Comparing the content of traditional faxed consultations to eConsults within an academic endocrinology clinic
Bibliographic record
Abstract
OBJECTIVE: To compare the content of traditional faxed referrals and electronic consultations (eConsults) and determine how many questions sent by traditional referral could be successfully addressed using eConsult. METHODS: We conducted a cross-sectional, qualitative study of eConsults and faxed referrals sent to a tertiary diabetes and endocrinology clinic in Ottawa, Ontario. A convenience sample of 300 faxed referrals sent between March and July 2017 and 300 eConsults submitted between January and December 2017 were selected and coded using an established taxonomy to determine question type. Two endocrinologists reviewed the faxed referrals to assess whether they could have been addressed using eConsult. Responses to a mandatory closeout survey were reviewed for all eConsults, assessing the case's outcome, impact on decision to refer, and educational value. RESULTS: Most faxed consultations were requests for shared care in diabetes mellitus, whereas most eConsults requested help in diagnostic test interpretation. 25-27% of faxed consults were felt to be potentially amenable to eConsult. Referring provider behaviour was changed in 45.3% of eConsult cases through avoidance of face-to-face consultation. CONCLUSION: eConsult is a promising tool for PCPs to improve access to specialist opinion without necessitating a face-to-face visit.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".