Pharmacists’ perceptions of the Canadian opioid regulatory exemptions on patient care and opioid stewardship
Bibliographic record
Abstract
BACKGROUND: This study explored the perceptions of Canadian pharmacists about the barriers and facilitators of providing opioid stewardship activities in pharmacy practice, considering the subsection 56(1) class exemption under Health Canada's Controlled Drugs and Substances Act (CDSA). METHODS: Qualitative key informant telephone interviews were conducted with a convenience sample of pharmacists from across Canada. We included community or primary health care team-based pharmacists who self-identified as having experience with providing care for patients using opioids via the exemptions. All transcripts were de-identified, and thematic analysis was conducted to identify themes. Ethics approval was obtained. RESULTS: Twenty pharmacists from community and primary health care teams, from all provinces and from urban and rural practices were interviewed. The following themes emerged: 1) optimization of opioid-related patient care, 2) jurisdictional impact and 3) awareness and education. Barriers and facilitators for opioid stewardship activities were identified. DISCUSSION: The exemptions facilitated the pharmacists' ability to provide opioid stewardship and positively affect patient care by providing continuity of and timely access to care. Our research demonstrated that pharmacists can responsibly and independently manage opioid prescriptions within this expanded scope, demonstrating the valuable contribution pharmacists can have in opioid stewardship. CONCLUSION: Pharmacists were willing and able to care for patients receiving opioid medication and thereby played a role in helping address the opioid crisis. The benefits of these exemptions were demonstrated beyond situations related to the COVID-19 pandemic and warrant consideration for consistent implementation across provincial and territorial jurisdictions, thereby ensuring equitable access to care for all Canadians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".