Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls

TL;DR

This paper introduces a novel optimization approach to redesign hospital room layouts, significantly reducing patient fall risks by considering object placement and patient trajectories, thus enhancing patient safety.

Contribution

It formulates a gradient-free constrained optimization problem for hospital room layout reconfiguration, incorporating a fall risk model and architectural constraints, solved efficiently with simulated annealing.

Findings

18% average reduction in fall risk compared to traditional layouts

41% reduction compared to random layouts

Effective optimization for real-world hospital rooms

Abstract

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.