Integrated decision-making in home health care: review and first model

Abstract

Home health care (HHC) may be defined as care workers visiting patients following predefined schedules in order to provide medical services in their home. As maintaining a sustainable and effective health care system is a major challenge, HHC providers must discover new ways to decrease costs and enhance productivity by optimizing the use of resources.

First, the findings of a literature review on OR models applied in HHC will be discussed. It was found that a key opportunity for improvement is the integration of decisions at different decision-making levels. Second, the specific problem setting on which we focus will be defined and its contributions will be stressed. This project contributes to the current state-of-the-art by integrating tactical (staff dimensioning) and lower decision-making (clustering, rostering, routing and scheduling) levels. A third part of the presentation will focus on the solution algorithm that is developed to solve the model under study. The solution algorithm first finds an initial feasible solution by using a combination of a tailored k-means heuristic to cluster patients and by solving a binary integer linear programming model to roster care workers. In a second phase of the solution algorithm, the initial solution is improved by executing iterations of a tailored large neighbourhood search heuristic. Finally, the results of some experiments conducted to assess the performance of the solution algorithm will be discussed.