Improving the medium-term schedule in a home health care context with different demand frequencies

This study, conducted at ExpertCare, focuses on optimizing the medium-term scheduling of the Injection Team to reduce travel time and improve the productivity. ExpertCare, a home care provider in the Netherlands, manually schedules appointments for approximately 900 clients with varying visitation frequencies. Analysis revealed significant travel times and three major client densities in Utrecht, Amersfoort, and Zeist. The current average travel time per nurse is 2.63 hours per day. To address this, a heuristic approach using the adaptive large neighborhood search (ALNS) was implemented. ALNS starts with a greedy heuristic for initial scheduling, then iteratively improves it. Various scenarios were tested, including flexible scheduling of clients. Results showed that this reduced travel time by 16.14%, enhancing productivity by 1.7%. This would lead to a reduction of the average travel time per nurse per day of 0.42. However, scenarios with client-selected time slots increased travel time, highlighting the need for a balance between efficiency and client preferences. Overall, the study provides insights into the current inefficiencies and potential improvements for ExpertCare's scheduling system, advocating for more advanced planning tools to manage the growing client base and improve nurse workload distribution.