Mapping Documentation Burden: Analyzing Centrality and Clusters among Flowsheet Measures and Templates Through...

Area of Science:

• Health Informatics
• Network Science
• Nursing Informatics

Background:

• Nursing flowsheets are critical for patient care but can contribute to significant documentation burden.
• Existing structures may be outdated, hindering efficient data capture and retrieval.
• Understanding the interconnectedness of documentation elements is essential for optimization.

Purpose of the Study:

• To apply network analysis (NA) to quantify and visualize documentation burden in nursing flowsheets.
• To identify key templates and measures contributing to this burden.
• To inform the optimization of nursing documentation structures.

Main Methods:

• Network analysis (NA) was employed to map relationships between nursing flowsheet templates and measures.
• Centrality metrics and edge weights were analyzed to identify influential nodes and connections.
• Community detection algorithms were used to reveal functional clusters within the network.

Main Results:

• The study identified an outdated flowsheet structure and highlighted specific templates and measures causing documentation burden.
• Highly repetitive, central hub, and intermediary nodes were pinpointed as key contributors.
• Consistently high centralities across multiple metrics indicated clear opportunities for streamlining documentation.

Conclusions:

• Network analysis provides a data-driven approach to understanding and addressing documentation burden in nursing.
• Optimization of documentation structures is necessary, especially with the integration of ambient technologies.
• Findings support the need for modern data structures to improve nursing workflow efficiency.