Long term outcomes of chronic pain patients attending a publicly funded community-based interdisciplinary pain program in the Greater Toronto area: results of a practice-based audit
Bibliographic record
Abstract
BACKGROUND: Chronic pain management multi/interdisciplinary programs attempt to address all elements of the biopsychosocial model. The primary objective of this retrospective study (based on practice-based audit) was to determine the effectiveness of a patient-centered, comprehensive and intense interdisciplinary pain management program in a publicly funded community-based pain clinic in the Greater Toronto Area. METHOD: This retrospective longitudinal study was conducted on 218 carefully selected sequential chronic pain patients, with 158 completing a 3-4-month interdisciplinary program between January 2016 and December 2018. Data collected upon exit, at 6 months and 12 months post-discharge included demographic information, pain characteristics, emotional/functional status obtained by validated instruments and global impression of change (GIC). Additionally, social health outcomes (return to work or school) were retrieved through retrospective chart review. Means of pre-and post-program variables were compared to assess changes of each patient's "journey". RESULTS: Physical and mental/ emotional health outcomes at exit, 6 months and 12 months post-discharge, showed initial and sustained, statistically and clinically significant improvement from pre-treatment levels, with GIC (much/very much improved) reported as 77%, 58% and 76%, respectively. Additionally, a substantial positive change in social health outcomes was noted particularly in patients on disability (29%), part time workers gaining full time employment (55%), and students (71%) who improved their level of schooling. CONCLUSION: The study showed that careful patient selection in a community-based publicly funded interdisciplinary pain management program can produce significant improvement in pain, physical, mental/emotional health and social function, with sustained long-term outcomes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".