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Record W4414736735 · doi:10.3899/jrheum.2025-0683

Evaluating Implementation Context to Prepare for Scaling Up the Integration of Interdisciplinary Healthcare Providers in Rheumatology Practices: A Rheumatology Workforce Survey

2025· article· en· W4414736735 on OpenAlexafffundvenueabout
Jessica Widdifield, Celia Laur, Timothy S.H. Kwok, Laura Oliva, C. Thomas Appleton, Vandana Ahluwalia, Carter Thorne, Jenna Wong, Nicolas S. Bodmer, Jennifer J. Lee, Claire Barber, Laura Passalent, Lauren King

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity Health NetworkResearch CanadaSickKids FoundationArthritis Research Centre of CanadaThorneloe UniversityWilliam Osler Health SystemThornhill Medical (Canada)University of TorontoWestern UniversitySunnybrook HospitalWomen's College HospitalSt. Michael's HospitalSunnybrook Health Science CentreToronto Rehabilitation InstituteUniversity of CalgarySt Joseph's Health Care
FundersCanadian Institutes of Health ResearchUniversity of TorontoArthritis Society
KeywordsWorkforceContext (archaeology)RheumatologyHealth careMEDLINEWorkforce planning

Abstract

fetched live from OpenAlex

OBJECTIVE: Interdisciplinary healthcare providers (IHPs) can support effective delivery of optimal rheumatology care. To inform widespread implementation efforts, we assessed rheumatology workforce characteristics and determinants of integrating of IHPs within rheumatology practices in Ontario, Canada. METHODS: A convergent mixed methods design included an environmental scan to identify clinically active rheumatologists and a workforce survey guided by the Consolidated Framework for Implementation Research (CFIR) 2.0. Quantitative data were analyzed descriptively and stratified by subgroups. Qualitative responses were analyzed using conventional content analysis. Integration of findings enabled a comprehensive understanding of implementation determinants. RESULTS: Of the 293 Ontario rheumatologists identified by the environmental scan (as of 2025), 26 were nearing retirement, leaving potentially 267 eligible for the survey. One hundred ninety-seven rheumatologists participated in the survey, yielding a response rate of 74% and coverage of > 90% of practice sites. Pediatric rheumatologists and those in hospital-based settings had more structural and collaborative supports than community-based rheumatologists. Overall, 177 (91%) indicated they were interested in adding IHPs, with 126 (65%) preferring an extended role/scope provider. Although inadequate funding was the key deterrent to adoption, motivational readiness was high: 92% perceived an IHP team-based model as an improvement, 86% saw it as a good fit, and 83% considered it a priority to better meet patient needs. Many noted a lack of supportive climate, including that of resources and processes, to enable this practice change. CONCLUSION: Rheumatologists report high motivation for practice change to integrate IHPs. System- and practice-level implementation strategies are needed to support workforce transformation.

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)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.168
GPT teacher head0.584
Teacher spread0.416 · 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 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

Citations0
Published2025
Admission routes4
Has abstractyes

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