Optimizing Flow in the Healthcare System for Older Adults

This thesis investigates the healthcare system for older adults through mathematical and analytical methods, with an emphasis on optimizing resource allocation and enhancing care delivery. Using advanced data analysis techniques, patient flows of older adults are modeled and analyzed, providing valuable insights into the demographics and utilization patterns of specific types of care. Stochastic models are developed to identify key inefficiencies in critical components of the healthcare system, such as intermediate care and long-term care. Building on these findings, novel allocation methods are proposed to improve the matching of older adults to available care resources. These methods account for individual preferences and systemic constraints, enabling a more person-centered and efficient distribution of resources. Simulation studies validate the effectiveness of the proposed approaches, demonstrating reductions in waiting times, improved capacity utilization, and better alignment of care delivery with the older adults’ needs. Overall, this work highlights the transformative potential of mathematical and analytical tools in addressing the challenges posed by an aging population.