Developing a minimum dataset for nursing team leader handover in the intensive care unit: A focus group study

Area of Science:

• Nursing
• Intensive Care
• Patient Safety

Background:

• Limited structured tools exist for nursing handover in intensive care units (ICUs).
• Increasing demand for structured processes highlights a gap in current handover practices.

Purpose of the Study:

• To identify essential components for a minimum dataset for shift-to-shift handover by ICU nursing team leaders.
• To improve the quality and consistency of information transfer during critical care nursing transitions.

Main Methods:

• Focus group study involving senior registered nurses in a 21-bed medical/surgical ICU in Australia.
• Nominal group technique used to generate and prioritize minimum dataset items for nursing handover.
• Analysis of participant agreement on including specific content items from previous handovers.

Main Results:

• Seventeen senior nurses participated, agreeing ISBAR (Identify-Situation-Background-Assessment-Recommendations) is a useful handover tool.
• Key recommended items included patient identification, diagnosis, significant events, and future plans.
• Unit-specific information (ICU admissions, staffing) and patient details (infection status, end-of-life plan) were also deemed important.

Conclusions:

• A minimum dataset for ICU nursing handover should integrate ISBAR elements with unit and patient-specific data.
• This comprehensive dataset is crucial for maintaining continuity of care and ensuring patient safety.
• Standardizing handover information improves communication and reduces risks associated with shift changes.