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Leveraging real-world data to improve cochlear implant outcomes: Is the data available?
Callum Findlay1,2, Mathew Edwards1, Kate Hough3
1Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Building 85, Highfield Campus, Southampton S017 1BJ, UK.
Cochlear Implants International
|April 23, 2023
Summary
Data science can improve cochlear implant (CI) outcomes by analyzing patient health records. Accurate data capture, including middle ear inflammation history, is crucial for understanding factors affecting CI success.
Area of Science:
- Audiology
- Data Science
- Clinical Informatics
Background:
- A subset of cochlear implant (CI) users do not achieve optimal outcomes.
- Data science offers a potential pathway to understand factors influencing CI success.
- Otitis media is linked to sensorineural hearing loss and may impact CI performance.
Purpose of the Study:
- To evaluate the quality and utility of CI user health records for data science applications.
- To assess the recording of otitis media in clinical data capture for CI patients.
Main Methods:
- Retrospective service improvement project.
- Evaluation of medical records for 594 CI users (2014-2020).
- Focus on the recording of middle ear inflammation (otitis media).
Main Results:
- Clinical records are suitable for data science research.
- 20% of adult CI users and over 40% of pediatric CI users have a history of middle ear inflammation.
Conclusions:
- Data science can enhance understanding of CI outcomes and performance mechanisms.
- Consistent and accurate patient data recording is vital for CI centers and registries.
- Data on conditions like middle ear inflammation are valuable for future analyses and clinical trials.
