Barriers and facilitators for implementation of electronic consultations (eConsult) to enhance specialist access to care: a scoping review protocol
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Electronic consultations (eConsult), asynchronous exchanges of patient health information at a distance, are increasingly used as an option to facilitate patient care and collaboration between primary care providers and specialists. Although eConsult has demonstrated success in increasing efficiency in the referral process and enhancing access to care, little is known about the factors influencing its wider adoption and implementation by end users. In this paper, we describe a protocol to conduct a scoping review of the literature on the barriers and facilitators to a wider adoption and implementation of eConsult service. METHODS AND ANALYSIS: . We will use the guidance for scoping reviews developed by the Joanna Briggs Institute to report our findings. In addition to several electronic databases (Medline, Embase, Cochrane Library, CINAHL, EBSCOhost and PsycINFO) studies will be identified by including relevant grey literature. Two reviewers will independently screen titles and full texts for inclusion. Studies reporting on barriers and/or facilitators in settings similar to eConsult will be included. Data on study characteristics and key barriers and facilitators will be extracted. Data will be analysed thematically and classified using the Quadruple Aim framework. ETHICS AND DISSEMINATION: Approval by research ethics board is not required since the review will only include published and publicly accessible data. Review findings will be used to inform future studies and the development of practice tools to support the wider adoption and success of eConsult implementation. We plan to publish our findings in a peer-reviewed journal and develop a useful and accessible summary of the results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it