Research on Digital Approaches to Improving the Quality of Elderly Care Services

Abstract

Background: The global aging population is increasing rapidly, creating an urgent demand for high-quality elderly care services. Traditional care models are often constrained by limited personnel, slow response times, and fragmented health information. Objective: This study aimed to evaluate the effectiveness of digital approaches—including Internet of Things monitoring, artificial intelligence demand-matching systems, and remote health management—in improving the quality of community-based elderly care services. Methods: A case study was conducted in a Shanghai community that implemented a digital elderly care project. Data were collected over 12 months post-implementation. Key performance indicators such as emergency response time, service matching accuracy, and rescue success rates were compared before and after the digital transformation using descriptive analysis. Results: The implementation of digital technologies led to significant improvements: health emergency warning response time decreased from 4 hours to 15 minutes; service demand matching accuracy increased from 65% to 92%; and the emergency rescue success rate improved from 70% to 100%. Additionally, annual hospitalization rates decreased, and service satisfaction scores rose. Conclusion: Digital approaches can effectively transform elderly care from a reactive to a proactive model, significantly enhancing service efficiency, health outcomes, and user satisfaction. However, challenges such as low digital literacy among the elderly and data security risks must be addressed. This research provides empirical evidence supporting the digital transformation of elderly care services.