SIGNATURE WORK
CONFERENCE & EXHIBITION 2024

In response to the escalating challenges posed by an aging trend in society, addressing the associated old-age care problems and devising strategies to accommodate future demands have emerged as paramount concerns for governments and directors of nursing homes. This study centers on Xiangcheng District in Suzhou City, China, focusing on the quantitative analysis of elderly population trends through linear regression modeling and predictive analytics. Additionally, leveraging Lingfeng Nursing Home as a case study within Xiangcheng District, this study endeavors to forecast nursing bed demand and occupancy dynamics. By scrutinizing past data and employing predictive methodologies, insights are gleaned to aid policymakers and nursing home administrators in optimizing elderly care services. The findings offer actionable recommendations aimed at enhancing resource allocation, facility planning, and service provision in anticipation of the evolving needs of the elderly population. Through data-driven analysis and proactive planning, this study contributes to the development of effective strategies to navigate the challenges posed by population aging.