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Authors: Koichiro Okada 1 ; Masanori Akiyoshi 2 ; Yukie Majima 1 ; Hiroe Takahashi 3 ; Sayuri Tanaka 4 ; Misae Tanioka 4 and Miwako Hori 4

Affiliations: 1 Osaka Prefecture University, Japan ; 2 Kanagawa University, Japan ; 3 Japan Community Health care Organization (JCHO), Japan ; 4 JCHO Osaka Hospital, Japan

ISBN: 978-989-758-170-0

Keyword(s): Incident Data, Ladder Level, Nurse Rostering, Nurse Scheduling, Pattern Mining.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Healthcare Management Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Medical and Nursing Informatics ; Ontologies and the Semantic Web ; Sensor Networks ; Signal Processing ; Society, e-Business and e-Government ; Soft Computing ; Web Information Systems and Technologies

Abstract: As described herein, we sought knowledge necessary to make a roster for nurses by analyzing nurse scheduling data and incident reports on the night shift. Even today, it is difficult to say that computers are used effectively producing nurse rosters. One reason is that algorithms suggested by researchers are not practical for nurses working at various sites because they are built without consideration of medical accidents known as “incidents”. Another reason is that the study of incidents from a team's perspective, which is the original mode of working as a nurse, is not available. Therefore, this study was conducted for discovery of knowledge to help produce a nursing roster by analyzing nurse scheduling data and incident data for night shifts from the viewpoint of teams, which is the original mode of working for nurses.

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Paper citation in several formats:
Okada, K.; Akiyoshi, M.; Majima, Y.; Takahashi, H.; Tanaka, S.; Tanioka, M. and Hori, M. (2016). Extraction of Useful Knowledge for Making Roster by Analyzing Nurse Scheduling Data and Incident Data.In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5 HEALTHINF: HEALTHINF, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 383-388. DOI: 10.5220/0005776303830388

@conference{healthinf16,
author={Koichiro Okada. and Masanori Akiyoshi. and Yukie Majima. and Hiroe Takahashi. and Sayuri Tanaka. and Misae Tanioka. and Miwako Hori.},
title={Extraction of Useful Knowledge for Making Roster by Analyzing Nurse Scheduling Data and Incident Data},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5 HEALTHINF: HEALTHINF, (BIOSTEC 2016)},
year={2016},
pages={383-388},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005776303830388},
isbn={978-989-758-170-0},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5 HEALTHINF: HEALTHINF, (BIOSTEC 2016)
TI - Extraction of Useful Knowledge for Making Roster by Analyzing Nurse Scheduling Data and Incident Data
SN - 978-989-758-170-0
AU - Okada, K.
AU - Akiyoshi, M.
AU - Majima, Y.
AU - Takahashi, H.
AU - Tanaka, S.
AU - Tanioka, M.
AU - Hori, M.
PY - 2016
SP - 383
EP - 388
DO - 10.5220/0005776303830388

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