Patient Adherence to Medication within a New Multidisciplinary Thrombosis Service
Notice bibliographique
Résumé
BACKGROUND Poor medication adherence puts patients who require thrombosis care at greater risk of complications. Little is known about the impact of multidisciplinary care models on medication adherence in patients requiring anticoagulation management. It is also unclear from the literature whether adherence varies in clinical practice with the advent of direct oral anticoagulants (DOACs) which have shorter half-lives and require limited or no laboratory monitoring compared to vitamin-K antagonists. We started a new multidisciplinary Adult Outpatient Thrombosis Service (TS) in October 2017 in a Canadian health authority servicing over 300 000 people. The TS is a comprehensive thrombosis and anticoagulation management program with unique, interrelated clinics providing the spectrum of care required for this patient group. The TS includes an Emergency Thrombosis Clinic for care after an acute episode of venous thromboembolism; Thrombosis Clinics addressing non-urgent thrombosis and anticoagulation questions and follow up; Anticoagulation Management Clinics for long term follow up of patients on anticoagulation; and a Perioperative Anticoagulation Management Clinic for patients on anticoagulation requiring surgery or procedures. The TS is staffed by Pharmacists, a Thrombosis Physician/Hematologist, and Clerical staff. The objective of the survey was to assess self-reported medication adherence of patients within the TS. PATIENTS/METHODS We conducted a cross-sectional survey of patients who were consulted to the TS between October 2017 and May 2019. Eligible patients were mailed an anonymous survey with a cover letter and self-addressed, return stamped envelope. Adherence to medication was assessed using the 12-item validated Adherence to Refills and Medications Scale (ARMS). The ARMS utilizes a 4 point scale (1-4), with the continuous score range of 12 to 48, and lower scores indicating better adherence. Baseline characteristics and patient satisfaction with the TS were evaluated for association with medication adherence. Linear regression analysis was used to examine the associations between patient's characteristics, their satisfaction with TS and medication adherence. RESULTS Of 1058 eligible patients, 563 responded to the survey representing a response rate of 53%. Seventeen were excluded who had more than 6 missing responses to the ARMS items. Out of remaining 546 patients with complete responses 55% (n=297) were on DOACs, 19% (n=102) on warfarin, 5.0% (n=27) on low molecular weight heparin (LMWH), 3.3% (n=18) on antiplatelet therapy and 18% (n=96) were not receiving anticoagulation therapy at the time of completing the survey. Nearly half had taken anticoagulant for 1 to 5 years (47%, n=253) while 28% (n=150) and 25% (n=137) had been on an anticoagulant for less than 1 year and more than 5 years respectively. Most patients (87%, n=475) were 50 years of age or older and half (51%, n=277) were male. About two-thirds (67%, n=360) had at least post-secondary education. The mean score for the ARMS was 13.9 (SD 2.2, range 12 to 25). Most patients (88%, n = 481) reported high adherence to medication (ARMS score = 12-16). In univariate analysis, post-secondary education (β = 0.0052, p = 0.006) and patient satisfaction with the TS (β = 0.0004; p = 0.019) significantly predicted medication adherence among participants. In multivariate analyses education (β = 0.0039, p = 0.048) and duration of anticoagulant use (β = 0.0047, p = 0.0244) were significantly associated with medication adherence. The internal consistency reliability for the ARMS tool was acceptable (Cronbach's alpha = 0.70). CONCLUSIONS Self-reported medication adherence was high (88%) in patients seen at a multidisciplinary TS. Post-secondary education and duration of anticoagulant use were important predictors of medication adherence. Disclosures Young: Sanofi Canada: Honoraria, Research Funding; Bayer: Research Funding; Pfizer: Honoraria. Chitsike:Bayer Canada: Research Funding; Sanofi Canada: Honoraria, Research Funding.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,004 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».