A Nationwide Descriptive Epidemiological and Text-mining Analysis of Incidents and Adverse Events Involving Clinical Engineers in Japan.

Authors

Ryo Sato, Keizo Wauchi, Hirohito Imada

Published in

Journal of patient safety. Aug 12, 2026. Epub Aug 12, 2026.

Abstract

Although clinical engineers (CEs) play essential roles in medical device safety management, analyses of CE-related safety events remain limited. This nationwide study characterizes CE-involved incidents and adverse events and identifies priority areas for improvement.
From 162,837 Japan Council for Quality Health Care patient safety reports (2010-2024), CE-related reports were retrieved by keyword searches across all columns and deduplicated by ID. Incidents were defined as events with no, minor, or unknown patient impact, whereas adverse events involved death, residual disability, or unexpected treatment beyond what had been anticipated. Two reviewers independently screened free-text descriptions to confirm CE involvement, and any discrepancies were resolved by a third reviewer. The final data set comprised 1845 CE-involved reports: 1484 incidents and 361 adverse events. Descriptive statistics and text mining were applied.
Cases were reported on weekdays in dialysis rooms, operating rooms, and intensive care units. Male patients were affected in 65.8% of incidents and 59.8% of adverse events; patients aged 70 to 79 years were most affected. Incidents most often involved CEs with 0 to 4 years' experience (35.2%); adverse events, those with 5 to 9 years' experience (29.1%). Co-occurrence network analysis identified clusters centered on multidisciplinary collaboration and device operation (case descriptions), verification and device setup (contributing factors), and verification and inspection (improvement measures).
Reported CE-related events most frequently involved elderly male patients and early-career CEs, with recurring vulnerabilities in device setup, connection, and verification. Rather than relying on human vigilance, prevention requires workflow standardization, technology-assisted verification, and supervision of junior staff.

PMID:
42599774
Bibliographic data and abstract were imported from PubMed on 15 Aug 2026.

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