Assessing Patient Trust in Automation in Health Care Systems: Within-Subjects Experimental Study
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View abstract on PubMed
Summary
This summary is machine-generated.Patients trusted semiautomation and no automation more than full automation in a cardiac risk assessment tool. Trust also increased with higher patient risk severity, highlighting the need for human-centered design in healthcare automation.
Area Of Science
- Medical Informatics
- Human-Computer Interaction
- Artificial Intelligence in Healthcare
Background
- Healthcare technology and automation significantly impact patient outcomes.
- Increasing integration of smart automation in healthcare work systems.
Purpose Of The Study
- Investigate patient trust in an automated cardiac risk assessment tool (CRAT).
- Compare trust levels across different automation modes (none, automation-only, semiautomation) in a simulated emergency department.
Main Methods
- Within-subjects experimental design comparing three CRAT automation modes.
- Participants rated trust (1-10) for CRAT risk classifications across automation conditions.
- Simulated symptoms were entered, and CRAT automatically classified risk levels.
Main Results
- Semiautomation was trusted significantly more than automation-only (P=.002).
- No automation was trusted significantly more than automation-only (P=.03).
- CRAT trust was significantly higher in high-severity scenarios compared to medium-severity (P=.004).
Conclusions
- The human element is crucial in designing automated healthcare technology.
- Emphasizes the need to consider human factors when integrating automation and AI into patient care delivery.
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