4.7 Article

A Novel Representation of Audiological and Subjective Findings for Acoustical, Bone Conduction and Direct Drive Hearing Solutions

Journal

JOURNAL OF PERSONALIZED MEDICINE
Volume 13, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/jpm13030462

Keywords

bone conduction implant; hearing aids

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This study aims to evaluate the overall benefits of hearing rehabilitation by presenting both audiological and subjective outcomes in one graph using data from an existing study. The graph allows tracking the user's performance over time and visualizing the correlation between different measures.
Background: The benefit of hearing rehabilitation is often measured using audiological tests or subjective questionnaires/interviews. It is important to consider both aspects in order to evaluate the overall benefits. Currently, there is no standardized method for reporting combined audiological and patient reported subjective outcome measures in clinical practice. Therefore, this study focuses on showing the patient's audiological, as well as subjective outcomes in one graph using data from an existing study. Method: The present paper illustrated a graph presenting data on four quadrants with audiological and subjective findings. These quadrants represented speech comprehension in quiet (unaided vs. aided) as WRS% at 65 dB SPL, speech recognition in noise (unaided vs. aided) as SRT dB SNR, sound field threshold (unaided vs. aided) as PTA(4) in dB HL, wearing time and patient satisfaction questionnaire results. Results: As an example, the HEARRING graph in this paper represented audiological and subjective datasets on a single patient level or a cohort of patients for an active bone conduction hearing implant solution. The graph offered the option to follow the user's performance in time. Conclusion: The HEARRING graph allowed representation of a combination of audiological measures with patient reported outcomes in one single graph, indicating the overall benefit of the intervention. In addition, the correlation and consistency between some results (e.g., aided threshold and aided WRS) can be better visualized. Those users who lacked performance benefits on one or more parameters and called for further insight could be visually identified.

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