Purpose: Cochlear implant device use, quantified by hearing hours percentage (HHP), is a known variable that impacts pediatric spoken language outcomes. Isolating specific factors that impact HHP could help clinicians intervene to reduce the implications of barriers and amplify the positive facets. The aim of this study is to identify variables that predict HHP in children.
Method: A retrospective chart review was completed using data collected from 2019 to 2023. Subjects were included if they were under the age of 18 years at the time of data collection and had data logging recorded in the clinical patient database. A mixed-effects model weighed the influence of year of the clinical visit (2019, 2020, 2021, 2022, and 2023), race/ethnicity (White, African American, Asian, Hispanic, Mixed Race, or Other), listener type (bilateral simultaneous, sequential, bimodal, unilateral hearing loss, or unilateral listener; one cochlear implant and a contralateral deaf ear), insurance type (private, Medicaid, or military, or none), age at surgery, presence of autism spectrum disorder (ASD) or an intellectual development delay (IDD), and age at test on HHP.
Results: There were a total of 5,106 data points from 958 subjects. The mean HHP of the cohort was 64.2% (SD = 26.94%). Lower HHP was associated with the presence of IDD or ASD, use of Medicaid, and older age at surgery. HHP increased with age. Subjects of color did not have a significantly different HHP than those who were White. There was an interaction between year of data collection and listener type. Each listener type's HHP was impacted differently by the year of data collection; however, years of the COVID-19 pandemic yielded lower HHP for all listener types.
Conclusions: The group mean of 64.9% is lower than the recommended 80% HHP goal, indicating that pediatric cochlear implant recipients have slightly more than half the access to sound as their age-matched typically hearing peers. Several variables that impact HHP were identified in this study. Cochlear implant teams can utilize these data to support vulnerable patients to increase HHP. Additional investigation is needed to determine what interventions most effectively improve HHP.