Risk Factors Preventing Immediate Fall Detection: A Study Using Zero-Inflated Negative Binomial Regression.

Area of Science:

• Healthcare safety research
• Patient fall analysis
• Clinical risk management

Background:

• Patient falls are a common hazard in healthcare facilities.
• Timely fall detection and intervention are critical for mitigating patient harm.
• Understanding factors influencing fall detection time is essential for improving patient safety.

Purpose of the Study:

• To identify factors affecting the time taken to detect patient falls.
• To analyze patient and hospital characteristics associated with delayed fall detection.

Main Methods:

• Retrospective analysis of 3,470 fall cases from the Korea Patient Safety Reporting and Learning System.
• Utilized zero-inflated negative binomial regression and logit models for data analysis.

Main Results:

• Female patients aged 60-69 and evening nursing shifts were associated with delayed fall detection.
• Hospital type (tertiary vs. general/hospitals) and shift comparisons also revealed significant influencing factors.
• The study identified specific risk factors contributing to prolonged fall detection times.

Conclusions:

• Findings help nurses recognize patient and hospital factors linked to delayed fall detection.
• Recommendations include patient-specific strategies (e.g., age) and improved nurse staffing.
• Enhancing nurse staffing is vital for immediate detection of patient falls.