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Record W3109462883 · doi:10.1503/cjs.015519

Strategies to improve communication in telementoring in acute care coordination: a scoping review

2020· review· en· W3109462883 on OpenAlexaffvenue
Lauren A. Hampton, Peter G. Brindley, Andrew W. Kirkpatrick, Jessica McKee, Julian Regehr, Douglas Martin, Anthony LaPorta, Jason Park, Ashley Vergis, Lawrence M. Gillman

Bibliographic record

VenueCanadian Journal of Surgery · 2020
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of ManitobaUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineCardiopulmonary resuscitationMEDLINEMedical emergencyStandardizationHealth careInterpersonal communicationMedical educationResuscitationEmergency medicineComputer science

Abstract

fetched live from OpenAlex

Background: Telementoring facilitates the coordination of advanced medical care in rural, remote or austere environments. Because the interpersonal element of telementoring has been relatively underexplored, we conducted a scoping review to identify strategies to improve communication in telementoring. Methods: Two independent reviewers searched all English-language articles in MEDLINE and Scopus from 1964 to 2017, as well as reference lists of relevant articles to identify articles addressing telementored interactions between health care providers. Search results were gathered in June 2017 and updated in January 2018. Identified articles were categorized by theme. Results: We identified 144 articles, of which 56 met our inclusion criteria. Forty-one articles focused on improving dispatcher-directed cardiopulmonary resuscitation (CPR). Major themes included the importance of language in identifying out-of-hospital cardiac arrest and how to provide instructions to enable administration of effective CPR. A standardized approach with scripted questions was associated with improved detection of out-of-hospital cardiac arrest, and a concise script was associated with improved CPR quality compared to no mentoring, unscripted mentoring or more complex instructions. Six articles focused on physician-physician consultation. Use of a handover tool that highlighted critical information outperformed an unstructured approach regarding transmission of vital information. Nine articles examined telementoring in trauma resuscitation. A common theme was the need to establish an understanding between mentor and provider regarding the limitations of the provider and his or her environment. Conclusion: The available data suggest that standardization coupled with short, concise validated scripts could improve efficacy, safety and engagement. Improvements will require multidisciplinary input, practice and deliberate efforts to address barriers.

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

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)0.030
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.108
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0230.019
Science and technology studies0.0010.001
Scholarly communication0.0050.007
Open science0.0030.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.057
GPT teacher head0.369
Teacher spread0.311 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2020
Admission routes2
Has abstractyes

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