Authors: Nicolas Vannson¹
¹Hearing Data Science
Background: In France, every hearing aid clinic relies on the Noah database to store essential patient data, such as audiograms, hearing aid selection and fitting records. However, as this database grows daily, the lack of dedicated analytical tools limits its utility for patient follow-up and clinical insights.
Method: To address this gap, Hearing Data Science developed Hearing Data, a data-driven tool that unlocks the full potential of the Noah database to enhance patient care and clinical research. This tool currently offers four core features:
- Population overview: Age-categorized demographic insights
- Hearing aid analytics: Comprehensive analysis of fitting sessions, brands, models, and temporal trends
- Geodata integration: Geographical and socioeconomic profiling of patients
- Audiogram classifications: Standardized categorization using BIAP recommendations, Bisgaard classifications, and detailed hearing measurements
Results: Hearing Data has demonstrated high efficiency analyzing datasets of over 300 subjects per file in just 10–30 seconds. Ongoing development aims to aggregate data from multiple hearing clinics, further expanding its analytical power and scalability.
Conclusion: This brand-new tool is also available for research projects, offering a powerful resource for data-driven advancements in audiology.
