Using mobility trace analysis, we generated occupancy rates for different rooms in the hospital occupied by both staff and patients. Results: Using ground-truth data, we estimated the accuracy of our system to be 96%. A number of analyses were conducted to estimate how people move in the hospital and where they spend their time.
In addition, we collected ground-truth data and used them to validate system performance and accuracy. The system recorded the position of 75 people (17 patients and 55 staff) during this period.
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Methods: We developed a Bluetooth low energy, proximity-based localization system and deployed it in a hospital for 30 days. Objective: The aim of this study is to measure the accuracy of the system and algorithmically calculate measures of mobility and occupancy. Such a streamlined data-driven approach can help in increasing the uptime of operating rooms and more broadly provide an improved understanding of facility utilization. In this study, we aim to develop a proximity-based localization system and show how its longitudinal deployment can provide operational insights related to staff and patients' mobility and room occupancy in clinical settings.
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