Stakeholder Priorities for Comparative Effectiveness Research in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Comparative effectiveness research (CER) is intended to address the expressed needs of patients, clinicians, and other stakeholders. Representatives of 54 stakeholder groups with an interest in chronic obstructive pulmonary disease (COPD) participated in workshops convened by the COPD Outcomes-based Network for Clinical Effectiveness and Research Translation (CONCERT) over a 2-year period. Year 1 focused on chronic care and care coordination. Year 2 focused on acute care and transitions in care between healthcare settings. Discussions and provisional voting were conducted via teleconferences and e-mail exchanges before the workshop. Final prioritization votes occurred after in-person discussions at the workshop. We used a modified Delphi approach to facilitate discussions and consensus building. To more easily quantify preferences and to evaluate the internal consistency of rankings, the Analytic Hierarchy Process was incorporated in Year 2. Results of preworkshop and final workshop voting often differed, suggesting that prioritization efforts relying solely on requests for topics from stakeholder groups without in-person discussion may provide different research priorities. Research priorities varied across stakeholder groups, but generally focused on studies to evaluate different approaches to healthcare delivery (e.g., spirometry for diagnosis and treatment, integrated healthcare strategies during transitions in care) rather than head-to-head comparisons of medications. This research agenda may help to inform groups intending to respond to CER funding opportunities in COPD. The methodologies used, detailed in the online supplement, may also help to inform prioritization efforts for CER in other health conditions.
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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 | 0.752 | 0.663 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".