“Unspoken Questions”: A Qualitative Study of Rheumatologists’ Perspectives on the Clinical Implementation of Patient-reported Outcome Measures
Bibliographic record
Abstract
OBJECTIVE: To identify rheumatologists' views on perceived barriers and facilitators to the clinical implementation of patient-reported outcome measures (PROM). METHODS: Semistructured interviews were conducted with academically affiliated clinical rheumatologists. Interviews were audio-recorded and transcribed. Deidentified transcripts were independently coded and analyzed for themes. RESULTS: Fifteen attending rheumatologists, 8 women (53%) and 7 men (47%) with a mean of 17.3 years in practice (range 5-43) at 2 urban academic medical centers, participated in interviews. Rheumatologists identified several barriers to integrating PROM in clinical care, highlighting physician buy-in and culture change as significant challenges beyond logistical considerations. They further underscored the lack of effective interventions and resources for addressing the domains of most interest to patients. Physicians also recognized significant benefits of PROM in clinical care, including contributing to the clinical impression by providing the patient perspective, and promoting agenda setting by uncovering "unspoken questions." They additionally noted that PROM could support treatment planning, build patient-physician relationships, and facilitate patient engagement. Participants suggested that technology, physician education, and team-based care could facilitate the effective implementation of PROM. CONCLUSION: Rheumatologists identified multiple mechanisms through which PROM could augment clinical care, but also noted several obstacles to implementation, questioning the added value of PROM and the limited availability of interventions to improve patient-centered outcomes. Programs seeking to successfully integrate PROM to enhance patient-centered care and meet quality benchmarks should prioritize physician buy-in and training, and provide resources to address the outcomes that are measured.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.060 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".