Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance

TL;DR

This paper presents a vision-based system for tracking hospital staff and visitors to improve hand hygiene compliance, aiming to reduce hospital-acquired infections and enhance operational efficiency.

Contribution

It introduces a non-intrusive, vision-based tracking method that outperforms existing solutions in measuring hand hygiene compliance in hospitals.

Findings

Outperforms proximity-based and observational methods

Provides interpretable spatial analytics of human movement

Shows promise in reducing hospital-acquired infections

Abstract

One in twenty-five patients admitted to a hospital will suffer from a hospital acquired infection. If we can intelligently track healthcare staff, patients, and visitors, we can better understand the sources of such infections. We envision a smart hospital capable of increasing operational efficiency and improving patient care with less spending. In this paper, we propose a non-intrusive vision-based system for tracking people's activity in hospitals. We evaluate our method for the problem of measuring hand hygiene compliance. Empirically, our method outperforms existing solutions such as proximity-based techniques and covert in-person observational studies. We present intuitive, qualitative results that analyze human movement patterns and conduct spatial analytics which convey our method's interpretability. This work is a step towards a computer-vision based smart hospital and demonstrates promising results for reducing hospital acquired infections.