Timing errors and temporal uncertainty in clinical databases-A narrative review.

Area of Science:

• Clinical informatics
• Biomedical engineering
• Data science

Background:

• Establishing causality in clinical settings relies on accurate event sequencing.
• Unsynchronized clocks and diverse data sources complicate timestamp reliability in critical care.
• Current clinical models may not adequately address timestamp inaccuracies with high-frequency data.

Purpose of the Study:

• To review factors affecting timestamp accuracy and precision in clinical settings, especially critical care units.
• To introduce the concept of temporal uncertainty.
• To propose a quantitative approach for modeling temporal uncertainty.

Main Methods:

• Narrative review of factors influencing timestamp recording.
• Exploration of clock synchronization, medical devices, data storage, algorithms, and human factors.
• Introduction and proposal of a holistic, quantitative model for temporal uncertainty.

Main Results:

• Identified multiple sources of timestamp errors including clocks, devices, data systems, algorithms, and human factors.
• Introduced the concept of temporal uncertainty as a critical factor in timestamp analysis.
• Proposed a quantitative approach to model and manage temporal uncertainty.

Conclusions:

• Timestamp accuracy and precision are critical for clinical causality and require re-evaluation.
• A holistic approach to modeling temporal uncertainty is necessary for enhanced model generalizability.
• Improved analytical outcomes can be achieved by addressing temporal uncertainty in clinical data.