Triage to Advice Only for Referring Providers: A Pilot Project Using Formal Consensus Methods to Establish Appropriate Patients for Electronic Consultations
Bibliographic record
Abstract
Background: Access to equitable, timely consultations by Endocrinologists remains problematic, requiring optimization of referral pathways to ensure rapid advice and reduce wait times. Objective: Our goal was to develop consensus amongst endocrinologists regarding referral scenarios that are most amenable to advice only (eConsultation) using formal consensus methods and to examine consistency across 2 distinct divisions of Endocrinology. Methods: Using the nominal group technique, members of the Division of Endocrinology at site 1, generated 58 clinical scenarios considered appropriate for advice back to the referring provider in place of an in person visit. A Modified Delphi process was conducted to indicate the level of agreement for each scenario. The rating scale included 5 items; strongly disagree, disagree, neutral, agree or strongly agree on whether the scenario is suitable for eConsultation. Three Modified Delphi rounds were conducted independently at 2 divisions of Endocrinologists at academic institutions in different cities and compared to identify areas of consensus or no consensus. We defined consensus as 70% or more of participants selected agree or strongly agree and fewer than 20% selected disagree or strongly disagree. Results: At site 1, among 12 initial respondents, consensus was obtained for 45 items (78%), of which 38 items were voted appropriate for eConsultation, 7 items were voted as not appropriate, and 13 had no consensus. At the second site, among 13 initial respondents, consensus was reached for 48 items (83%) of which 34 were voted as appropriate while 14 were considered not appropriate for eConsultation and no consensus was found for 10 items. Major discordance between sites occurred for only 2 items. Conclusion: There was a high degree of consensus at 2 academic medical centers identifying clinical scenarios appropriate for advice back/eConsultation in place of an appointment utilizing a Modified Delphi process. Identifying scenarios with consensus supports consistent decision making for eConsultation among clinicians involved in triaging referrals for ambulatory care Endocrinology.
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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 | 0.112 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".