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Record W3001657778 · doi:10.2147/por.s213966

<p>Patient, Rheumatologist and Therapist Perspectives on the Implementation of an Allied Health Rheumatology Triage (AHRT) Initiative in Ontario Rheumatology Clinics</p>

2020· article· en· W3001657778 on OpenAlexafffundabout
Laura Mary Fullerton, Sydney Brooks, Raquel Sweezie, Vandana Ahluwalia, Claire Bombardier, Anna R. Gagliardi

Bibliographic record

VenuePragmatic and Observational Research · 2020
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of TorontoArthritis SocietyWilliam Osler Health SystemToronto General Hospital
FundersArthritis Society
KeywordsRheumatologyMedicineTriageInternal medicineFamily medicineAlternative medicinePhysical therapyPsychiatryPathology

Abstract

fetched live from OpenAlex

PURPOSE: The objective of this qualitative study was to explore patient, rheumatologist, and extended role practitioner (ERP) perspectives on the integration of an allied health rheumatology triage (AHRT) intervention in Ontario rheumatology clinics. Triage is the process of identifying the urgency of a patient's condition to ensure they receive specialist care within an appropriate length of time. This research explores the clinical/logistical impact of triage by occupational and physical therapists with advanced arthritis training (ERPs), including facilitators and barriers of success, and recommendations for future application. PARTICIPANTS AND METHODS: Semi-structured telephone interviews were held with participating rheumatologists, ERPs, and a sample of patients from each clinical site (4 community, 3 hospital) in five Ontario cities. Interviews were audio-recorded and transcribed verbatim. Transcripts were analyzed using basic qualitative description. Two independent researchers compared coding and achieved consensus. RESULTS: Patients (n=10), rheumatologists (n=6), and ERPs (n=5) participated in the study and reported reduced wait-times to rheumatology care, diagnosis, and treatment for those with inflammatory arthritis (IA). Rheumatologists and ERPs perceived that the intervention improved clinical efficiency and quality of care. Patients reported high satisfaction with ERP assessments, valuing early joint examination/laboratory tests, urgent referral if needed, and the provision of information, support, and management strategies. Facilitators of success included: supportive clinical staff, regular communication and collaboration between rheumatologist and ERP, and sufficient clinical space. Recommendations included extending ERP roles to include stable patient follow-up, and ERP care between scheduled rheumatology appointments. CONCLUSION: Findings support the integration of ERPs in a triage role in the community and hospital-based rheumatology models of care. Future research is needed to explore the impact of utilizing ERPs for stable patient follow-up in rheumatology settings.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.008
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.131
GPT teacher head0.416
Teacher spread0.284 · 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 designQualitative
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

Citations4
Published2020
Admission routes3
Has abstractyes

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