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Objective To use data-logging technology to objectively track and identify predictors of hearing aid (HA) usage and aided sound exposure. Study Design Case series with planned data collection. Setting Tertiary academic medical center. Subjects and Methods Individuals with HAs between 2007 and 2016 were included (N = 431; mean, 74.6 years; 95% CI, 73.1-76.0). Data-logging technology intrinsic to new-generation HAs was enabled to track usage and sound exposure. With multivariable linear regression, age, sex, number of audiology visits, duration of audiologic follow-up, pure tone average, and HA side were assessed as predictors of usage (hours/day) and aided sound exposure (dB-hours/day; ie, "dose" of sound per day). Results Mean follow-up was 319 days (95% CI, 277-360). Mean HA usage was 8.4 hours/day (95% CI, 8.0-8.8; N = 431). Mean aided sound exposure was 440 dB-hours/day (95% CI, 385-493; n = 110). HA use (β < 0.001, P = .45) and aided sound exposure (β = -0.006, P = .87) were both stable over time. HA usage was associated only with hearing loss level (pure tone average; β = 0.030, P = .04). Aided sound exposure was associated only with duration of audiologic follow-up (β = 0.100, P = .02). Conclusion While measurement of HA use has traditionally relied on subjective reporting, data logging offers an objective tool to longitudinally track HA use and sound exposure. We demonstrate the feasibility of using this potentially powerful research tool. Usage and sound exposure were stable among patients throughout the study period. Use was greater among subjects with greater hearing loss. Maximizing aided sound exposure might be possible through continued audiology follow-up visits. [ABSTRACT FROM AUTHOR]