MétaCan
Menu
Back to cohort
Record W3090028479 · doi:10.1111/1475-6773.13409

DISSEMINATION, IMPLEMENTATION, AND IMPACT

2020· article· en· W3090028479 on OpenAlexaffabout
Mylaine Breton, Mélanie Ann Smithman, Catherine Lamoureux‐Lamarche, Maxine Dumas Pilon, Gerard Farrell, Alexander Singer, Phil Woods, C. Bibeau, Véronique Nabelsi, Isabelle Gaboury, M.‐P. Gagnon, Carolyn Steele Gray, J. Shaw, Catherine Hudon, Kris Aubrey‐Bassler, Paula Louise Bush, Élizabeth Côté-Boileau, Jean-Sébastien Gagnon, Regina Visca, Clare Liddy

Bibliographic record

VenueHealth Services Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsBruyèreUniversity of OttawaMcGill UniversityCanadian HeritageUniversité LavalWomen's College HospitalUniversité du Québec en OutaouaisCanadian Patient Safety InstituteMemorial University of NewfoundlandBridgepoint Active HealthcareUniversity of ManitobaUniversité de Sherbrooke
Fundersnot available
KeywordsThematic analysisScale (ratio)Focus groupHealth carePopulationPublic relationsMedicineBusinessMedical educationMarketingEconomic growthPolitical scienceQualitative researchGeographySociologyEnvironmental healthEconomics

Abstract

fetched live from OpenAlex

Research Objective Effective health innovations are rarely scaled‐up—missing countless opportunities to improve health systems. Yet, little evidence exists on strategies to support large scale implementation of proven innovations. eConsult is an asynchronous online platform connecting primary care providers to specialists to discuss patients’ care, that improves access, patient experience, provider satisfaction, and reduces costs. eConsult services have been implemented in 16 countries, most widely in the United States and Canada. In Canada, each province has a single payer health system with universal coverage and efforts to scale‐up eConsult are underway in several provinces, with over 75 000 eConsult cases completed across the country thus far. This provides a unique opportunity to understand the strategies used to support scale‐up of this type of innovation across a range of contexts. Our objective is to present the strategies used to scale‐up eConsult in multiple jurisdictions. Study Design We conducted a multiple case study, where the cases were four Canadian provinces at varying stages of scaling‐up eConsult (Ontario, Quebec, Newfoundland and Labrador and Manitoba). Our data sources include document review (e.g., meeting minutes, reports, websites, presentations), meeting observations where provincial scale‐up of eConsult is discussed ( n = 26), semi‐structured interviews ( n = 25) and focus groups ( n = 2). We conducted deductive and inductive thematic analysis using Milat et al.’s scaling‐up conceptual framework (2016) to identify strategies and emerging themes. Population Studied Our study was conducted with key stakeholders (e.g., patients, family physicians, specialists, policy makers, decision makers) involved in the scaling‐up of eConsult in four Canadian provinces. Principal Findings We identified 6 common strategies used to support scaling‐up of eConsult in Canada : (a) Linking eConsult to research has helped develop and improve the innovation (e.g., technological infrastructure), establishing rigorous evidence to support the rationale for scaling‐up provincially, and maintaining eConsult activities during the scaling‐up process through funding and other resources; (b) building on a “coalition of the willing” by engaging partners who believe in the innovation and are willing to support it; (c) having physicians (both primary care and specialists) lead and adapt the innovation to their practice contexts, and relying on physician champions to help spread and scale the innovation; (d) engaging patient partners to strengthen the case to scale‐up eConsult through compelling patient stories and help drive scaling‐up efforts; (e) creating a “buzz” by engaging stakeholders across Canada, getting endorsements from organizations with influence, holding an annual national eConsult policy forum, presenting at various events, and building on other provinces’ experiences and expertise to help catalyze scale‐up efforts; (f) keeping the innovation simple to avoid becoming side‐tracked by peripheral challenges thus facilitating widespread adoption by physicians. Conclusions These strategies have been used in a range of contexts across Canada and are perceived by stakeholders as instrumental in scaling‐up efforts to date. The next step of this study is to foster cross‐level and cross‐jurisdictional knowledge exchange between key stakeholders. Implications for Policy or Practice This provides a new real‐world understanding of how stakeholders have tackled the challenges of scaling‐up eConsult and may be useful to inform future scaling‐up efforts for eConsult and similar innovations. Primary Funding Source Canadian Institutes of Health Research.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.067
GPT teacher head0.476
Teacher spread0.408 · 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 teacher head, not a consensus.

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

Citations3
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueHealth Services ResearchSame topicHealthcare Systems and TechnologyFrench-language works237,207