysis including all otolaryngologists in the United States. Subjects and Methods All otolaryngologists board certified by the American Board of Otolaryngology–Head and Neck Surgery in the United States in 2018 were compared with overlaid demographic data from the 2010 United States Census Bureau by county and HRR. Associations between the density of otolaryngologists per population and socioeconomic characteristics were assessed and stratified by region. Results The average number of otolaryngologists was 3.6 (SD 9.6) per 100,000. On multivariable regression analysis, the density of otolaryngologists was positively associated with counties with the highest quartile of college education (1.8 providers per 100,000 [95% confidence interval [CI] 0.89, 2.90], P <. 001) and income (2.1 providers per 100,000 [95% CI 1.03, 3.07], P =. 01). Significant regional variation existed in access to otolaryngology care. Conclusion There are significant areas with disparate densities of otolaryngologists in the United States. Lower socioeconomic status, more severe poverty, and a lower number of college graduates in a county correlated with reduced density of otolaryngologists.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".