Observation chart design features affect the detection of patient deterioration: a systematic experimental evaluation

Area of Science:

• Healthcare Informatics
• Human Factors Engineering
• Clinical Observation

Background:

• Observation chart design influences the speed and accuracy of detecting abnormal patient data.
• The specific contributions of individual design features remain largely unexplored.

Purpose of the Study:

• To systematically evaluate how specific design features of observation charts with early-warning scoring systems affect the detection of patient deterioration.
• To determine the impact of data-recording format, scoring-system integration, and scoring-row placement on user performance.

Main Methods:

• A 2x2x2x2 mixed factorial design was employed, varying data-recording format, scoring-system integration, and scoring-row placement.
• 205 novice chart-users completed 64 trials using real patient data presented on various chart designs.
• Response times and error rates were recorded to assess performance across different design configurations.

Main Results:

• Drawn-dot data recording and integrated color-based scoring systems led to faster responses and fewer errors compared to written numbers and non-integrated tabular systems.
• Response times varied based on scoring-row placement: faster with grouped rows when scores were absent, and faster with separate rows when scores were present.
• The presence or absence of scores also influenced response times and error rates.

Conclusions:

• Individual design features of observation charts demonstrably impact novice users' ability to detect patient deterioration.
• Empirical evaluation of chart designs is crucial for optimizing clinical observation tools and improving patient safety.