English

Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls

Artificial Intelligence 2021-01-12 v1

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.

Keywords

Cite

@article{arxiv.2101.03210,
  title  = {Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls},
  author = {Sarvenaz Chaeibakhsh and Roya Sabbagh Novin and Tucker Hermans and Andrew Merryweather and Alan Kuntz},
  journal= {arXiv preprint arXiv:2101.03210},
  year   = {2021}
}

Comments

Accepted in: "10th International Conference on Operations Research and Enterprise Systems". 13 pages, 10 figures