Take Control. Period. - Needs Assessment Leading to the Development of a Digital Quality Improvement Intervention Designed to Enhance Adherence to Tranexamic Acid and Iron Supplementation in Women with Heavy Menstrual Bleeding
Notice bibliographique
Résumé
Introduction Heavy menstrual bleeding (HMB) affects up to 51% of all women and 93% of those with bleeding disorders. It is essentially universally associated with iron deficiency +/- anemia (ID/IDA), resulting in substantial fatigue and reduced quality of life. Despite the large body of evidence to support the use of tranexamic acid (TXA) in reducing HMB, in the real world, many patients report difficulty taking this medication on a consistent basis. Adherence to oral iron supplementation is similarly poor, despite its seemingly straightforward use. Our goal was to further understand the problem of adherence to these oral medications in women with HMB and to begin developing a potential digital solution. Methods We performed a retrospective practice audit of an outpatient hematology clinic between November, 2018 and January, 2019 to determine the baseline adherence to prescribed TXA and oral iron in women with HMB. We then conducted a root-cause-analysis to identify common themes affecting medication adherence and opportunities for patient education. Key contributing factors were determined based on quality improvement (QI) team brainstorming, practice audit, qualitative survey of patients and practitioners, and review of literature. Results There were 252 clinical encounters with women ≤55 years-old during this time frame. Of these, 85 involved active management of HMB, with 47 cases already prescribed TXA. Only including days with ≥2 patients on TXA, the median adherence rate per clinic was 33%. There were 114 encounters involving management of ID/IDA due to HMB, with 57 already on oral iron. The median adherence rate per clinic with ≥2 patients on oral iron was 40%. Common barriers to TXA adherence identified by the patient/practitioner survey included: need to take at least two large tablets three times per day during bleeding; premature cessation of TXA due to the perception of it interfering with "normal" blood loss; high cost of oral TXA; difficulty with dose and frequency titration; common side effects including nausea, diarrhea, and headache; concern regarding the potential thromboembolic risk of TXA, and the synergistic thromboembolic risk with TXA and estrogen based therapies. Common concerns with oral iron were: difficulty managing gastrointestinal side effects; not taking iron on an empty stomach or with acidic foods/beverages; cessation of therapy before iron stores are replete; forgetting to take doses; and high cost of polysaccharide and heme-based iron supplements. Conclusions HMB negatively impacts the quality of life and productivity of women of reproductive age. There is a robust body of evidence supporting TXA and iron supplementation in this context. Despite best efforts at counselling on proper utilization of these agents in clinic, baseline adherence was only 33% to TXA and 40% to oral iron. We identified numerous barriers to adherence that are amenable to QI initiatives. Using these results, we have begun to develop a multimodal, interactive website for women with HMB to improve adherence to TXA and oral iron, called "Take Control. Period." Future steps will be to evaluate changes in adherence to TXA and oral iron per patient per clinic week prospectively after digital intervention implementation. Disclosures Sholzberg: Novartis: Honoraria; Amgen: Honoraria, Research Funding.
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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 | 0,005 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,002 |
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 ».