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Record W4243722288 · doi:10.2196/preprints.17672

Characteristics and Outcomes of Physician-to-Physician Telephone Consultation Programs: Environmental Scan (Preprint)

2020· preprint· en· W4243722288 on OpenAlexaffabout
Peter George Jaminal Tian, Jeffrey Harris, Hadi Seikaly, Thane Chambers, Sara Alvarado, Dean T. Eurich

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHotlineSpecialtyFamily medicineMedicineEmergency departmentMedical emergencyMEDLINENursing

Abstract

fetched live from OpenAlex

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.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.208
Threshold uncertainty score0.414

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0120.031
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.019
GPT teacher head0.246
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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