Related Experiment Video
Updated: May 24, 2026
03:58
Enhancing Electrode Location Assessment in Cochlear Implantation via Computed Tomography Image Fusion
Published on: January 17, 2025
A Data-Driven Visit Windowing Approach Applied to Cochlear Implant Follow-Up Data
Annette Günther1, Oliver J Bott2, Eugen Kludt1
1Department of Otolaryngology, Hannover Medical School, Hannover, Germany.
Studies in Health Technology and Informatics
|May 23, 2026
Summary
A new data-driven visit windowing (DDW) method improves cochlear implant (CI) follow-up analysis by better accounting for real-world visit timing. This approach enhances data consistency and prediction accuracy for hearing outcomes.
Area of Science:
- Audiology
- Medical Data Analysis
- Biostatistics
Background:
- Cochlear implant (CI) patients need consistent follow-up for optimal hearing.
- Clinical visits often deviate from schedules, impacting data reliability.
- Existing study-protocol visit window (SPW) methods lack flexibility.
Purpose of the Study:
- To develop and evaluate a data-driven visit windowing (DDW) approach for CI patient follow-up.
- To compare the DDW method against the traditional SPW scheme.
- To improve the reproducibility and comparability of longitudinal CI data analysis.
Main Methods:
- Analyzed 31,344 speech test visits from 5,264 CI patients.
- Defined data-driven visit windows with start/end points.
- Developed a rule to select the most representative visit within each window.
Main Results:
- DDW windows are reproducible and capture visit timing variability.
- DDW covered 40.3% more visits than SPW.
- DDW achieved slightly lower prediction errors for speech recognition.
Conclusions:
- DDW offers a reproducible, extensible, and clinically relevant basis for defining visits.
- Enables consistent longitudinal CI analyses and improved data quality.
- Facilitates better data comparisons across different clinical centers and studies.
