Last-Mile Attended Home Healthcare Delivery: A Robust Strategy to Mitigate Cascading Delays and Ensure Punctual Services

Abstract

The attended home healthcare (AHH) industry is experiencing rapid growth due to the rising demand from an aging population and the potential benefits of alleviating pressures on traditional healthcare resources. However, ensuring timely one-on-one AHH services for homebound patients remains a challenge because of cascading delays arising from uncertainties in travel and service times. To address this issue in last-mile homecare delivery, we develop a systematic cascading delay mitigation strategy to ensure patients receive dependable homecare services. Specifically, we introduce a compound set reliability index (CSRI) that captures risk exposure by separately characterizing distinct travel and service time uncertainties, instead of approaching them as a single type of uncertainty in previous studies. The CSRI-based service-level constraints are then integrated into a set-partitioning formulation to mitigate the cascading delays. We devise an exact branch-price-and-cut framework and employ a variable neighborhood search metaheuristic to achieve fast-effective solutions. Numerical experiments with benchmark and real-world datasets validate the effectiveness of our methods, underscore the benefits of adopting a systematic cascading delay mitigation strategy, and provide insights to AHH service providers regarding the impact of crucial managerial parameters on delay manifestation. The CSRI constraints and dedicated solution methods can effectively support practical decision-making and enhance the punctuality of AHH services, leading to better service dependability and heightened stakeholder satisfaction.