UC San Diego

Telehealth has significantly enhanced various medical sectors, notably in postpartum care, by increasing breastfeeding rates and reducing postpartum depression. However, issues in patient management and triage, particularly in high-demand telehealth lactation consultations, lead to LC burnout, unnecessary costs and diagnostic delays. To address these challenges, this study introduces a pain assessment tool for telehealth lactation consultations, enhancing patient-provider communication through momentary assessment and AI mediation. It features a user interface with image quality assessment and condition classification algorithms, aiding remote diagnosis and triage. The tool guides patients and uses a severity-based feedback system, helping LCs prioritize cases. This method boosts tele-lactation service efficiency, streamlines LC workload, and serves as a model for specialized healthcare triaging. Future work includes refining the feedback system and evaluating the tool in clinical settings to standardize symptom severity grading and estimate its impact, potentially improving expert patient triaging in remote healthcare settings.