An estimation and visualization method for the movement lines of nurses in an unattended time and motion study with beacons and mobile devices

Abstract

　In Japan, many hospitals are facing a shortage of nurses due to the declining birthrate and aging population, and thus it is necessary for them to improve operational efficiency based on objective data such as nursing workload and the movement lines of nurses. In this paper, we utilize an unattended time and motion study with Bluetooth low energy (BLE) beacons and mobile devices, which is low cost, imposes a low burden on nurses, and can be conducted over a long term. Our goal is to construct a software framework designed to estimate the movement lines of nurses based on the received signal strength indicator (RSSI) series obtained from the study and to visualize them as videos. We propose a simple method for estimating movement lines without using supervised machine learning, making it a practical solution for large hospitals with numerous wards. Moreover, we develop software to visualize each nurse′s estimated movement lines as videos using Data-Driven Document (D3) module. We validate our proposed framework with an unattended time and motion study conducted in one ward of a large acute care hospital, demonstrating its ability to capture each nurse′s movement lines throughout the entire ward in detail.