Supporting Chronic Pain Management across Provincial and Territorial Health Systems in Canada: Findings from Two Stakeholder Dialogues
Bibliographic record
Abstract
BACKGROUND: Chronic pain is a serious health problem given its prevalence, associated disability, impact on quality of life and the costs associated with the extensive use of health care services by individuals living with it. OBJECTIVE: To summarize the research evidence and elicit health system policymakers', stakeholders' and researchers' tacit knowledge and views about improving chronic pain management in Canada and engaging provincial and territorial health system decision makers in supporting comprehensive chronic pain management in Canada. METHODS: For these two topics, the global and local research evidence regarding each of the two problems were synthesized in evidence briefs. Three options were generated for addressing each problem, and implementation considerations were assessed. A stakeholder dialogue regarding each topic was convened (with 29 participants in total) and the deliberations were synthesized. RESULTS: To inform the first stakeholder dialogue, the authors found that systematic reviews supported the use of evidence-based tools for strengthening chronic pain management, including patient education, self-management supports, interventions to implement guidelines and multidisciplinary approaches to pain management. While research evidence about patient registries/treatment-monitoring systems is limited, many dialogue participants argued that a registrysystem is needed. Many saw a registry as a precondition for moving forward with other options, including creating a national network of chronic pain centres with a coordinating 'hub' to provide chronic pain-related decision support and a cross-payer, cross-discipline model of patient-centred primary health care-based chronic pain management. For the second dialogue, systematic reviews indicated that traditional media can be used to positively influence individual health-related behaviours, and that multistakeholder partnerships can contribute to increasing attention devoted to issues on policy agendas. Dialogue participants emphasized the need to mobilize behind an effort to build a national network that would bring together existing organizations and committed individuals. CONCLUSIONS: Developing a national network and, thereafter, a national pain strategy are important initiatives that garnered broad-based support during the dialogues. Efforts toward achieving this goal have been made since convening the dialogues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".