Characteristics and Outcomes of Physician-to-Physician Telephone Consultation Programs: Environmental Scan
Bibliographic record
Abstract
BACKGROUND: Telephone consultations between physicians provide quick access to medical advice, allowing patients to be cared for by calling physicians in their local settings. OBJECTIVE: As part of a quality assurance study of a physician-to-physician consultation program in Alberta, Canada, this environmental scan aims to identify the characteristics and outcomes of physician-to-physician telephone consultation programs across several countries. METHODS: We searched 7 databases to identify English publications in 2007-2017 describing physician-to-physician consultations using telephones as the main technology. To identify Canadian programs, the literature search was supplemented with an additional internet search. RESULTS: The literature search yielded 2336 citations, of which 17 publications were included. Across 7 countries, 14 telephone consultation programs provided primary care providers with access to various specialists through hotlines, paging systems, or call centers. The programs reported on the avoidance of hospitalizations, emergency department visits and specialty visits, caller satisfaction with the telephone consultation, and cost avoidance. CONCLUSIONS: Telephone consultation programs between health care providers have facilitated access to specialist care and prevented acute care use. .
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.018 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".