The Impact of a Primary Care, Pharmacist-Driven Intervention in Patients with Chronic Non-Cancer Pain—A Pilot Study
Bibliographic record
Abstract
Background: Chronic pain is a prevalent condition, experienced by 15.3% to 55% of Canadians, that is difficult to manage. With their broad accessibility and expertise on drugs, primary care pharmacists can help patients optimize their pain management. Methods: The objective of this study is to examine the effectiveness of a primary care, pharmacist-driven chronic pain intervention on pain and quality of life in patients with chronic non-cancer pain. A three-month naturalistic prospective study was conducted in primary care settings (five community pharmacies and one Family Health Team) across Ontario, Canada with a total of six pharmacists and 19 study participants. The primary care, pharmacist-driven chronic pain intervention consisted of patient assessments, medication reviews, care plan recommendations, and patient education. In order to evaluate the effectiveness of the intervention, pain intensity, pain interference, and quality of life were evaluated at baseline and at follow up (week 2 and month 3). Results: Trends towards improvement in pain and quality of life were found, however, these improvements were not statistically significant at follow up (month 3). Conclusions: This study provides the foundational research required to better understand the impact of Ontario pharmacists’ extended role in pain management in non-cancer patients within multiple primary care settings (e.g., Family Health Team, etc.) and has illustrated the importance of modifying and customizing care plans in patients with chronic pain. A larger sample size with tailored outcome measures may be necessary to better highlight significant improvements in pain and quality of life in patients with chronic non-cancer pain using a primary care, pharmacist-driven intervention.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".