Association of Data Integration Technologies With Intensive Care Clinician Performance: A Systematic Review and...

Area of Science:

• Critical care medicine
• Human factors engineering
• Health informatics

Background:

• Intensive care units (ICUs) generate vast amounts of data, increasing exponentially.
• The benefits of displaying multiparametric, high-frequency data are not well understood.
• Poorly designed data integration and visualization technologies (DIVTs) may cognitively burden clinicians, hindering decision-making.

Purpose of the Study:

• To systematically review and summarize evidence on user-centered DIVTs and their association with intensive care clinician performance.
• To assess the impact of DIVTs on cognitive workload and decision-making processes.

Main Methods:

• A systematic review and meta-analysis of studies published between 2004 and 2016.
• Searched MEDLINE, Embase, Cochrane, PsycINFO, and Web of Science.
• Included studies involving intensive care clinicians, viable DIVTs, and quantitative decision-making results.

Main Results:

• Twenty studies (16 experimental, 4 survey-based) were included.
• DIVTs showed improvement over paper records in self-reported performance, mental demand, and temporal demand.
• Electronic displays, tabular displays, and novel visualizations reduced cognitive workload compared to paper.

Conclusions:

• DIVTs are associated with improved data integration and consistency.
• Further research is required to identify optimal visualizations for reducing cognitive workload and enhancing ICU decision-making.
• Standardizing human factors testing for DIVTs could accelerate the development and selection of effective technologies.