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Record W3168565872 · doi:10.2147/jmdh.s304206

An Advanced Clinician Practitioner in Arthritis Care (ACPAC) Maintains a Positive Patient Experience While Increasing Capacity in Rheumatology Community Care

2021· article· en· W3168565872 on OpenAlexaff
Vandana Ahluwalia, Taucha Inrig, Tiffany Larsen, Rachel Shupak, Tripti Papneja, Arthur Karasik, Carol Kennedy, Katie Lundon

Bibliographic record

VenueJournal of Multidisciplinary Healthcare · 2021
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity of TorontoEtobicoke General HospitalHeadwaters Health Care CentreSt. Michael's HospitalWilliam Osler Health System
Fundersnot available
KeywordsMedicineReferralRheumatologyPhysical therapyRheumatoid arthritisFamily medicineInternal medicineConfidence intervalPatient satisfactionArthritisNursing

Abstract

fetched live from OpenAlex

PURPOSE: This study describes patient care experiences of solo-rheumatologist and co-managed care models utilizing an Advanced Clinician Practitioner in Arthritis Care-trained Extended Role Practitioner (ACPAC-ERP) in three community rheumatology practices. MATERIALS AND METHODS: Patients with inflammatory arthritis (IA) were assigned to care provided by one of three (2 senior, 1 early-career) community-based rheumatologists (usual care), or an ACPAC-ERP (co-managed care) for the 6-months following diagnosis. Patient experiences were surveyed using validated measures of patient satisfaction (Patient Doctor Interaction Scale-PDIS), global ratings of confidence and satisfaction, referral patterns, disease activity (RADAI) and self-perceived disability (HAQ-Disability) as well as demographic information. Practice capacity was evaluated 18-months prior to, and across, the study period. RESULTS: Of 55 participants (mean age 56.6 years, 61.8% female), 33 received co-managed care. Most participants were diagnosed with rheumatoid arthritis (65.5%) with a median symptom duration of 1.1 years. At 6-months, patients from both models of care were equally satisfied in terms of the information provided (usual care 4.6 vs co-managed care 4.7/5=greater satisfaction), rapport with health-care provider (4.6 vs 4.6/5) and having needs met (4.7 vs 4.5/5). Overall satisfaction was high (87.2 vs 85.3/100=completely satisfied) as was confidence in the system by which care was received (85.0 vs 82.1/100=completely confident). Usual care patients reported higher perceived disability than co-managed patients (HAQ-Disability 0.5 vs 0.2/3=unable to do). Significant differences in overall RADAI score (p=0.014) were found between the two models. The senior rheumatologist, with a previously saturated practice, attained a 37% capacity increase for new patients utilizing the co-managed care model. CONCLUSION: The ACPAC-ERP model was equivalent to the solo-rheumatologist model with regard to patient experience and satisfaction. A co-management model utilizing a highly trained ACPAC-ERP can increase capacity in community rheumatology clinics for patients newly diagnosed with IA while maintaining confidence and satisfaction with their care.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.367
Teacher spread0.325 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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