The Safety Implications of Information Technology in Nursing: Japanese Incident Data Analysis.


Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
24 Jul 2024
Historique:
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 25 7 2024
Statut: ppublish

Résumé

This study delves into the impact of Information Technology (IT) on nursing practice in Japan, focusing on patient safety within the 2021-2022 Japanese Medical Accident Report Data. The research aims to understand how IT factors contribute to nursing-related medical incidents in a healthcare landscape rapidly integrating IT. The study identifies IT-related incidents through a retrospective analysis of medical incident reports, primarily in nursing, by analyzing categorized data and free-text descriptions for IT-related keywords. The findings indicate significant IT-related issues, with 'Other EHR Related' problems (36%) and 'EHR Reporting' errors (25%) being the most prevalent. These incidents often involve challenges in patient identification and medication management. The study suggests improvements like enhanced verification processes and automated systems to mitigate these risks. Conclusively, it underscores the dual nature of IT in nursing: while it holds the potential to enhance patient care, it also introduces challenges that necessitate specialized informatics expertise to ensure its beneficial integration into nursing practices.

Identifiants

pubmed: 39049228
pii: SHTI240108
doi: 10.3233/SHTI240108
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

69-73

Auteurs

Shoko Miyagawa (S)

Keio University, Tokyo, Japan.

Yuyu Urata (Y)

Keio University, Tokyo, Japan.

Shizuka Watanabe (S)

Keio University, Tokyo, Japan.

Hiromori Sugihara (H)

Keio University, Tokyo, Japan.

Shinya Mitani (S)

Keio University, Tokyo, Japan.

Hiroki Fukahori (H)

Keio University, Tokyo, Japan.

Maxim Topaz (M)

Columbia University, New York, NY, USA.

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Classifications MeSH