SAFER-OPIOIDS
Bibliographic record
Abstract
Chronic noncancer pain (CNCP) affects a considerable and increasing number of Canadians.1 Opioids have been demonstrated to reduce pain intensity in CNCP conditions; however, their use also presents risks and potential adverse effects.1 The Canadian Guideline for Safe and Effective Use of Opioids for Chronic Non-Cancer Pain recognizes that pharmacists need to take responsibility for assessing risks of opioid therapy and minimizing harm.1 Recent attention in the media about these risks reinforces the need for pharmacists to be proactive in assessing and monitoring opioid therapy.2 The removal of OxyContin from the market has also prompted a call to action for pharmacists and physicians to work collaboratively around dose changes and to reduce prescription fraud.1,3 Use of a structured approach for pharmacists to assess all patients on opioid therapy is important to ensure comprehensiveness and to avoid specific patients feeling targeted. Patients on opioid therapy may feel stigmatized because of recent increased media coverage about its harms, including the risk of addiction. Patients should play an active role in facilitating the safest possible use of opioids, and pharmacists can reinforce patient education with accurate information.1 Clinical pharmacists from the University Health Network (UHN) and the Centre for Addiction and Mental Health (CAMH) work collaboratively in an ambulatory program to provide detailed medication assessments focused on opioid therapy. They found that, when contacted for information, pharmacists in the community often reported that they were concerned about their patients’ opioid therapy; however, they felt that they did not have enough information about the indication or treatment plan to complete an assessment. These subjective reports are consistent with survey results from 2011 about Ontario pharmacists’ experiences dispensing opioids; of 642 respondents, most (86%) reported that they were concerned about the prescription opioid use of several or many of their patients.4 Respondents from this survey felt that physicians often failed to recognize that pharmacists can help with opioid management; 56% reported that physicians were unwilling to communicate their therapeutic plans to the pharmacists; and 61% reported that physicians sometimes or frequently did not respond to their concerns.4 Based on the structure of standardized assessments performed in the ambulatory clinic, a mnemonic to trigger identification of key information and a thorough and efficient assessment of patients’ opioid therapy was created to help pharmacists take responsibility for opioid management in their practice. Components of the tool were based on the pharmaceutical care process but, to facilitate a simple mnemonic phrase (SAFER-OPIOIDS; Box 1), they are not in the recommended order for consideration of indication, efficacy, safety and convenience.5 Box 1 SAFER-OPIOIDS mnemonic tool Side effects Aberrant behaviours Function Effect on pain Collaborative Relationship with physician Over the watchful dose of 200 mg morphine equivalents Pill count Interactions Opioid treatment agreement Indication Psychiatric Diagnosis Substance use
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.336 | 0.067 |
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".