Pilot study on the use of data mining to identify cochlear implant candidates

Abstract

Objectives: The goal of this pilot study was to determine the clinical utility of data-mining software that screens for cochlear implant (CI) candidacy.

Methods: The Auditory Implant Initiative developed a software module that screens for CI candidates via integration with a software system (Noah 4) that serves as a depository for hearing test data. To identify candidates, patient audiograms from one practice were exported into the screening module. Candidates were tracked to determine if any eventually underwent implantation.

Results: After loading 4836 audiograms from the Noah 4 system, the screening module identified 558 potential CI candidates. After reviewing the data for the potential candidates, 117 were targeted and invited to an educational event. Following the event, a total of six candidates were evaluated, and two were implanted.

Discussion: This objective approach to identifying candidates has the potential to address the gross underutilization of CIs by removing any bias or lack of knowledge regarding the management of severe to profound sensorineural hearing loss with CIs.

Conclusion: The screening module was an effective tool for identifying potential CI candidates at one ENT practice. On a larger scale, the screening module has the potential to impact thousands of CI candidates worldwide.

Keywords:

• Cochlear implant
• data mining
• candidacy

ORCID

Anne Lam http://orcid.org/0000-0002-3712-0183

Terry Griffin http://orcid.org/0000-0001-5664-484X