Improving accessibility through referral management: setting targets for specialist care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of optimized referral distribution strategies to improve access to specialty care is assessed. A mathematical model of a generalized care pathway is developed and the distribution of referrals is posed as an optimization problem. The objective is to minimize time from referral to a targeted stage in the care pathway (e.g., specialist consult, surgery, etc.). Numerical simulations informed by data on hip and knee surgeries demonstrate wait reductions from 21 to 38 days (16.8–30.4%) from time of referral to time of consult and from 33 to 66 days (12.6–24.7%) to time of surgery. However, the optimized referral distribution strategy minimizes wait times to the targeted stage only; wait times to non-targeted stages in the care pathway are suboptimal and may increase as an unintended consequence. Consequently, to achieve desired improvements in access, the targeted stage for wait time minimization must be carefully identified and prioritized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it