Primary Care Providers' Perspectives on the Ontario eConsult Program
Why this work is in the frame
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Bibliographic record
Abstract
Background: Electronic consultation (eConsult) allows asynchronous virtual communication between primary care providers (PCPs) and specialists regarding patient care. Introduction: The Ontario eConsult Program enables timely and equitable access to specialist advice for Ontarians. This study examines clinicians' perspectives and experiences with the program. Materials and Methods: We conducted an anonymous survey of PCPs registered for the Ontario eConsult Program. The survey ran from June to August 2019 and included questions on PCPs' experiences with the service, opinions on remuneration, and recommendations for enhancement. Results: One thousand two hundred fifty-six PCPs completed the survey (response rate of 16%). Seventy-eight percent had submitted an eConsult, of whom 67% were active users (i.e., had submitted ≥3 eConsults in the past 6 months). The majority of PCPs stated that their user experience was very good (57%) or good (31%), 74% agreed that eConsult improved their referral decision making, and 73% agreed that eConsult increased their ability to manage a broader array of diagnoses. Thirty-seven percent felt adequately compensated for using eConsult, 30% wanted higher rates of remuneration, and 31% were not compensated or were unaware of the fee code. Discussion: The majority of PCPs who use eConsult had positive experiences with the service. Nevertheless, improvements to further streamline the service's use, particularly through electronic medical record integration, were broadly cited as a desirable improvement. Conclusions: PCPs expressed an overall positive experience with the Ontario eConsult Program, citing prompt response times and improved care delivery as chief benefits.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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