Background: Taiwan’s rapidly aging population and shortage of long-term care (LTC) manpower underscore the need to reduce administrative workload while maintaining care quality. Objective: This study evaluated the effectiveness of an AI-assisted voice assistant in improving work efficiency and reducing documentation burden in LTC settings. Methods: The AI-assisted voice assistant was implemented across 14 residential and non-residential LTC facilities in southern Taiwan. Pre- and post-evaluations, along with user feedback, were collected from 68 staff members through self-administered questionnaires. Key indicators included changes in documentation time, monthly cost-effectiveness, perceived reduction in documentation burden, and perceived work assistance. Results: The average daily documentation time decreased from 2.88 to 2.23 hours (−22.57%). The overall sample showed an estimated monthly labor cost saving of approximately NT$3,165, while documentation burden improved by 21.01%. The perceived helpfulness score (4.66/10) was slightly lower than the pre-implementation expectation (5.44/10), and overall satisfaction averaged 3.21/5. Qualitative feedback revealed enhanced real-time communication, reduced redundant input, and improved record accuracy, while also emphasizing the need for better system integration, simplified operation, and more stable speech recognition. Conclusion: The AI-assisted voice assistant effectively reduced documentation burden and improved workflow efficiency among LTC personnel. Further optimization of system integration, speech recognition accuracy, and user training may enhance its usability and long-term impact on care quality.

Authors:
Ching-Ju Chiu, National Cheng Kung University, Taiwan

About the Presenter(s)
Ching-Ju Chiu is a professor at the Institute of Gerontology, College of Medicine, National Cheng Kung University.

See this presentation on the full schedule – Tuesday Schedule

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