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Record W2972320355 · doi:10.1136/bmjgh-2019-001629

Barriers and facilitators for implementation of electronic consultations (eConsult) to enhance access to specialist care: a scoping review

2019· review· en· W2972320355 on OpenAlexafffund
Mohamed A. Osman, Kara Schick‐Makaroff, Stephanie Thompson, Liza Bialy, Robin Featherstone, Julia Kurzawa, Deenaz Zaidi, Ikechi G. Okpechi, Syed Shahid Habib, Soroush Shojai, Kailash Jindal, Branko Braam, Clare Liddy, Braden Manns, Marcello Tonelli, Brenda R. Hemmelgarn, Scott Klarenbach, Aminu K. Bello

Bibliographic record

VenueBMJ Global Health · 2019
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsOttawa HospitalBruyèreUniversity of OttawaUniversity of CalgaryUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta InnovatesUniversity of AlbertaFaculty of Medicine and Dentistry, University of AlbertaAmgen
KeywordsNursingPublic healthMedicineBusiness

Abstract

fetched live from OpenAlex

INTRODUCTION: Electronic consultation (eConsult)-provider-to-provider electronic asynchronous exchanges of patient health information at a distance-is emerging as a potential tool to improve the interface between primary care providers and specialists. Despite growing evidence that eConsult has clinical benefits, it is not widely adopted. We investigated factors influencing the adoption and implementation of eConsult services. METHODS: We applied established methods to guide the review, and the recently published Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews to report our findings. We searched five electronic databases and the grey literature for relevant studies. Two reviewers independently screened titles and full texts to identify studies that reported barriers to and/or facilitators of eConsult (asynchronous (store-and-forward) use of telemedicine to exchange patient health information between two providers (primary and secondary) at a distance using secure infrastructure). We extracted data on study characteristics and key barriers and facilitators were analysed thematically and classified using the Quadruple Aim framework taxonomy. No date or language restrictions were applied. RESULTS: Among the 2579 publications retrieved, 130 studies met eligibility for the review. We identified and summarised key barriers to and facilitators of eConsult adoption and implementation across four domains: provider, patient, healthcare system and cost. Key barriers were increased workload for providers, privacy concerns and insufficient reimbursement for providers. Main facilitators were remote residence location, timely responses from specialists, utilisation of referral coordinators, addressing medicolegal concerns and incentives for providers to use eConsult. CONCLUSION: There are multiple barriers to and facilitators of eConsult adoption across the domains of Quadruple Aim framework. Our findings will inform the development of practice tools to support the wider adoption and scalability of eConsult implementation.

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)0.068
metaresearch head score (Gemma)0.224
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 score0.068
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.224
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0130.016
Science and technology studies0.0010.002
Scholarly communication0.0060.005
Open science0.0030.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.060
GPT teacher head0.510
Teacher spread0.450 · 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

Citations119
Published2019
Admission routes2
Has abstractyes

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