Measuring the Impact of Pharmacist Intervention: Results of Patient Education about Osteoporosis after Fragility Fracture
Bibliographic record
Abstract
ABSTRACT Background: Fragility fractures are physical manifestations of osteoporosis, yet studies show undertreatment of osteoporosis after such fractures. Objective: To determine the impact of pharmacist-initiated patient education on osteoporosis knowledge, modification of risk factors, and prescribed therapy after fragility fractures. Methods: A pilot educational intervention was prospectively evaluated over a 5-month period at Kingston General Hospital, Kingston, Ontario. Patients older than 45 years who had recently sustained a fragility fracture (n = 23) were contacted 12 to 14 weeks after an educational intervention to determine if their osteoporosis knowledge had improved, if they had modified their risk factors, and if discussion with the family physician had led to bone mineral density assessment and/or osteoporosis treatment. Postdischarge reviews of the subjects’ charts were used to determine if patients with fragility fracture were routinely assessed for osteoporosis at the study hospital. Results: The proportion of patients who had discussed osteoporosis with their physicians increased (p = 0.024), which led to greater use of antiresorptive agents (p Conclusions: Pharmacists can improve a patient’s knowledge of osteoporosis, stimulate discussion with their family physician, and influence treatment rates. However, single teaching sessions do not influence modifiable osteoporosis risk factors, so continuous encouragement may be necessary. RESUME Historique : Les fractures de fragilite osseuse sont une manifestation physique de l’osteoporose; malgre ce fait, les etudes montrent que le traitement de l’osteoporose est insuffisant a la suite de telles fractures. Objectif : Determiner l’impact d’une intervention educative entreprise par le pharmacien aupres des patients sur la connaissance de l’osteoporose, la modification des facteurs de risque et le traitement prescrit par suite d’une fracture de fragilite. Methodes : Une intervention educative pilote a ete evaluee de facon prospective sur une periode de cinq mois au Kingston General Hospital, a Kingston, en Ontario. De 12 a 14 semaines apres l’intervention educative, on a communique avec les patients de plus de 45 ans qui avaient souffert recemment d’une fracture de fragilite (n = 23) pour determiner s’ils avaient une meilleure connaissance de l’osteoporose, s’ils avaient modifie leurs facteurs de risque et s’ils avaient subi une evaluation de la densite minerale osseuse et (ou) recu un traitement contre l’osteoporose apres avoir consulte leur medecin de famille. L’examen des dossiers des patients ayant subi une fracture de fragilite a servi a determiner apres leur conge s’ils avaient fait systematiquement l’objet d’une evaluation relative a l’osteoporose a cet hopital. Resultats : La proportion de patients qui avaient discute d’osteoporose avec leur medecin avait augmente (p = 0,024), ce qui a entraine une plus grande utilisation d’inhibiteurs de la resorption osseuse (p Conclusions : Les pharmaciens peuvent ameliorer la connaissance qu’ont les patients de l’osteoporose, favoriser leurs discussions avec leur medecin de famille et exercer une influence sur les taux de traitement. En revanche, les seances d’information uniques n’ont aucun effet sur les facteurs de risque modifiables de l’osteoporose; un soutien suivi peut donc etre necessaire.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".