Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls
This work provides a method to improve patient safety by reducing fall risks in hospital rooms, benefiting patients and healthcare providers.
This paper addresses the persistent problem of patient falls in hospital rooms by formulating and solving a gradient-free constrained optimization problem. The proposed method generates and reconfigures hospital room layouts, achieving an 18% average reduction in patient fall risk compared to traditional layouts and 41% compared to randomly generated layouts.
Despite years of research into patient falls in hospital rooms, falls and related injuries remain a serious concern to patient safety. In this work, we formulate a gradient-free constrained optimization problem to generate and reconfigure the hospital room interior layout to minimize the risk of falls. We define a cost function built on a hospital room fall model that takes into account the supportive or hazardous effect of the patient's surrounding objects, as well as simulated patient trajectories inside the room. We define a constraint set that ensures the functionality of the generated room layouts in addition to conforming to architectural guidelines. We solve this problem efficiently using a variant of simulated annealing. We present results for two real-world hospital room types and demonstrate a significant improvement of 18% on average in patient fall risk when compared with a traditional hospital room layout and 41% when compared with randomly generated layouts.