Evaluating the Implementation of The Champlain BASE™ eConsult Service in a New Region of Ontario, Canada: A Cross-Sectional Study
Bibliographic record
Abstract
OBJECTIVE: To replicate an existing electronic consultation (eConsult) service in a new jurisdiction to test its generalizability. METHODS: We conducted a cross-sectional study of all eConsults submitted by providers in the region of Mississauga Halton, Ontario, between January 5, 2015, and May 31, 2016. We compared our results to those from the original pilot in Eastern Ontario. The RE-AIM model served as our study framework. RESULTS: Providers submitted 594 patient cases to 46 different specialty groups during the study period. Specialists responded in a median of 1.1 days, with 75% of cases answered within four days. Providers rated the service as having high or very high value for themselves and their patients in 92% of cases. The service yielded a net program cost of $10,321.56. CONCLUSION: Our findings resembled those of the initial implementation, though with a faster rate of uptake and lower cost because of the avoidance of start-up and administrative costs.
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.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".