C. Lewis, A. Lehman, M. Schaffner, I. Wang, A. Andoy
360 Social Impact Studios,
United States
Keywords: AI, AR, assisted reality, nursing documentation, LTC workflow, patient-centered care
Summary:
LifeLensAR is an emerging AI-driven assisted reality platform designed to streamline clinical documentation and enhance direct resident care within long-term care (LTC) settings. Nurses typically spend a significant portion of their shift on time-consuming and repetitive documentation tasks. This burden can detract from patient-centered activities, contributing to stress, burnout, and lower-quality interactions with residents. LifeLensAR addresses these challenges by integrating advanced voice recognition—trained specifically on LTC terminology—and a hands-free, wearable heads-up display (HUD) that lets clinicians document care in real time. In addition to significantly reducing administrative overhead, the system aims to improve accuracy of documentation by capturing notes immediately at the bedside. This timely data capture can reduce the risk of missed details and improve overall continuity of care. The voice-enabled interface also minimizes keyboard reliance, enabling staff to remain focused on resident well-being rather than navigating complex software or devices. LifeLensAR will begin pilot testing in partner LTC facilities, where success metrics include time-motion analyses to quantify documentation time savings, error reduction rates, and staff usability scores (e.g., System Usability Scale). By allowing nurses to chart as they go, facilities may observe operational benefits such as reduced overtime, less end-of-shift backlog, and improved billing accuracy. From a patient perspective, we expect more individualized attention and timelier clinical interventions, especially given the dynamic demands of LTC populations. By sharing our early-stage research, system architecture, and pilot design at the TechConnect World Innovation Conference, our goal is to foster collaboration with industry, academia, and additional healthcare stakeholders who value real-world solutions that balance staff efficiency and patient-centered care. The potential impact extends beyond LTC, laying a foundation for broader adoption of AI-assisted workflows in diverse healthcare environments.