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Record W4416028564 · doi:10.1016/j.apro.2025.100207

Prioritizing patient-reported outcome measures for routine collection in rheumatoid arthritis: An integrated consensus-building process with patients and health care providers

2025· article· en· W4416028564 on OpenAlexafffund
Racheal Githumbi, Steven J. Katz, Ania Kania‐Richmond, Kim Giroux, Yvonne Wallace, C Allyson Jones, Amanda Steiman, Anshula Ambasta, Cheryl Barnabé, Diane Lacaille, Elaine Yacyshyn, Glen Hazlewood, Jessica Widdifield, Claire Barber

Bibliographic record

VenueAdvances in Patient-Reported Outcomes · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsAlberta Bone and Joint Health InstituteUniversity of TorontoResearch CanadaUniversity of AlbertaUniversity of CalgaryUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsHealth careProcess (computing)Data collectionOutcome (game theory)MEDLINEWork (physics)

Abstract

fetched live from OpenAlex

Background: Effective clinical use of patient-reported outcome measures (PROMs) hinges on selecting appropriate measures.The aim of this study was to establish priorities for PROM routine collection in RA care at a health-system level based on patient and provider preferences.Methods: Candidate PROMs were identified through an environmental scan.We adopted a dual-panel consensus-building approach with a patient-exclusive panel, and separate engagement with rheumatology healthcare providers (HCPs).Consensus among patients with RA was established via a modified Delphi process, co-led with two patient partners.HCPs were engaged in a rating and discussion exercise with two groups of providers from academic centres.Patient-panel consensus was achieved if median ratings on a 9-point Likert scale were 7 in all 3 criteria (importance, content validity and feasibility) and results informed HCP discussions for final selection.Results: 15 patients with RA participated in the Delphi rounds and 22 HCPs participated in a rating exercise followed by two group discussions attended by a total of 43 rheumatologists.From an initial set of 15 candidate PROMs, 9 were rated highly ( 7) across all three criteria in Round 3 by patients.Among these, the PROMIS Physical Function 10a ranked highest.HCP feedback suggests a preference for PROMs that align with clinical documentation needs, including insurance forms for advanced therapies and disability claims. Conclusion:A measure of physical function achieved a high priority from the patient panel, and it also supports clinical documentation needs of HCPs, and will thus be an initial implementation focus. Keywords. rheumatoid arthritis patient-reported outcome measure Quality of CareOver the past half century, patient-reported outcome measures (PROMs) have been widely and effectively used alongside clinical, imaging, and laboratory assessments to evaluate and manage health outcomes in individuals living with rheumatoid arthritis (RA). [1][2]2][3][4] Their integration into clinical care has supported a patient-centered approach and enhanced communication between patients and providers. 5,6These benefits extend to clinicians and health systems by enabling consistent disease monitoring over time 5 and supporting quality improvement initiatives 7,8 that identify unmet needs at the systems-level to better inform policy and resource allocation decisions.Despite their proven value, the widespread implementation of PROMs in RA care is hindered by a lack of consensus on which specific measures are best suited for routine use.This uncertainty may reflect variation in patients, providers, and health systems valuing different aspects of care that best serve both RA patient needs and clinical workflows.In the context of increasing interest in value-based care and the development of learning health systems, 9,10 identifying consensus on PROMs that meet both clinical and patient needs is an important step toward

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.339
Teacher spread0.320 · 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.

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 routes2
Has abstractyes

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