Notice bibliographique
Résumé
Reid McDonald and Anita Cumbleton have updated me on their new pharmacy that opened in June in Cochrane, Alberta. While traditional measures of prescription volume suggest a slow start, clinical services have been booming. And that’s by design. Indeed, over two-thirds of their income is from provision of clinical services. A great start indeed! What is striking to me is how these practitioners are taking advantage of a number of opportunities for patient-centred care and using these to drive the volume of clinical services. So far, this includes a 24-hour ambulatory blood pressure monitoring service, partnering with a psychologist for a patient who does not have a family physician, partnering with a physiotherapist and participating in the RxEACH study (a trial of cardiovascular risk reduction by pharmacists). In partnering with nonphysician practitioners, Anita and Reid can use their prescribing authority and medication review skills to provide timely and accessible patient-centred care. Their biggest challenge has been awareness in the community. Despite radio and print advertising, many people in the community of Cochrane are not aware of their pharmacy and their services. My guess is that if they continue setting themselves apart the way they have been, the word will spread throughout the community and they will flourish. Meanwhile, in Thunder Bay, Bryan Gray has also remarked that the traditional prescription business has been growing slowly. In speaking to him about opportunities, he says, “As pharmacists, we are sometimes too focused on our own profession. In order to collaborate, we should also learn about the practice and funding models of other clinicians—this will help us to ‘fit in’ with them.” Indeed, he has created an opportunity by offering his services to the nurse practitioners in 2 aboriginal health clinics, a day per week in each. Asked how he got in to these clinics, he states that he just “cold called” and offered his services. That is a bold approach that we need to see more often. In this case, he realized that primary care team members are salaried and get paid a flat fee to take care of patients. So, by understanding that payment model, he realized that offering his services would result in less work for them, increasing their capacity and range of services. Another opportunity that Bryan has been taking advantage of is Ontario’s Pharmaceutical Opinion program. He and his staff have been proactively reviewing patient profiles for drug interactions and drug therapy problems (using Lexi-Drugs to help). While pharmaceutical opinions pay much less than MedsCheck reviews, he says that his revenue from pharmaceutical opinions is actually higher than that from MedsChecks because patients can have more than one per year. It helps him to detect real or potential problems for his patients. Brilliant! At the risk of repeating myself, you can see a theme building here. It’s about looking for and seeking out opportunities to improve primary care. It’s time for pharmacists to be proactive and bold. ■
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 | 0,009 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,013 | 0,010 |
| Communication savante | 0,023 | 0,024 |
| Science ouverte | 0,002 | 0,025 |
| Intégrité de la recherche | 0,008 | 0,016 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,097 | 0,044 |
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 ».