P.216 Improving access to neurosurgeons through an electronic consultation service
Bibliographic record
Abstract
Background: Timely access to neurosurgeons for clinical advice is limited depending on region and other social factors. An eConsult service providing access to neurosurgeons in Ontario, Canada may influence primary care provider (PCP) course of action and referral behaviours. Methods: The Champlain BASE (Building Access to Specialist Care via eConsult) service allows PCPs to access specialist care in lieu of traditional face-to-face referrals. We conducted a cross-sectional study of eConsult cases submitted to neurosurgeons by PCPs between Jan 1, 2017 and Dec 31, 2018. Usage data and PCP responses to a mandatory closeout survey were analyzed. Results: A total of 432 eConsults were submitted. Specialist median response time was 2.29 days with 86.8% of responses occurring within 7 days. PCPs received a new or additional course of action in 53% of cases. An unnecessary face-to-face referral was avoided in 57% of all eConsults, and 50% of cases where the PCP initially contemplated requesting a referral. Over 86% of cases were rated at least 4 out of 5 in value for PCPs and their patients. Conclusions: The use of eConsult improves access to neurosurgeons by providing timely, highly-rated practice-changing clinical advice while reducing the need for patients to attend face-to-face office visits.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.073 | 0.006 |
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".