Background: Medication nonadherence rates as high as 50-75% have been widely reported in children and adolescents with chronic medical conditions. Anticoagulation nonadherence is associated with increased morbidity and mortality from hemorrhagic and thrombotic complications, reported mostly in older adult populations. As direct oral anticoagulant use increases, it is critical that pediatric clinicians understand the prevalence, adverse sequelae, and predictors of nonadherence for various anticoagulants prescribed for children and young adults to facilitate self-management in this population. To begin to address these critical knowledge gaps, this study explored the frequency of reported barriers to anticoagulation adherence and the relationship between reported barriers and adherence among a cohort of children and young adults who were prescribed anticoagulants through a pediatric thrombosis clinic.
Methods: Data for this abstract were collected as part of a quality improvement (QI) initiative in the pediatric thrombosis clinic from May 2019 to November 2019. This QI initiative included the administration of a self-report measure which asked families to rate the presence/absence of 19 barriers to adherence and respond to two items assessing adherence ("How many anticoagulation doses did you/your child miss in the past 7 days?"; "Did you/your child miss any anticoagulation doses in the past month?"). Patients aged > 10 years (yr.) and/or their caregivers (for patients 0-17 yr.) visiting the clinic for anticoagulation follow-up completed the measure. With IRB approval, results from 161 anonymous measures from 130 families (n = 37 caregivers; n = 62 patients; n = 31 patient/caregiver dyads) were analyzed. Descriptive statistics were used to summarize the most frequent barriers, rates of adherence, and concordance of barriers within patient/caregiver dyads. Linear regression was used to explore relationships between barriers and adherence after controlling for medication administration type (injections versus oral). To ensure only one measure per family was included in this analysis, the regression was run on the subset of measures completed by caregivers of children < 18 yr. and patients ≥ 18 yr. (n = 105 [37 caregivers + 62 patients + 31 caregivers from patient/caregivers dyad = 130 families; 130 - 25 families with missing adherence data = 105 families]).
Results: Of 161 reporters, 120 reported at least 1 barrier. The most common barriers were medication side effects (n = 44), alterations in lifestyle secondary to medication (n = 44) and forgetting to take the medications (n = 37). The distributions of barriers by reporter and medication type are illustrated in Figure 1. Of 31 dyads, 26 reported 1 or more barriers. Only 6 caregiver/child dyads reported the same set of barriers. The remaining 77% (n = 20) of caregivers endorsed different barriers than their children.
On average, patients and caregivers reported 1.85 barriers (SD = 1.95, range 0 - 10) and that they/their child took 96% of prescribed doses (SD= 9%, range = 71 - 100%). The linear regression was significant (F(2, 102) = 4.19, p = 0.02, R2 = 0.08). After controlling for medication type (p = 0.06), a greater number of barriers was significantly associated with lower adherence (t = -2.63, p = 0.01). Every one unit increase in total barriers (1 additional barrier reported) was associated with a decrease of .26% in adherence.
Discussion: Although self-reported adherence was high, 75% of patients and caregivers reported 1 or more barriers to adherence. A greater number of barriers is associated with lower adherence, regardless of medication route, suggesting that addressing reported barriers might improve adherence. The spectrum of reported barriers was diverse, differing even within patient and caregiver dyads. Therefore, it is important to evaluate both patients and caregivers to fully assess the burden of barriers. Future studies are needed to evaluate the impact of addressing barriers and the relationship between anticoagulation adherence, barriers, and health outcomes.
Figure 1
Disclosures
Luchtman-Jones: Corgenix: Other: Provided discounted kits for study; Accriva Diagnostics: Other: Provided kits for study.
Effect of Economic Growth on Poverty in Bima City
