Abstract
At the University of Miyazaki Hospital (UMH), we have accumulated and semantically structured a vast amount of medical information since the activation of the electronic health record system approximately 10 years ago. With this medical information, we have decided to develop an alert system for aiding in medical treatment. The purpose of this investigation is to not only to integrate an alert framework into the electronic heath record system, but also to formulate a modeling method of this knowledge. A trial alert framework was developed for the staff in various occupational categories at the UMH. Based on findings of subsequent interviews, a more detailed and upgraded alert framework was constructed, resulting in the final model. Based on our current findings, an alert framework was developed with four major items. Based on the analysis of the medical practices from the trial model, it has been concluded that there are four major risk patterns that trigger the alert. Furthermore, the current alert framework contains detailed definitions which are easily substituted into the database, leading to easy implementation of the electronic health records.
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This study was not funded. Author Takuya Sakata, Author Kenji Araki, Author Tomoyoshi Yamazaki, Author Koichi Kawano, Author Minoru Maeda, Author Muneo Kushima, Author Sanae Araki declare that they have no conflict of interest.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.
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Informed consent was obtained from all individual participants included in the study.
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This article is part of the Topical Collection on Systems-Level Quality Improvement
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Sakata, T., Araki, K., Yamazaki, T. et al. Development of an “Alert Framework” Based on the Practices in the Medical Front. J Med Syst 42, 114 (2018). https://doi.org/10.1007/s10916-018-0967-9
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DOI: https://doi.org/10.1007/s10916-018-0967-9