Pharmacist-Led Follow-Up Program for Rural Acute Coronary Syndrome Patients: The PLURAL-ACS Study
Notice bibliographique
Résumé
Background: Rural patients have been shown to have reduced access to care, delayed discharge prescription fills, and frequent readmissions following acute coronary syndrome (ACS) compared to urban patients. While virtual and pharmacist-led programs have shown benefit in providing efficient care to cardiac patients, to our knowledge, their implementation in rural ACS-population have not been assessed. The purpose of this two-phase study was to implement a first-ever pharmacist-led virtual follow-up program for rural Canadian ACS patients and to determine the impact of the program as compared to a matched control group. Methods: Consecutive rural ACS-patients discharged from the Mazankowski Alberta Heart Institute between March-May 2022 were included in the pharmacist-led follow-up pilot program. Structured telephone interviews were used to identify and resolve cardiac medication-related issues for each patient on day 1, 10, and 30 post discharge. Descriptive outcomes of the program were collected, which included the total number and type of cardiac medication-related issues identified and resolved by the program and change in cardiac medication knowledge using questionnaires adapted from prior studies. Program-patients were then compared to a control group, which included ACS patients with usual care (discharged November 2021-July 2022), matched for sex, zone of residence, and age within 10 years. Outcomes were collected from administrative databases and multivariable regression analyses were conducted for comparisons. In the retrospective analysis, the primary outcome was time to prescription fill of discharge ACS-medications within 30 days of discharge. Secondary outcomes included 30-day cardiac-related hospital readmissions, cardiac-related emergency department visits, and primary care practitioner (PCP)-visits. Results: 40 patients entered the 15-week pilot-program and a total of 139 virtual visits were completed. Median time spent per visit was 60 (interquartile range [IQR], 50-80) minutes. A total of 255 cardiac medication-related issues (mean 6 per patient; IQR, 3.75-8.25) were identified, and 91% were resolved by the pharmacist. Discharge prescription errors, real adverse events, and therapy optimization were most common on day 1, 10, and 30 respectively. Cardiac medication knowledge was significantly increased in patients post program compared to their knowledge prior to program implementation (median score difference of 2.5 of 7; IQR, 2-4). When comparing the pilot program participants to matched control group (n=80), there was no significant differences in time to prescription fill (0.25 [IQR, 0.0-0.25] days vs 0 [IQR, 0.0-1.0] days; adjusted hazard ratio [aHR], 1.17; 95% confidence interval [CI], 0.80-1.74), cardiac-related hospital readmissions (8% vs 5%; aHR, 1.69; 95% CI, 0.36-7.96), or cardiac-related emergency department visits (10% vs 8%; HR 1.33; 95% CI, 0.38-4.73). PCP-visit was higher in the program patients (90% vs 73%; aHR, 2.99; 95% CI, 1.47-6.10). Conclusion: Our study highlights that a high number of cardiac medication-related issues are encountered by ACS patients early post hospital discharge. A pharmacist-run post ACS follow-up program identified and resolved majority of medication issues, as well as enhancing patient safety and overall follow-up of care as outpatient. Longer duration studies, with adequate power, are required to confirm these findings and assess the impact of such a program on clinical outcomes.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».