Development of the Self-Voice Program for the Digital Transformation of Voice-Related Patient-Reported Outcome Measures - Chang Yoon Lee; Soo-Youn An; Hee Young Son (Journal of The Korean Society of Laryngology, Phoniatrics and Logopedics, 2026)
Background and Objectives To develop Self-Voice, a browser-based platform for administration, scoring, visualization, longitudinal tracking, and export of voice-related patient-reported outcome measures (PROMs).Materials and Method Self-Voice was developed as a static client-side web application in which patient and assessment data are stored in the user’s browser. The platform implements the Korean Voice Handicap Index (K-VHI)-30, K-VHI-10, Korean Voice Fatigue Index (K-VFI), and Korean Voice-Related Quality of Life (K-VRQOL), preserving each instrument’s original scoring structure and direction. It calculates raw and subscale scores, 0–100 range-transformed scores, direction-aligned scores for visual display, and the instrument-standardized K-VRQOL score. Instrument-specific literature-based change references are applied only to the original score metric of the same instrument and scale. The program also supports assessment-context recording, patient-specific export, bulk research CSV export using system-generated research IDs, encrypted JSON backup, PIN-based locking, automatic locking, and audit logging. Internal verification used fictional data and predefined functional cases.Results Automated scores matched expected calculations, and 11 boundary cases for instrument-specific change references were processed as intended. No automatic change threshold was applied to K-VFI. Assessment-context information remained linked to the corresponding assessment. Bulk research export generated one row per PROM administration, retained stable research IDs across repeated assessments, and excluded direct identifiers and raw free-text information. Browser-local storage, access-control functions, encrypted backup pathways, audit logging, and version-based data migration were implemented and reviewed.Conclusion Self-Voice provides an integrated, voice-disorder-specific workflow for digital PROM administration and longitudinal data management. Range-transformed and direction-aligned scores are visual aids rather than normative or severity measures. Prospective studies with patients and clinicians are required to evaluate usability, feasibility, and clinical utility.