Patient assignment and grouping problem on home health care: A case in Hong Kong

Home healthcare (HHC) service systems have been attracting researchers’ attentions in recent decades. Many resources are involved in delivering HHC service, consisting of different categories of human resources (nurses, physicians, physiotherapists, social assistants, and psychologists), support staff, and material resources. One of the main issues encountered when managing HHC services is the patient assignment problem, i.e., assigning operators to admitted patients given some sets of constraints (e.g., the continuity of care). This paper addresses the patient assignment and grouping problem for HHC system, Alice Ho Miu Ling Nethersole Hospital (AHNH) in Hong Kong, which focuses more on assigning new-admitted patients in a period to operators with achieving the aims of workload balance and minimum delay visits, and meanwhile grouping the assigned patients for each operator based on the patients’ geographical location and next visit due time to reduce the travel time and improve the efficiency of operators. This hospital suffers from ineffective manual planning methods to manage their human resource when providing home health care. In order to improve the quality of service and efficiency of operators, we model the patient assignment and grouping problem and will use heuristic method such as discrete particle swarm optimization, Tabu Search, genetic algorithm to obtain the optimal solution.