Audiogram Digitization Tool for Audiological Reports

TL;DR

This paper introduces an automated audiogram digitization tool that accurately extracts hearing thresholds from scanned reports, significantly reducing manual effort in audiological claim assessments and advancing automation in adjudication processes.

Contribution

It presents the first automated algorithm for extracting audiogram data from scanned reports, enabling semi-supervised digitization and streamlining insurance claim adjudication.

Findings

Most thresholds extracted within 5 dB accuracy

Reduces time for audiogram digitization

Supports semi-supervised processing

Abstract

A number of private and public insurers compensate workers whose hearing loss can be directly attributed to excessive exposure to noise in the workplace. The claim assessment process is typically lengthy and requires significant effort from human adjudicators who must interpret hand-recorded audiograms, often sent via fax or equivalent. In this work, we present a solution developed in partnership with the Workplace Safety Insurance Board of Ontario to streamline the adjudication process. In particular, we present the first audiogram digitization algorithm capable of automatically extracting the hearing thresholds from a scanned or faxed audiology report as a proof-of-concept. The algorithm extracts most thresholds within 5 dB accuracy, allowing to substantially lessen the time required to convert an audiogram into digital format in a semi-supervised fashion, and is a first step towards the automation of the adjudication process. The source code for the digitization algorithm and a desktop-based implementation of our NIHL annotation portal is publicly available on GitHub (https://github.com/GreenCUBIC/AudiogramDigitization).