Methods Inf Med 2009; 48(06): 574-581
DOI: 10.3414/ME9245
Original Articles
Schattauer GmbH

A Three-layered Model of Nursing Based on Hospital Observation Data

Analysis of Nursing Care with Ubiquitous Sensors
N. Ohboshi
1   Department of Informatics, School of Science and Engineering, Kinki University, Higashi-Osaka City, Japan
,
T. Tanaka
2   Nippon Telegraph and Telephone Corporation (NTT) Data Kansai, Osaka, Japan
,
N. Kuwahara
3   Kyoto Institute of Technology, Kyoto, Japan
,
H. I. Ozaku
4   National Institute of Information and Communications Technology (NICT), Tokyo, Japan
,
F. Naya
5   Nippon Telegraph and Telephone Corporation (NTT), Communication Science Laboratories, Tokyo, Japan
,
K. Kogure
6   Kanazawa Institute of Technology, Kanazawa, Japan
› Author Affiliations
Further Information

Publication History



05 November 2009

Publication Date:
17 January 2018 (online)

Summary

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 work-flow 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.