Bibliographic record
Abstract
BACKGROUND: The prevalence of chronic pain is high and increasing. Medication management is an important component of chronic pain management. There is a shortage of physicians who are available and comfortable providing this service. In Alberta, pharmacists have been granted an advanced scope of practice. Given this empowerment, their availability, training and skill set, pharmacists are well positioned to play an expanded role in the medication management of chronic pain sufferers. OBJECTIVE: To compare the effectiveness and cost of a physician-only vs a pharmacist-physician team model of medication management for chronic nonmalignant pain sufferers. METHOD: Data was analyzed for 89 patients who had received exclusively medication management at a rural Alberta multidisciplinary clinic. 56 were managed by a sole physician. 33 were managed by a team (pharmacist + physician). In the team model, the physician did the medical assessment, diagnosis, and established a treatment plan in consultation with the patient and pharmacist. The pharmacist then provided the ongoing follow-up including education, dose titration and side effect management and consulted with the physician as needed. Change in pain (Numerical Rating Scale) and disability (Pain Interference Questionnaire) over the course of treatment were recorded. The treatment duration and number of visits were used to calculate cost of care. RESULTS: Both models of medication management resulted in significant and comparable improvements in pain, disability and patient perception of medication effectiveness. Patients in the physician-only group were seen more frequently and at a greater cost. The pharmacist-physician team approach was markedly more cost-effective, and patients expressed a high level of satisfaction with their medication management. CONCLUSIONS: The pharmacist-physician team model of medication management results in significant reductions of pain and disability for chronic nonmalignant pain sufferers at a reduced cost and is well accepted by patients.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".