An evaluation of the performance of the Opioid Manager clinical tool in primary care: A qualitative study
Bibliographic record
Abstract
AIMS: The Opioid Manager (OM) is a point-of-care paper tool for physicians, which summarizes the Canadian Guideline for Safe and Effective Use of Opioids for Chronic Non-Cancer Pain. To evaluate the efficacy of the OM, there is a need to better understand how physicians are using the OM, and how it is relevant to their practice. METHODS: Semistructured interviews were conducted with six family physicians in Ontario with clinical pain management experience. The interviews were analyzed using content analysis. The technique of "code-recode" was conducted by two analysts to verify content validity. RESULTS: The following main themes emerged: 1) OM as a communication tool; 2) OM as an educational tool; 3) OM as a clinical tool; 4) OM content/design; 5) OM benefits; 6) who the OM is used with; 7) OM potential; and 8) challenges of pain management. Physicians' commented the OM was a useful reference for helping their clinical decision making regarding opioids, and used it to educate and communicate with their patients/colleagues. Although many felt the content/design of the OM had a number of good features, there was a need for modifications (ie, merge with other tools and create electronic version). Given the challenges associated with pain management, a number of benefits were derived from using the OM (ie, protection and building therapeutic alliance), and respondents' felt the tool had the potential to meet a number of unmet needs related to opioid management. CONCLUSIONS: Overall, the OM was viewed positively for improving pain management practices but further work is required to refine the tool's potential.
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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 | 0.005 | 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 | 0.000 |
| 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".