SAFER-OPIOIDS
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,336 | 0,067 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».