Implementation of the Ottawa Hospital Pain Clinic stepped care program: A preliminary report
Bibliographic record
Abstract
BACKGROUND: Access to multidisciplinary pain management treatment in Canada is limited, with wait times up to 4 years. Stepped care approaches to mental health treatment have led to substantial reduction and elimination of wait times and may be applicable to chronic pain settings. There is no unifying framework for stepped care chronic pain programs. A systematic review of the efficacy of stepped care in chronic pain management conducted by the Canadian Agency for Drugs and Technologies reported varied results that may be due to heterogeneous stepped care models across facilities. AIM: We propose a unifying framework for multidisciplinary stepped care chronic pain programs and present its application at The Ottawa Hospital Pain Clinic. The Ottawa Hospital stepped care framework is an eight-tiered approach that allows patients the opportunity to decide collaboratively with a health care professional which treatment program will best suit their needs for the management of chronic pain. As levels of stepped care increase, the time and resource commitment to each step will also increase. Treatment is stepped up or down, depending on patient needs. METHOD: This is a descriptive case study. RESULTS: Implementing the interprofessional model of care with the stepped care program has eliminated wait times for access to The Ottawa Hospital Pain Clinic Interprofessional Chronic Pain Management Program and has improved communication between professions of the interprofessional team, resulting in better care for patients. CONCLUSION: More research is needed to further develop and evaluate the clinical efficacy of stepped care to manage chronic pain.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".