A Study on the Utility of Text Mining Techniques for Analyzing Near-Miss Incidents

A Study on the Utility of Text Mining Techniques for Analyzing Near-Miss Incidents - A Study on the Utility of Text Mining Techniques for Analyzing Near-Miss Incidents

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

JPRN

Registry ID

JPRN-UMIN000056209

Enrollment

Registered

2024-11-30

Start date

2024-12-01

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Since near-miss reports are the focus of this study, specific disease names are not applicable.

Interventions

A pilot study will be conducted with two participants to determine an appropriate sample size for the main study. Using the difference between the two groups and the standard deviation obtained from t

near-miss&quot

incident reports will be prepared. Both sets will be analyzed using text mining techniques and manual methods. The primary outcome measure will be the accuracy of the analysis, while the secondary out

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Clinically experienced nurses without a specialization in patient safety.

Exclusion criteria

Exclusion criteria: Nurses specializing in patient safety.

Design outcomes

Primary

Measure	Time frame
Percentage of correct responses to near-miss report analysis	—

Secondary

Measure	Time frame
Time required to analyze near-miss reports	—

Countries

Japan

Contacts

Public ContactFurukawa Taishi

Osaka University Graduate School of Medicine, Division of Health Sciences Research Laboratory of Peripatetic Management

u094295d@ecs.osaka-u.ac.jp06-6879-5111

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026