care quality

The global demographic transition toward an aging population presents unprecedented challenges for long-term care systems, with critical workforce shortages affecting $92 \%$ of nursing homes and $70 \%$ of assisted living facilities. This mixed-methods study investigates the effectiveness of AI-enhanced human-machine collaboration in improving long-term care service efficiency and quality. Following PRISMA and STROBE guidelines, we conducted a systematic review of 105 studies and controlled trials across 218 facilities ( 94 intervention, 124 control) over 18 months. The AI-enhanced system analyzed 150 daily clinical data points per patient, providing real-time alerts for condition changes, fall risk assessment, and medication monitoring. Results demonstrated significant improvements in $89 \%$ of quality measures, including a $9 \%$ reduction in major falls ( $p=0.034$ ), 22\% decrease in ADL dependency ( $p DOI: https://dx.doi.org/10.17654/0973700626007 Received: October 18, 2025 Accepted: November 3, 2025;