Transforming Geriatric Care: A HIMSS Level 7 Model for Holistic Patient-Centered Service Delivery (® Life Concerto).

Background: As societies age, the demand for high-quality, continuous elderly care rises. Traditional clinical care often struggles to address the multifaceted needs of older adults, particularly those requiring long-term care. The Continuity of Care Maturity Model (CoCMM) by HIMSS highlights the importance of integrated, patient-centered care, yet challenges such as fragmented communication, insufficient data integration, and lack of real-time records persist in Taiwan.

Objective: This study aimed to design, implement, and evaluate "Life Concerto," (®) an AI-enabled integrated communication and collaboration platform, to address these gaps and improve care quality and efficiency.

Methods: Life Concerto utilized a BERT-based natural language processing system for keyword and message classification, supported by expert-curated decision-support algorithms. The platform facilitated multilingual communication, real-time interaction, and structured documentation among caregivers, healthcare providers, and family members. Pilot implementation included 897 chat rooms and over 2,167 users across 35 institutions, integrating use cases for long-term care, home-based acute care, and dementia care.

Results: Results showed a 5.5 times per week interaction frequency between patients and care teams, significantly higher than traditional care models. It also reduced dementia visit times by 66.4%, cutting administrative workload and improving data accuracy, as it enabled real-time sharing of patient conditions, vital signs, and episode records. Multilingual support, including Indonesian, Filipino, Vietnamese, and English, broke down language barriers and ensured inclusive communication for foreign caregivers.

Discussion: Achieving HIMSS Continuity of Care Maturity Model Level 7, Life Concerto established a dynamic, interconnected, patient-centered care model. While adoption barriers such as training requirements and resistance to change were noted, the platform's success highlights the transformative potential of AI-driven solutions in elderly care. Future efforts should focus on seamless integration with electronic health records (EHRs) and addressing implementation challenges to promote widespread adoption and enhance holistic care delivery.