Development of an Integrated Digital GRBAS–CAPE-V System for Auditory-Perceptual Voice Assessment and Preliminary Needs Analysis

Background and Objectives To investigate clinical needs for digitalizing auditory-perceptual voice assessment and to develop a prototype integrated Grade, Roughness, Breathiness, Asthenia, Strain (GRBAS)–Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V) digital assessment system.Materials and Method A preliminary needs assessment was conducted with 21 speech-language pathologists experienced in voice assessment or intervention. The survey examined perceptions of auditory-perceptual evaluation, documentation practices, workflow barriers, and functional requirements. Based on the findings, a web-based GRBAS–CAPE-V prototype was developed to support patient registration, structured GRBAS and CAPE-V input, integrated visualization, longitudinal monitoring, PDF reporting, and research-oriented data export.Results Participants considered auditory-perceptual assessment important for voice evaluation, treatment monitoring, and complementing instrumental assessment. GRBAS was the most frequently used scale, while CAPE-V was also used by many respondents. Most participants documented results using unstructured electronic medical record text. Major barriers included record-management difficulties, limited clinical time, and evaluator subjectivity. Functional needs were rated highly, particularly automated cumulative management, reuse of entered data for research, integration of GRBAS and CAPE-V, and visualization of session-to-session changes. The prototype integrated discrete GRBAS ratings and continuous CAPE-V scores within a single digital workflow and was implemented with visual summary and longitudinal tracking functions.Conclusion Clinicians recognize the importance of auditory-perceptual assessment but experience practical limitations in documentation, visualization, and longitudinal data management. The prototype may facilitate structured documentation and longitudinal use of perceptual voice data; however, it does not directly address evaluator subjectivity or inter- and intra-rater reliability. Further studies should evaluate usability and clinical feasibility and determine whether training-based extensions can improve rating reliability