Inpatient nurses' preferences and decisions with risk information visualization.

Area of Science:

• Health Informatics
• Nursing Informatics
• Human-Computer Interaction

Background:

• Clinical decision-support systems (CDSS) are crucial for managing acute clinical deterioration.
• Effective presentation of risk information within CDSS is vital for accurate clinical decision-making.
• Nurses' preferences and understanding of risk data significantly impact CDSS usability and effectiveness.

Purpose of the Study:

• To evaluate the influence of four distinct risk information formats on inpatient nurses' preferences and decisions within an acute clinical deterioration CDSS.
• To identify optimal methods for presenting quantitative risk data to nurses to enhance clinical judgment.

Main Methods:

• A comparative usability evaluation was conducted in a simulated setting.
• Qualitative data were gathered using think-aloud methods.
• Quantitative data were collected by assessing nurses' actions in response to three patient scenarios presented with different risk information formats.

Main Results:

• The probability format was preferred by a majority of nurses (n=6) over relative risk ratios (n=2), absolute differences (n=2), and number of persons out of 100 (n=0).
• Nurses favored trend graphs with average lines and consistent color-coding, while disliking excessive text and confidence intervals.
• The probability format demonstrated greater concordance in nurses' decision-making compared to other formats.

Conclusions:

• Presenting risk information as probabilities, supplemented by trend graphs, offers valuable insights for designing effective CDSS for inpatient nurses.
• Future CDSS development for nurses should prioritize probability-based risk displays and graphical trend representations for improved clinical decision support.