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Record W3030393818 · doi:10.1186/s12961-020-00574-0

Key factors for national spread and scale-up of an eConsult innovation

2020· article· en· W3030393818 on OpenAlexafffundabout
Isabella Moroz, Douglas Archibald, Mylaine Breton, Élizabeth Côté-Boileau, Lois M. Crowe, Tanya Horsley, Lirjie Hyseni, Gina Johar, Katharina Kovacs Burns, Craig Kuziemsky, Jim Laplante, Ariana Mihan, L. Oppenheimer, Don Sturge, Delphine S. Tuot, Clare Liddy

Bibliographic record

VenueHealth Research Policy and Systems · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsCARE CanadaUniversity of ManitobaOttawa HospitalBruyèreRoyal College of Physicians and Surgeons of CanadaMacEwan UniversityAlberta Health ServicesUniversité de SherbrookeUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsHealth services researchContext (archaeology)StakeholderThematic analysisScale (ratio)Health carePublic relationsHealth administrationHealth informaticsHealth policyPopulationPopulation healthQualitative researchPublic healthMedicineKnowledge managementEconomic growthNursingPolitical scienceSociologyEnvironmental healthGeographySocial scienceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Expanding healthcare innovations from the local to national level is a complex pursuit requiring careful assessment of all relevant factors. In this study (a component of a larger eConsult programme of research), we aimed to identify the key factors involved in the spread and scale-up of a successful regional eConsult model across Canada. METHODS: We conducted a constant comparative thematic analysis of stakeholder discussions captured during a full-day National eConsult Forum meeting held in Ottawa, Canada, on 11 December 2017. Sixty-four participants attended, representing provincial and territorial governments, national organisations, healthcare providers, researchers and patients. Proceedings were recorded, transcribed and underwent qualitative analysis using the Framework for Applied Policy Research. RESULTS: This study identified four main themes that were critical to support the intentional efforts to spread and scale-up eConsult across Canada, namely (1) identifying population care needs and access problems, (2) engaging stakeholders who were willing to roll up their sleeves and take action, (3) building on current strategies and policies, and (4) measuring and communicating outcomes. CONCLUSIONS: Efforts to promote innovation in healthcare are more likely to succeed if they are based on an understanding of the forces that drive the spread and scale-up of innovation. Further research is needed to develop and strengthen the conceptual and applied foundations of the spread and scale-up of healthcare innovations, especially in the context of emergent learning health systems across Canada and beyond.

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
Other designmedium
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.929
GPT teacher head0.761
Teacher spread0.168 · 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.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations27
Published2020
Admission routes3
Has abstractyes

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