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BMC Health Services Research
Published in: BMC Health Services Research 1/2019

Open Access 01-12-2019 | Research article

Prediction of the service life of surgical instruments from the surgical instrument management system log using radio frequency identification

Authors: Takeki Yoshikawa, Eizen Kimura, Emi Akama, Hiromi Nakao, Toshihiro Yorozuya, Ken Ishihara

Published in: BMC Health Services Research | Issue 1/2019

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Abstract

Background

Bar code- or radio frequency identification (RFID)-based medical instrument management systems have gradually been introduced in the field of surgical medicine for the individual management and identification of instruments. We hypothesized that individual management of instruments using RFID tags can provide previously unavailable information, particularly the precise service life of an instrument. Such information can be used to prevent medical accidents caused by surgical instrument failure. This study aimed to predict the precise service life of instruments by analyzing the data available in instrument management systems.

Methods

We evaluated the repair history of instruments and the usage count until failure and then analyzed the data by the following three methods: the distribution of the instrument usage count was determined, an instrument failure probability model was generated through logistic regression analysis, and survival analysis was performed to predict instrument failure.

Results

The usage count followed a normal distribution. Analysis showed that instruments were not used uniformly during surgery. In addition, the Kaplan–Meier curves plotted for five types of instruments showed significant differences in the cumulative survival rate of different instruments.

Conclusions

The usage history of instruments obtained with RFID tags or bar codes can be used to predict the probability of instrument failure. This prediction is significant for determining the service life of an instrument. Implementation of the developed model in instrument management systems can help prevent accidents due to instrument failure. Knowledge of the instrument service life will also help in developing a purchase plan for instruments to minimize wastage.
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Metadata
Title
Prediction of the service life of surgical instruments from the surgical instrument management system log using radio frequency identification
Authors
Takeki Yoshikawa
Eizen Kimura
Emi Akama
Hiromi Nakao
Toshihiro Yorozuya
Ken Ishihara
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2019
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-019-4540-0

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