Objectives: Our aim is to investigate causes of medical incidents and construct a knowledge base for preventing malpractice based on monitored data.
Methods: To monitor nursing care, we developed an observing system of nursing activities with a ubiquitous sensor network and detecting errors in nursing care. This system is composed of a voice-recording device, mobile sensors and environmental setting type sensors. In cooperation with a hospital in western Japan, we have collected nursing activity data of nurses engaged at a combined ward, including ophthalmology, otolaryngology, and internal medicine for diabetes. After analyzing intravenous drip injection procedure (IVDI procedure) data, we introduce a three-layered model of nursing to understand nursing activities based on observed data. This model consists of three layers, 1) nursing care classification layer: Class, 2) nursing care step layer: Step, and 3) nursing care action layer: Action. This model is designed to take consistency with existing nursing care workflows.
Results: We implemented a detection system and succeeded in comprehending the workflow of IVDI procedure at the rate of over 95%. This system also can distinguish IVDI workflows performed in parallel by at least two or several nurses. We implemented a picture showing interface of IVDI workflows which can show each patient with a specific color and distinct nurses.
Conclusions: Our system succeeded in verification of nursing care steps in IVDI procedure in ratios of more than 95%. Detection errors are due to the sensor system, so it is necessary to use or develop more precise devices.